Home
Blog
Business Analytics
What are Sampling Techniques? Different Types and Methods

What are Sampling Techniques? Different Types and Methods

Updated on 25 October, 2024

14.03K+ views

• 15 min read

Table of Contents

What is Sampling?
Major Types of Sampling Methods
Different Types of Sampling Techniques
Factors While Choosing Probability and Non-Probability Samples
Difference Between Probability Sampling and Non-probability Sampling Methods
Importance of Sampling
Important Terminologies Need to Know
Conclusion

Data is the backbone of the majority of what researchers and data scientists do, and they require data to undertake experiments, analyze scenarios, and test ideas. The data samples come from the study population, and samples are the selected portion of the data that represent the whole population. However, dealing with enormous amounts of data is one of the main challenges in data analytics. It is unnecessary and even impractical to investigate the entire population when researching a specific group.

Data sampling is the process of analyzing data from a small group of individuals in a larger group. Data sampling allows you to research using various sampling techniques in data analytics without looking at the complete dataset. But what is the sampling technique? Essentially, it's the methods used to obtain a subset of data from a larger set for analysis. However, It is crucial for a person with a career to make sense of data, navigate it, and use it to impact a world filled with data. upGrad is an online platform focused on providing outcome-based immersive learning experiences to learners. Dive deep into the world of sampling and similar concepts by pursuing an Executive PG Program in Business Analytics from LIBA.

What is Sampling?

Statistics defines sampling as the process of gathering information about a population from a subset, like a selected individual or a small group and analyzing that information to study the whole population. The sample space constitutes the foundation of data which in turn is responsible for determining the accuracy of the study or research. Sampling, however, is not as simple as it seems. To land an accurate result, the sample size needs to be accurate, followed by implementing the right sampling methods based on the sample size. based on sample size.

Sampling Steps

An analyst needs to follow certain steps in order to reach conclusions from a broader perspective. The Sampling steps include the following -

Step 1: Identity and clearly define the target group/population.
Step 2: Create a specific sampling frame.
Step 3: Select the right sampling methods to be used.
Step 4: Specify the sample size.
Step 5: Collect the required sampled data.

Major Types of Sampling Methods

There are two types of sampling methods used in market action research -

1. Probability Sampling

In the probability sampling approach, a researcher selects a few criteria and randomly selects individuals from a population. Using this selection parameter, each member has an equal chance of participating in the sample.

2. Non-Probability Sampling

In this type of sampling, randomly chosen participants are used by researchers. This type of sampling is not a set or predetermined selection procedure. As a result, it is difficult for all parts of a population to have equal chances of being included in a sample.

The expert-designed Bootcamp for Data Science can help you pursue your dream career in data science with comprehensive real-world skills and knowledge.

Different Types of Sampling Techniques

1. Probability Sampling

To choose and reach every unit in the population, probability sampling is typically favored when conducting large-scale investigations, particularly when a sample frame is available. We can measure the standard deviation of estimations, create confidence intervals, and formally test hypotheses using probability sampling.

The different sampling methods in probability sampling include:

A. Simple random sampling

Simple random sampling gives each member of the population an equal chance of being chosen for the sample. It's similar to drawing a name out of a bowl. Simple random sampling can be performed by anonymizing the population, for example, assigning a number to each object or person in the population and selecting numbers randomly.

Simple random sampling eliminates any bias from the sampling process and is inexpensive, simple, and quick to use. It also provides the researcher with no means of control, increasing the likelihood that unrepresentative groupings will be chosen randomly.

Applications

Lottery techniques,
Split and Train in machine learning.

Advantages

Little bias due to the random nature of the sample collection
Given the usage of random generators, sample selection is straightforward.
Due to representativeness, the findings can be broadly interpreted.

Disadvantage

All responders' potential availability might be expensive and time-consuming.
Huge sample size

B. Cluster sampling

Cluster sampling involves selecting portions of the target population randomly from groupings rather than from single units. These might be already established groupings like residents of particular postal codes or students who attend a particular academic year.

However, in the case of a two-stage cluster sampling, the cluster can be randomly chosen in the first stage, and then the cluster can be randomly chosen again in the second stage.

Applications

One Stage Cluster
Two Stage Cluster

Advantages

Reduces time and money.
Practical and easy to use.
Larger sample sizes can be used.

Disadvantage

Increased errors in sampling
The sample frame's variety might not be well reflected.

C. Systematic sampling

In systematic sampling, sometimes called systematic clustering, only the first item is subject to random selection. Afterward, every nth thing or person is chosen according to a rule. Although there is some element of randomness, the researcher may control the frequency at which things are chosen, ensuring that the picks won't unintentionally group.

Applications

Quality Control:
To statistically check the quality of their goods, industrial companies frequently utilize systematic sampling. Here, a sample is gathered by periodically grabbing something from the present production stream.
Auditing:
The most obvious method to sample an account list for an audit of savings accounts is to look for conformity with accounting processes.

Advantages

Cost- and time-effective
increases the sample's distribution across the population.

Disadvantage

It is important to know the full population.
Probable sample bias in case the dataset contains periodic patterns.

D. Stratified random sampling.

Stratified sampling uses random selection within established groupings. Knowing information about the target population helps researchers stratify it for research purposes. Although stratified sampling offers advantages, it also raises the issue of subdividing a population, increasing the chance of bias.

Applications

The three types of stratified random sampling are:

Proportionate:
When compared to the overall population, the sample size for each stratum in this method is proportionate to the number of the stratum's population.
Disproportionate:
A proportionate stratified random sampling differs from a disproportionate stratified random sampling only by its sampling fraction. Disproportionate sampling results in different sampling fractions for different strata.
Optimal:
Variable standard deviation determines the size of these strata in optimal stratified random sampling.

Advantages

A greater percentage of all groups represented.
The estimations can be as precise if there is uniformity within strata and variation across strata.

Disadvantage

Complex methodology
Possibly more costly and time-consuming
Requires understanding of strata membership.

Check out our free courses related to upskill yourself.

2. Non-Probability Sampling

Non-probability sampling techniques are selected when the precision of the results is not crucial. Non-probability sampling doesn't need a frame, is affordable, and is simple. The bias in the results can be lessened if a non-probability sample is appropriately implemented. Making assumptions about the entire population is hazardous to make, according to the fundamental drawback of non-probability sampling.

The different types of sampling techniques in non-probability sampling include:

A. Convenience sampling

The simplest sampling technique is convenience sampling, where participants are picked up based on their availability and desire to participate in the survey. The sample could not be representative of the population as a whole. Hence the results are subject to severe bias.

Applications

This type of sampling technique is usually conducted in offices and social networking sites. Example of sampling techniques includes online surveys, product surveys etc.

Advantages

Obtaining a sample is comparatively easy.
Cost-effective
Participants are easily accessible.

Disadvantage

Results cannot be generalized.
Possibility of an imbalance in the population's representation
Rise of substantial prejudice or biases in the sample frame

B. Judgmental or purposive sampling

In judgment (or purposeful) sampling, a researcher uses judgment to select individuals from the population to take part in the study. Researchers frequently think they can use good judgment to gather a representative sample while saving time and money.

There is a likelihood that the results will be extremely accurate with a small margin of error because the researcher's expertise is essential for establishing a group in this sampling approach.

Applications

This sampling method is used for a small group of chosen groups.

Advantages

Relatively inexpensive and less time consuming
Enables researchers to directly contact their target market.
Near-real-time outcomes

Disadvantage

Risk of the researcher making mistakes in judgment
Bias levels are high, and dependability is low.
Difficulty in generalizing study results

3. Snowball sampling

This sampling technique entails primary data sources proposing other prospective primary data sources that may be employed in the study. To create more subjects, the snowball sampling approach relies on referrals from the original participants. As a result, using this sampling technique, sample group members are chosen by chain referral.

When examining difficult-to-reach groups, the social sciences frequently adopt this sampling methodology. As more subjects who are known to the existing subjects are nominated, the sample grows in size like a snowball. For instance, participants can be asked to suggest more users for interviews while researching risk behaviors among intravenous drug users.

Applications

Three sub-parts of snowball sampling include

Linear snowball sampling:
Only one subject is recruited, and the subject only makes one referral.
Non-discriminatory exponential snowball sampling:
One subject is recruited, and that one subject offers several references.
Exponentially discriminative snowball sampling:
One subject is recruited, who generates several references. However, only one topic is chosen from the recommendations.

Advantages

Researchers can access uncommon subjects in a certain community.
Inexpensive and simple to execute.
The additional subjects can be recruited without the assistance of recruiting staff.

Disadvantage

It's possible that the sample isn't representative.
Bias in sampling might exist.
It might be challenging to infer conclusions about the wider population with certainty since the sample is liable to biases.

D. Quota sampling

Quota sampling is the most used sampling technique used by most market researchers. The survey population is split up into subgroups that are mutually exclusive by the researchers. These categories are chosen based on well-known characteristics, qualities, or interests. The researcher chooses representative samples from each class.

Quota sampling is carried out in the following steps -

Separate the population into distinct subgroups.
Determine the percentage of auxiliary groupings in the population.
Choose unique subjects for every group of subgroups.
Make sure the sample represents the population.

Applications

Controlled quota sampling:
This limit the samples that researchers can choose by introducing certain restrictions.
Uncontrolled quota sampling:
In uncontrolled quota sampling, a researcher is allowed to select the individuals of the sample group.

Advantages

Cost-effective
Independent of sample frames
Provides researchers with the opportunity to study a particular subgroup.

Disadvantage

Possibility of an oversized sample
Impossible to calculate the sampling error.
Researchers' incompetence and/or lack of experience may lead to biases and substandard work.

Learn business analytics courses online from the World’s top Universities. Earn Masters, Executive PG Programmer Certification, or Global Master Certification to fast-track your career.

Factors While Choosing Probability and Non-Probability Samples

To achieve the objectives of the study accurately, it is critical to pick a sampling technique carefully for every research project. However, it is important to note that different sampling methods require different elements to form the sample frame. The efficiency of the sample depends on several variables, which include types of sampling methods require different elements to form the sample frame. The efficiency of the sample depends on a number of variables, which include:

To answer a research question, the sample size should be large enough but not so large that it becomes inefficient to sample.
The margin of error.
Depending on the study or use case, determine the best sampling method.
Deviate from any pre-established sample guidelines to rule out biases.
Omit hard-to-reach target groups.
Low response rates.

Difference Between Probability Sampling and Non-probability Sampling Methods

The various sampling techniques in research and their subtypes have already been considered. To summarise the entire subject, however, the key distinctions between probability sampling techniques and non-probability sampling techniques are as follows:

	Probability Sampling	Non- Probability Sampling
Sampling techniques definition	This is a sampling approach in which samples from a larger group are picked using a method based on probability theory.	This is a sampling strategy where samples are chosen by the researcher based on their own assessment as opposed to random selection.
Alternate Name	Random sampling	Non-random sampling
Nature	Conclusive	Exploratory
Selection of Population	Random selection	Arbitrary selection
Sample	Since this sampling is conclusive, it follows definitive sampling techniques.	Since this sampling is arbitrary, the sample representation is often biased.
Total time taken	Takes a longer time to complete because the research structure establishes the specified selection criteria before the market research investigation.	As none of the sample nor the sample's selection criteria are unstructured and ambiguous, this form of the sampling procedure is quick.
Results	Entirely unbiased and conclusive	Entirely biased and speculative
Hypothesis	Before the investigation ever starts, there is a guiding hypothesis, and the goal of probability sampling is to support that hypothesis.	In non-probability sampling, the hypothesis is created after the research study has been completed.

Importance of Sampling

In data analytics, sampling is the process of selecting a representative subset of a larger population. Sampling is a relatively easier technique to study a population closely from drawn samples. "What is sampling techniques in research?" is a common question among budding researchers. Sampling helps an analyst determine a given population's characteristics more cost-effectively and practically.

Sampling aims to collect data that can be used to draw conclusions about the wider population. There are many reasons why sampling is important in data analytics -

Sampling allows the data analysts to work with a smaller dataset, which can be more manageable and easier to work with.
Sampling can help to ensure that the data is representative of the population as a whole, which is important because it means that the conclusions drawn from the data are more likely to be accurate.
Sampling can help to reduce bias in data analysis. This is because Sampling allows analysts to select a representative subset of a population, which can help to reduce the skew that may be present in the data.
Sampling is an important tool that helps analysts to collect accurate and reliable data.

Acquire the deeper understanding of sampling analysis with the Business Analytics Certification Program from upGrad.

Important Terminologies Need to Know

1. Population

The population in statistics is the entire group of items from which a sample can be drawn. The population can be defined in terms of geographical location, age, gender, occupation, etc. A population can be very large, making it impractical or impossible to study all group members.

2. Sample

A sample is a set of data collected and used to determine the population parameters. Once the sample has been selected, data can be collected and analyzed in order to make inferences or predictions about the population as a whole.

3. Sampling

Sampling is the process of selecting a representative group from a larger population. The main purpose of sampling is to provide information about a population that can be used to make inferences or predictions about that population.

Conclusion

Research and surveys require a sample from a large population. Sampling is a great way to achieve that. As many might wonder, "What is sampling techniques?", it's essential to know that sampling techniques vary depending on the type of results that one wants. It is important to remember that different sampling techniques should be applied according to the case taken; keeping this in mind, we must choose the appropriate sampling techniques. You would have a highly accurate (and time-consuming) undertaking on your hands if you could ask everyone in a population to participate in your study and have everyone respond. You would have a similarly accurate effort if you could ask every single person in a population to participate and have each one respond.

But since that isn't practicable, sampling provides a "good enough" option that trades some accuracy for convenience and usability. How well you account for bias, non-sampling error, and sampling error in your survey design will determine how much precision you lose. upGrad is a trusted online platform dedicated to skill-based learning modules. If you want to learn more about business analytics, you may check out Job-ready Program in Business Analytics, which is offered by upGrad. It offers a variety of learning resources, including live faculty engagement, interactive discussion boards, quizzes, and assignments, career counseling, interview preparation, and much more. Get started with this course right away to launch a successful business analytics career.

Join our business analytics programs from top universities and gain the expertise to harness data effectively, empowering you to make impactful business decisions.

Business Analytics Programs from Top Universities

Business Analytics Certification Programme	Busines Analytics EPGP - LIBA
Professional Certificate Program in Data Science and Business Analytics	Master of Science in Business Analytics
Global Master Certificate in Business Analytics
Busines Analytics Certification - upGrad

Frequently Asked Questions (FAQs)

1. Why is the sampling technique important?

In statistical analysis, sampling techniques meaning is the process of selecting a specified number of observations from a larger population. Depending on the sort of study being done, a variety of methods, including systematic sampling and simple random sampling, may be employed to draw samples from a broader population.

2. What are the limitations of sampling?

Certain limitations of sampling techniques include the following -

Probability of biased results
Selecting a good sample frame can be difficult at times
Different sampling techniques demand different time frames

3. What is data sampling in data science?

Data sampling in data science is a statistical analysis approach used to pick, move, and analyze a representative selection of data points in order to spot trends and patterns in the larger data set being looked at.

4. What is your salary as a data scientist?

The salary range of a data scientist can be anywhere between ₹4 Lakhs to ₹24 Lakhs annually. The average salary of a data scientist in India is ₹11 Lakhs per annum.

5. Is data science a good career?

With the rapid growth of automation and technology in business modules, data scientists are very much in demand, which is projected to grow even more in the coming years. So it can be said that data science is a very promising career with tremendous growth opportunities shortly.

SUGGESTED BLOGS

5.97K+

Career Options in Business Analytics

Data and business analytics are integral when it comes to tech companies across the world. In recent times, thanks to the big data boom, over hundreds of terabytes of data is generated by 6 billion connected devices, every hour throughout the world. Such massive data numbers need to be churned and derive original and meaningful insights for the companies to stay ahead of each other in the industry. This is precisely where the business analytics professionals come in! So what exactly does a business analytics professionals do? In a nutshell, these individuals keep a close watch on the entire life cycle of data – right from data mining, data analysis, predictive modeling, and data testing. Apart from this, business analytics professionals can play a huge role in decision making for the organization based on the trends found in the data. Meaning these people get to be drenched in data as well as taken seriously in those black-suited boardroom meetings! Given the continually expanding field of analytics – it has become a broad spectrum industry with abundant career options in business analytics. Plus, apart from the IT industry, there are several sectors – like banking, healthcare, automobiles, etc. which comes with their own set of opportunities in business analytics. As we said before, since data and analytics are united, this can let business analytics professionals easily blend in with some specialized streams like Machine Learning, Artificial Intelligence, etc. Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad To be precise, the business analytics professional roles include: Data Scientist Data Visualization Analyst Big Data Analytics Architect Big Data Engineer Financial Analyst Marketing Analytics Manager Business Intelligence and Analytics Consultant Analytics Associate Metrics and Analytics Specialist Database Administrator Fraud Analyst Retail Sales Analyst Statistician Image Credits According to a 2017 McKinsey report, there is going to be a shortage of more than 1.9 million data scientists and analysts in the USA in the next two years. And when it comes to India, according to this LinkedIn article, India shall have the highest number of business analysts by 2020. With such overwhelming numbers and growing demand, here is how to start a career in business analytics: Must read: Business analyst course free! In recent times, business analysts are one of the most promising professionals in the IT industry in India. And since their work demands a constant switching between analytics, decision making, and communication skills – having an engineering and mathematics background is essential. Apart from the former, the other skills required for a promising career in business analytics are: Curiosity Given the vast heaps of data and the possibilities, it comes with, that itself should be enough for you to keep going for the right solutions all the time. Analysis To extract meaningful conclusions from the data trends, it needs to be churned out based on strategies and relevant tools. This comes with good experience in the field along with an enhanced industry aptitude in Data analysis. Also check out: Job-ready Program in Business Analytics from upGrad Grasp over Tools and Methods If you have an aptitude in SAS and MS-Excel, then you need to get it in alignment with your IQ to reach to the relevant insights the chunks of data is trying to present. Attention to Details Data Mining can be a daunting task and therefore can often result in distractions, losing track of the bigger picture and thus landing in irrelevant information. It with a keen eye to details, such situations can be averted. Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully At Ease with Numbers Data analysis requires fluency in mathematical formulas and calculations, so you have to be a pro in such situations. Our learners also read: Business Analytics Free Online Courses Scope of Business Analytics: The field of business analytics has been dynamically growing – allowing more and more people into the system as well as helping the company giants stay in the big game. It needs the correct focus, technology, and dedication to pull off effectively all the time. With the help of several high-end business analytics tools, companies like Deloitte, IBM, etc. come up with scaleable profit generation techniques each time. Since organizations rely heavily on the big data analysis to extract relevant data insights, this shall only grow in numbers in the coming years. Therefore the scope of a business analyst isn’t restricted to its core, but other places like: Big data analysis Quality Control and Assurance SDLC Business Process Modelling, etc Thanks to the upgrading to IoT (Internet of Things) and Big Data analytics, this combination technology shall witness an exponential surge in 2020 that can prove to be revolutionary for the business analytics industry in the long term. upGrad’s Certificate in Business Analytics from IIT Delhi on “Applying Business Analytics” can help you enhance your business performance and drive growth. Since the course is conducted 100% online, it doesn’t require you to compromise focus on business operations. So, book your seat now and avail the benefit of learning from world-class faculty and industry experts for the next seven months! upGrad’s Exclusive Business Analytics Webinar for you – How upGrad helps for your Business Analytics Career? document.createElement('video'); https://cdn.upgrad.com/blog/vivek-and-ayush.mp4 Join Job-ready Program in Business Analytics from upGrad to become a certified Business Analyst professional. Fast-track your professional career after graduation with this Business analytics course with placement assistance.

by Athul Uday

30 Aug'19

7.05K+

What Does a Business Analyst Do? Role, Qualification & Opportunities

What is Business Analysis? All businesses operate on a set of working procedures. An expansion from small scale businesses to large corporate houses, all systems run on a set of defined standard procedures. These rules can be aimed at an operational task-projection or from a business viewpoint. All departments in organizations work simultaneously to attain a singular goal of business development. The operating bullets define how tasks need to be done, by whom, and on what scale. The standard operating procedures (SOPs) or business models affect the outcomes of marketing campaigns. The ultimate objective is to increase business returns and benefit more with less cost. Business Analysis is when you dive deep into these SOPs and models to extract data and process ways to reason a project/campaigns success or failure. The analyst here works to establish data, recommend analytical stand-points, and implement changes. Learn Job-ready Program in Business Analytics from upGrad to become a certified Business Analyst professional. Fast-track your professional career after graduation with this Business analytics course with placement assistance. Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad Understanding a Business Analyst The profile of a business analyst is described best with a simple, classic example of comparing their role with a healthcare consultant. Doctors in the healthcare industry serve a primary responsibility to treat their patients. They apply methods in consultations and medications to prescribe. The process involves: Attending to their patient, Enquiring issues, Analyzing symptoms, Diagnosing results, and Prescribing medications Now, relate the points mentioned above with the role of a business analyst as one who: Identifies problem areas in a business process Determines responsible factors Uses tools and techniques to formulate a solution Presents the recommendation in a data-driven method, and Reports the data-driven change to processes The responsibility of the doctor is to use their consultation skills to treat the responsible agent, causing sickness. Similarly, the responsibility of a business analyst is to use their data analysis skills to find solutions to business problems. Must read: Learn business analytics online free! Describing the Roles of Business Analyst The position of a Business Analyst in an organization demands the use of data analytics to bridge the gap between information technology (IT) and the business. Your business might be working on a problem that is not bringing the desired results. This is where the Business Analyst (you) will enter: Help the organization understand their business problem and the need to work on a particular project (if data says it is required) Provide solutions backed with data and business models to make the stakeholders understand the areas that would need changes Document those needs and requirement to implement into the business Come up with new plans to increase returns By socializing with users and business leaders, you will understand how a data-driven change can alter effectiveness in existing processes. You will be needed to evaluate your idea’s technological feasibility and the company’s financial support. Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully Qualifications of a Business Analyst You need to have a minimum of a bachelor’s degree to be qualified for the Business Analyst job profile. Other educational qualifications will vary with diverse industries and job requirements. Learn how to become a business analyst. Degrees in finance, accounting, or business administration prove to be useful to satisfy job demands. It can pertain individually to business administration or be general to a distinct industry. Be it a health sector or software IT group, the requirements on skill set and educational background will reflect demand. Specific additional courses and certifications on Business Analysis programs will prove to be useful to showcase knowledge of the subject matter. Our learners also read: Business Analytics Free Online Courses upGrad’s Exclusive Business Analytics Webinar for you – How upGrad helps for your Business Analytics Career? document.createElement('video'); https://cdn.upgrad.com/blog/alumni-talk-by-monalisha-dash.mp4 Skills Required The profile expects you to be functionally productive while juggling with cost constraints and reasonable ideas for higher output. To meet the demands of the Business Analyst profile, following skills will be expected: Organisational Skills Functioning in an organisation and collaborating with various departments Analytical Skills Data Analysis and Interpretation Business Process Re-engineering Remodelling processes and implementing changes in existing business plans Business Administration Concepts Basics of finance, accounting, marketing and operations Understanding technology and network models Engineering processes with the help of technological competence Cost-benefit Project Analysis Evaluating alternate decisions and analyzing outcomes Orientation to details Pricing and Budgeting processes require detailed inputs Writing Skills Documenting business plans with technical information for stakeholder’s ease in understanding Soft-Skills Communication Ability to think out-of-the-box Problem-solving Being an Influential Leader Interpersonal skills Presentation Skills Demonstrating chosen pathways to valuate maximum profit Technical Skills It is not necessary to be a computer programmer for a business analyst profile. The job demands intermediate computer operating skill with the use of spreadsheets, database programs, and software. Learn more about Business analyst skills. Industry Opportunities With the upscaling rise in demand, various industries are opening up positions of Business Analysts. The impressive profile and job description are leading many professionals to opt for this role as the next step of their career growth-plan. Some of the industries witnessing a rising demand of business analysts are: Government Organisations and Public Sector Information Technology Small-scale businesses Multinational Business Corporations Health and Hospital Services Finance and Banking Institutions Consulting Firms Business Analyst Job Description The business analyst works incorporating technology and data-driven analysis to offer business solutions. They report the same to responsible executives and stakeholders with the following tasks: Planning and Monitoring Business Plans Defining Role Establishing the scope of the business and IT projects Levelling out problem areas at each step in the organisation’s workflow Analysing Variance Investigate differences between actual and planned behavior, sales difference Initiate changes from the conventional and existing business processes Budgeting and Pricing Setting aside financial asset for a business plan Defining each business step’s price Business Forecasting Predicting future developments in sales, expenditures and profits Preparing with adjustments for unexpected events Obligations on Accountability Your business could be a product, service, software or hardware based. Working on data sets, all that is required from you is to improve efficiencies and add value to the business. Your duties as a business analyst include: Quality Assurance Project Management Conduct surveys on projects Alter existing processes to increase returnsFormulate business cases Carry out statistical analysis Take steps to make the internal departments for effective Product Management Modify product and service offerings Collaborate technical and process re-engineering Present data-driven recommendation on changes Invent new systems Reasoning solutions on the scale of financial structure and feasible operations, you will be responsible for: Design test cases on business plans Review cases to optimise returns Manage the scope of business projects Analyse acceptance of the project under review Instal methods to modify changes Deploy mechanisms to increase returns Expectations on know-how A lot is expected here, from inspiring others to devising plans to scale heights in business growth. Following are some of the requirements from the profile of a business analyst in the organisation: Understanding how the business in the particular organisation works and operational process flows Working on multiple projects to meet deadlines Collaborating with project managers on the mission Brainstorming ideas to meet ends with multiple teams and stakeholders Documenting loopholes from standard procedures Re-evaluate opportunities on business returns Documenting processes to refine the problem that is to be solved Add details to the solution with technological inputs. Conclusion As leaders in growth, business analysts are required to indulge in various tasks of the organisation’s framework to be the catalysts for change. Companies across both IT and e-commerce sectors pay excellent compensation to deserving candidates who can add value to their organization. Apart from the regular educational qualifications and work experience, having certification in Job-ready Program in Business Analytics also helps in bagging jobs that offer high-level salaries.

by upGrad

23 Dec'19

5.99K+

How Business Analytics Help To Grow Business

In the past decade, thanks to the growing proliferation of smartphones and smart devices and the increasing adoption of Data Science technologies – AI, ML, Data Analytics, Business Analytics – the world has been churning out colossal volumes of data. And although we now sit on this data goldmine, raw data is of little or no value to us unless processed, analyzed, and interpreted. This is where Business Analytics enters the scene. What Is Business Analytics? Business Analytics focuses on analyzing large volumes of historical data using a combination of diverse technologies like information technology, statistical analysis, quantitative methods, and computer-based models to gain meaningful business insights. Companies and organizations use these insights to make data-driven, actionable decisions for the future. While statistical methods help extract the relevant patterns from within large datasets, computer-based models allow business owners to visualize the performance of different strategies and decisions under varying scenarios. In simple words, business analytics refers to the technique of employing different quantitative methods to extract meaning from data to make informed business decisions. As such, by analyzing past performances and delivering data-oriented results, business analytics enables companies to prepare for the future. This is particularly crucial in the present age when every business entity is looking to optimize their decision-making process to achieve the competitive upper hand. Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad Must read: Business analytics free online courses! What’s great about business analytics is that it offers a wide range of applications suited to almost every industry such as customer relationship management, financial management, inventory management, and marketing, banking, supply-chain management, human resource management, to name a few. Business Analytics involves three core methods Descriptive which interprets historical data to identify trends that can create value for a business. Predictive that leverage statistics to predict future outcomes. Prescriptive that uses a host of techniques to determine which outcome is likely to deliver the best results in a specific business scenario. What Benefits Do Business Analytics Bring To A Business? Here are the top seven benefits that business analytics brings to the table 1. It Promotes Informed Decision-Making As we mentioned, business analytics is all about uncovering insights from raw data and using it to influence business decisions positively. When companies can analyze their past performances, they get to identify missed opportunities and subpar strategies. Accordingly, they can improve their ongoing campaigns and future decisions. 2. It Improves Customer Experience The market is flooded with choices – the product/service you offer may be provided by ten other brands. So, why should a customer choose you? It all boils down to the quality of products and the degree of personalization you offer to your customers. Modern customers are all about products/services that are customized to suit their specific needs and preferences. Business analytics can help you understand the purchasing behavior, tastes, requirements, etc., of your buyer personas. Equipped with this data, you can extend highly-targeted offers/discounts, campaigns, and products to your target customers, winning their loyalty time and again. In the long run, the efforts you put into creating a unique customer experience boost the customer satisfaction factor significantly. Also check out: Job-ready Program in Business Analytics from upGrad Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully 3. It Improves Operational Efficiency Business analytics is one of the most vital tools for increasing operational efficiency. By analyzing the performance of your business processes, campaigns, marketing strategies, and business decisions, you can optimize the results. In other words, analytics helps paint a clear picture of what is working for your business and what is not. This allows you to fine-tune business operations and processes for enhanced performance and higher returns. 4. It Increases ROI Since business analytics enhances operational efficiency and improves decision-making, it inevitably creates new opportunities to increase the financial gains of businesses. According to McKinsey research, companies that use big data analytics witnessed a 6% increase in profits which can escalate to 9% provided steady investments are made in a five-year term. upGrad’s Exclusive Business Analytics Webinar for you – How upGrad helps for your Business Analytics Career? document.createElement('video'); https://cdn.upgrad.com/blog/vivek-and-ayush.mp4 5. It Helps Identify New Business Opportunities The potential of business analytics is not limited to identifying opportunities to boost decision-making and operational efficiency. Companies can use analytics to conduct market and competitor research to find out untapped opportunities such as new markets, new customer segments, new product ideas, etc. As new doors open, the potential to grow and earn more profits increases manifold. 6. It Doubles As An HR Tool While AI and ML have already revolutionized the hiring process across the industry, today, many companies are using business analytics in HR management. Data analytic can evaluate employee performance and assess their job satisfaction and willingness to upskill/take on additional responsibilities, and so on. This makes it easier for HR managers to determine the professional development of employees, make promotion decisions, and offer fair performance evaluations. 7. It Minimizes Risks By enabling business owners to make informed decisions based on concrete data including performance, customer behavior, and market trends, business analytics minimizes risks to a great extent. This, in turn, not only establishes a company as a leader in the market, but it also saves it from incurring financial losses. Our learners also read: Learn Business Analytics Free Why Study Business Analytics? As an increasing number of organizations realize the potential of data backed by different Data Science technologies, the demand for skilled professionals is also rising. Any business failing to take the data-driven approach is going to fall behind in the race. However, be it AI, or ML, or business analytics tools, these will not deliver tangible results if a company lacks the right talent. The global business analytics market continues to grow steadily as we speak, indicating that there’s a rapidly growing demand for certified business analytics experts. In fact, business analysis ranked as one of the most in-demand skills. Unfortunately, the demand far exceeds their supply, and while this is bad news for companies, it is great for aspirants who’re looking to build a career in Data Science. The proven pathway to entering the business analytics domain is by opting for a certification course or training program. For instance, the Global Master Certificate in Business Analytics is an excellent choice to broaden your domain knowledge and take your career to the next level. Taught by expert instructors of the Michigan State University, this 6-month course will teach you how to use data insights to improve business performance, enhance decision making, and craft long-term development plans. This course takes a holistic approach to business analytics by integrating business management, data engineering, and the natural sciences in the curriculum. Apart from mastering the fundamentals of data analytics, you will learn how to use various analytical and statistical tools like Tableau, R, and Microsoft Access. You can also Check out certification in business analytics from IIT Delhi. IIT Delhi is one of the top institutes in India and also one of the oldest IIT’s and is always excelled in giving highly industry-relevant courses, Now IIT Delhi has partnered with upGrad to get these top IIT Delhi courses online. They have a variety of other programs like Machine Learning, Executive Management Programme in Strategic Innovation, Digital Marketing and Business Analytics etc Learn Job-ready Program in Business Analytics from upGrad to become a certified Business Analyst professional. Fast-track your professional career after graduation with this Business analytics course with placement assistance.

by Rohit Sharma

30 Dec'20

5.54K+

8 Business Analytics Tips: Which Helps to Run Business Successfully

Business analytics is the process of extracting information and insights through statistical analysis of market trends, customer reactions, and past performance to drive better decision-making practices and help businesses achieve goals. In any industry, data analytics, intelligence and insights play a key role in driving a business’s success. There are tools and technologies to conduct iterative research and extract valuable information that can result in strategic planning and actionable decision-making. This doesn’t just influence the financial aspects of a business and streamline customer experience but also brings management professionals to effectively contribute to an organization’s success. In this article, we will explore the role of business analytics in business decision-making to gain an advantage in the competitive market. How Does Business Analytics Impact Business Success? Business analytics and insights aren’t just limited to implementing initiatives that maximize the efficiency of external factors impacting a business. It is also targeted at enhancing internal performance and quality by gaining a comprehensive understanding of the management system. This ensures timely availability of resources, better coordination, risk assessment and management, and improved customer experience. Must read: Business analytics free course! Here is how business analytics helps businesses become more strategic and achieve goals: 1. Visualize Long-Term Business Goals Statistical facts based on the evaluation of a company’s past performance, industry trends and future projections can help a business visualize long-term goals for the company. This is essential to ensure growth and retain a competitive edge in the market. When company CFOs, managers, executives and sales teams have direct access to business intelligence and “one view of the truth”, it accelerates the process of decision-making. Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad 2. Enhance Business Performance With streamlined data analytics in place, businesses have a comprehensive view of the human side of the equation that deals with how people process information and use it to implement a given task. Through this, companies can allocate their resources in a better fashion as per the skills, strengths and weaknesses of employees, and work on aspects that require improvement, so as to maximize internal performance. By staying on top of employee operations, companies can recognize inconsistencies in management, and work to streamline them and enhance productivity. It would also impact recruitments and reduce the cost of hiring. 3. Improve Risk Management Business analytics in business decision making help forecast aspects of management that can go awry in time. This allows businesses to implement practices to prepare for potential structured and unstructured issues by streamlining communication between departments and configuring improved risk management models. Based on this, businesses can then forecast risks with even more accuracy in future and eradicate potential crises by deploying necessary tools. 4. Identify Sales Opportunities Through data analytics, companies can conduct iterative studies on customer behaviour, their purchasing habits and favourable reactions, to identify sales opportunities. They can discover the most effective cross-sell and up-sell opportunities and use them to improve their sales decisions. Data analytics also provide comprehensive insight into the type of customers a business should be targeting. This can help sales teams recalibrate their sales strategies and tailor their acquisition and conversion plans accordingly. Also check out: Job-ready Program in Business Analytics from upGrad Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully 5. Identify New Business Opportunities Business professionals may recognize short-term trends, but the sustainability of a business depends on identifying new business opportunities and strategizing accordingly to ensure longevity. Business analytics gives a clear insight into the shifts in markets and allow businesses to determine which products must be updated. Such intelligence-based decisions result in profitable outcomes and enhance the growth potential of a company. They also help predict risks down the road, so key areas of concern can be improved to increase a business’s chance of success. upGrad’s Exclusive Business Analytics Webinar for you – How upGrad helps for your Business Analytics Career? document.createElement('video'); https://cdn.upgrad.com/blog/vivek-and-ayush.mp4 6. Improve Marketing Strategies By monitoring customer’s reactions towards promotions and marketing campaigns, a business can determine which campaigns to prioritize and devise strategies to capitalize on the most successful products and services. As per a study by McKinsey & Company, data insights and analytics positively impact marketing decisions and help drive productivity by 15-20%. Take Target’s “pregnancy prediction score” for instance, that analyzes the purchasing habits of a customer to ascertain how likely they are to be pregnant. Based on this, retailers decide the promotional coupons and discounts that will be sent to the customer. Predictive analytics is a common practice by companies to drive customer experience and foster reliability and loyalty with respect to their brands in a customer’s mind. This requires conducting investigative research in real-time, monitoring purchase habits, internet searches, and deducing fact-based conclusions to fine-tune marketing decisions. Based on these insights, sales teams can also collaborate with marketing departments to make quick and effective decisions. 7. Streamline Customer Service Data insights have a key role to play in decisions that directly impact the customer experience. By identifying patterns in customer reactions and studying the interactions between your employees and customers, a business can align their marketing strategies to drive profitable outcomes. These data simulations can help both marketing teams and the IT department to restructure budgets and devise campaigns that improve customer interaction as well as drive business goals. 8. Improve Financial Status When companies have a thorough insight into their profit margins and losses, incoming and outgoing transactions and finance sheets, they are well-positioned to evaluate the potential of their products and services. This helps eliminate cost concerns and identify revenue streams to improve the financial status of the company. Inconsistencies in inventory management also affect the profit margins of a company. An exhaustive view of ordering patterns, quantities, and prices can help reduce inventory costs and gain a stronghold on the finances of the company. Our learners also read: Learn Business Analytics Free Business Analytics in Business Decisions Business analytics puts companies in a position to streamline internal processes, be it HR, marketing/sales or supply chain, and help improve the relevance of their product offerings. It allows them to employ strategic decision-making at all levels to influence business operations. Businesses all around the world rely on data analytics and intelligence to retain a competitive advantage in the market. It is the need of the hour for companies to invest in data mining practices to stay relevant and in-demand. The good news is there are online courses on business analytics that anyone can take up and upgrade their skill set in a way that they become indispensable to an organization. Conclusion upGrad’s Global Master Certificate in Business Analytics from Michigan State University with separate courses on “Data Mining and Management Strategies” and “Applying Business Analytics” can help you enhance your business performance and drive growth. Since the course is conducted 100% online, it doesn’t require you to compromise focus on business operations. So, book your seat now and avail the benefit of learning from world-class faculty and industry experts for the next six months! Learn Job-ready Program in Business Analytics from upGrad to become a certified Business Analyst professional. Fast-track your professional career after graduation with this Business analytics course with placement assistance.

by Rohit Sharma

16 Feb'21

11.67K+

Scope & Future of Business Analytics in India: What Should You Do?

Even though businesses worldwide were increasingly adopting business analytics, artificial intelligence and agile delivery methods in their business practices before COVID-19 struck, the process has surprisingly accelerated post the pandemic. Business analytics, widely known for its diagnostic, predictive and prescriptive prowess, has gained tremendous traction in the last year as governments and healthcare institutions embraced this progressive approach to overcome organisational obstacles and provide long-lasting solutions. As per Mckinsey, business analytical capabilities are projected to create $9.5 trillion to $15.4 trillion annual economic impacts across nineteen industries worldwide, of which 40% can be credited to AI implementation. This article will analyse the scope of business analytics in India and shine a light on how business leaders have updated their approach towards business decision-making. Let’s first understand business analytics and look at the questions analytical techniques seek to answer. Also Read: What is business analytics – Career scope, Salary & Job Roles. What is Business Analytics (BI)? Business Analytics is the iterative and systematic analysis of a company’s statistical data to gain insights into the past performance records, ongoing business operations, and industry trends to foster strategic planning and data-driven decision-making capabilities and drive the growth of a company. Business Analytics is an investigative approach that seeks to answer the what, why, when and how of business operations. 1. Descriptive Analysis: Uses historical data to recognise trends, inconsistencies, or patterns used to profit an organisation. 2. Diagnostic Analysis: It is the analysis of an observed event to understand why it took place. It usually involves conducting test hypotheses to draw fact-oriented conclusions. 3. Predictive Analysis: It is the interpretation of information to forecast potential outcomes and improve risk assessment and management. 4. Prescriptive Analysis: It usually involves testing and comparing outcomes to determine which has the potential for success. Businesses employ business analytics as navigational tools to solve potential problems, streamline existing operations and invest in solutions that are most likely to assist in scalability and progress. Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad Our learners also read: Business analyst course free! Scope of Business Analytics As small to medium and large size businesses tap into the problem-solving prowess of business analytics, some business operations sections stand to benefit more than others. Forecasting demands, risk assessment, identifying potential disruptions in the supply chain, and providing support in crisis times are just a few scenarios where business analytics has proven to be a boon in India. Read: Business analyst career path and professional roles. To that end, we estimate the scope of business analytics is poised to tremendously impact the following business scenarios: 1. Customer Experience: Quality consumer experience is key to ensuring smooth business operations. By gaining a deep understanding of what type of customers frequent your business and what their purchase habits are like and studying their behaviours, companies can tailor their services to achieve customer gratification and ensure their loyalty to the brand. Business analytics provides businesses with this possibility and allows them to personalise their products and services to cater to customers. 2. Inventory Management: businesses can streamline supply chain processes and reduce overhead costs. Business analytics provides an understanding of the frequency and timing of orders, which products are in demand and how poised a company is to serve those demands, strategically planning their supply chain operations. It also provides businesses with the capability to scale their services sustainably. 3. Sales and Marketing: Companies can study customers’ reactions towards their marketing campaigns and product offerings to create targeted campaigns and identify the most effective cross-sell and up-sell opportunities. It involves investigating the age demographic a consumer falls into, their average income, what motivates them to make purchases to predict patterns, and trends in their purchasing behaviour. This helps businesses focus their product messages and launch timings to suit their customers’ requirements. 4. Hiring and Recruitment: Companies are keen on associating with HR officials with a background in data analytics and business intelligence. This ensures that HR specialists can analyse data to onboard skilled and professional employees who contribute to a company’s growth. It also helps save companies hiring and training costs. 5. Finance: Big data and business analytics allow companies to handle their finances more effectively. Insights on marketing spend, and a comprehensive view of incoming and outgoing transactions can help businesses improve their business decision-making abilities, so they allocate their resources more efficiently. McKinsey & Company’s study showed that an integrated analytics approach towards marketing expenditure could free up to $200 billion worldwide. Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully upGrad’s Exclusive Business Analytics Webinar for you – How upGrad helps for your Business Analytics Career? document.createElement('video'); https://cdn.upgrad.com/blog/alumni-talk-by-monalisha-dash.mp4 Also, check out: Job-ready Program in Business Analytics from upGrad Future of Business Analytics A business-focused approach to analytics has allowed companies to update the relevance of their product offerings, helping them maximise reach, discover business opportunities and tap into new revenue streams. It has also helped businesses provide optimised solutions to consumers, thereby enhancing customer experience. Take Walmart’s search engine for example, that at one point during the launch of NBC’s latest House season was witnessing a significant number of “house” related searches. Since the results displayed were based on Walmart’s internal data, including household items, doghouses, etc., customers who came to buy CD/DVD sets of House would abandon the check-out process without completing the purchase. Walmart noticed this increase in the ‘shopping-cart abandonment’ rate and successfully employed business analytics tools to reduce it by 10% to 15%. which was done with the help of external data from other search engines, including Twitter and Facebook. This is a common trend all over the world. Tech giants like IBM, Cognizant, and KPMG invest in analytical technologies and tools to yield ground-breaking results and drive unparalleled performance. This favourable attitude towards business analytics is one of the key developments in India, and businesses of all sizes are looking to connect big data to business intelligence to attain distinction in their respective industries. To that end, here are the changes we can expect to see in future: AI, Machine Learning and Big Data implementation will play a huge role in providing quality services and ensuring business progress. Data quality management is poised to become a crucial digital trend. As consumers become more conscious of privacy and receptive to personalised services, business analytics will pave the way for better and secure customer experience. Predictive and prescriptive analytical approaches will force companies to rethink traditional models favouring unconventional technologies that increase sustainability and chances of success. Business analytics is expected to significantly impact marketing, sales, customer experience, finance, risk management, HR, and social media practices, among others. Business professionals with an in-depth understanding of business analytics are better positioned to be industry leaders. They will have an edge in addressing short-term challenges and fulfilling long-term goals by constantly updating their descriptive and predictive analytical models to eliminate uncertainties and tap into new business opportunities. Certifications in business analytics courses will help business professionals attract favour from top companies in India and bolster their success chances. Equally valuable will be degrees in Data Science, and Machine Learning and Artificial Intelligence. Now you can also get certifications in business analytics from IIT Delhi. IIT Delhi is one of the top institutes in India and also one of the oldest IIT’s and is always excelled in giving highly industry-relevant courses, Now IIT Delhi has partnered with upGrad to get these top IIT Delhi courses online. They have a variety of other programs like Machine Learning, Executive Management Programme in Strategic Innovation, Digital Marketing and Business Analytics etc Our learners also read: Business Analytics Free Online Courses Adopting a Data-Oriented Mindset The COVID-19 pandemic has demonstrated that expeditious changes are both necessary and possible for a business’s sustainability. Companies that rely on fact-based insights to develop a vision for the future and are quick to adapt to evolving technological standards have the potential to be industry leaders. Conclusion To survive and thrive in a competitive environment, business professionals must invest in proven solutions and constantly upgrade their skills to stay ahead in the race. They must be able to analyse data and deduce profitable conclusions from it to strategise effective business plans. And a Master’s Degree in Business Analytics from a reputed university can bring you a lot closer to these goals. If you are looking to incorporate business analytics and intelligence into your skills set, upGrad x Michigan State University’s online Business Analytics program can help you. With uninterrupted access to world-class faculty and advanced technologies for six months, you stand to gain an undeniable competitive advantage that will benefit both your company and your career. Learn Job-ready Program in Business Analytics from upGrad to become a certified Business Analyst professional. Fast-track your professional career after graduation with this Business analytics course with placement assistance.

by Rohit Sharma

16 Feb'21

5.77K+

Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics

Businesses are always on the lookout for new things and technologies that can enhance their productivity or help them get greater results. One such domain is analytics. Analytics helps businesses in creating, implementing, and testing new strategies for various sections including customer acquisition, customer experience, business growth, financial management, and much more. However, because analytics is such a broad field, its subdivisions can get quite confusing especially when it comes to business analytics vs data analytics. Even though they are different from each other, people use these terms interchangeably. That’s why we’ll discuss the difference between business analytics and data analytics today. We’ll explore the distinctions between these two fields and understand why they are different from each other: Check out our business analytics courses to upskill yourself. Business Analytics vs Data Analytics: Definition The first difference between business analytics and data analytics is in their definitions. Both of them use data to help a business make better-informed decisions but they cover different sections of an enterprise. What is Business Analytics? Business analytics refers to the iterative exploration of an enterprise’s data while using statistical analysis techniques to get insights so they can make smart decisions with them. It is a subcategory of business intelligence that focuses on using financial analysis and reporting tools, data mining tools, and data visualization tools to figure out how to use data properly. The aim is to simplify data application for businesses to identify weaknesses, enhance value, and optimize costs for the current operations. Business analytics helps a business in solving its unique problems and so, is usually at the front of the pipeline. This is a huge distinction because data analytics focuses more on the backend of the business’s data use. In simple terms, business analytics uses data to help the business make smart decisions about its various aspects. It can help in nearly every section of a business including sales, finance, human resources, product development, customer service, etc. Must read: Business analyst course free! Explore our Business Analytics Programs from World's Top Universities Business Analytics Certification Programme Busines Analytics EPGP - LIBA Professional Certificate Program in Data Science and Business Analytics Master of Science in Business Analytics Global Master Certificate in Business Analytics Busines Analytics Certification - upGrad What is Data Analytics? Data analytics focuses on collecting and using large amounts of raw data to draw conclusions about it and gain valuable insights. Data analytics consists of analysis and categorising of data including sorting, cleansing, storing the data while identifying patterns in the same. One of the most popular aspects of data analytics is machine learning. Machine learning allows you to process huge amounts of data and find patterns that allow you to make accurate predictions about that field. It also helps you generate insights that solve complex business problems for your enterprise. Data analytics is vital for businesses as it helps them become more efficient and devise new strategies through making predictions. Business Analytics vs Data Analytics: Salary When we look at the average pay for both of these roles, we find that there’s a little difference between business analytics and data analytics. The average pay of a data analyst in India is INR 4.3 lakh per annum. Experience matters a lot in this field as an entry-level data analyst with less than a year’s experience gets INR 3.44 lakh per year including the average bonus, overtime pay, and additional benefits. A data analyst with one to four years of experience gets around INR 4.15 lakh per annum while a professional in this field with five to nine years of experience gets INR 6.73 lakh per annum on average. On the other hand, an experienced data analyst with more than 10 years of experience can get more than INR 10 lakh per annum on average. The average pay of a business analyst in India is INR 6 lakh per annum. A fresher in this sector makes around INR 3.5 lakh per annum while a business analyst with one to four years of experience gets INR 5.28 lakh per annum on average. Like most sectors, experience matters a lot in this field as professionals with five to nine years of experience get INR 8.3 lakh per annum. However, a business analyst with more than 10 years of experience gets INR 10 lakh per annum while a business analyst with more than 20 years of experience gets INR 20 lakh per annum. upGrad’s Exclusive Business Analytics Webinar for you – How upGrad helps for your Business Analytics Career? document.createElement('video'); https://cdn.upgrad.com/blog/vivek-and-ayush.mp4 As you can see, the pay range for these fields is quite similar but business analytics has a higher upper limit in comparison to data analytics. Learn Job-ready Program in Business Analytics from upGrad to become a certified Business Analyst professional. Fast-track your professional career after graduation with this Business analytics course with placement assistance. Read our Other Articles Related to Business Analytics What is Business Analytics? Career, Salary & Job Roles Top 7 Career Options in Business Analytics Business Analytics Free Online Course with Certification Business Analytics Vs Data Analytics: Difference Between Business Analytics and Data Analytics Top 7 Best Business Analytics Tools Recommended for every Business Analyst Top 11 Industry Applications of Business Analytics Future Scope of Business Analytics Business Analytics Eligibility or Requirement 8 Business Analytics Tips: Which Helps to Run Business Successfully Business Analytics vs Data Analytics: How to Enter Business analytics and data analytics require you to develop different industry skills and so, you’ll need different certifications to enter these industries. Data analysis professions such as data analyst, product analyst, and data scientist require you to be familiar with various data science subjects including predictive analysis, statistics, data visualization, and big data analytics. On the other hand, business analytics requires you to be familiar with business acumen (the keenness of solving business problems), data fundamentals, statistical and modelling tools, ability to track latest industry trends and make decisions accordingly. Courses for Data Analytics At upGrad, we offer multiple data analytics courses. You can enroll in our Master of Science in Data Science program. We have launched this program in partnership with Liverpool John Moores University. It lasts for 20 months and is completely online. Apart from that program, you can enroll in our PG Certification in Data Science program. We offer this program with IIIT-B and lasts for seven months. If you want a more detailed learning experience from IIIT-B, you can enrol in the PG Diploma in Data Science program. It’s India’s first NASSCOM certified PG diploma program in data science. Business Analytics Courses If you prefer to pursue a career in business analytics, you can enroll in our Business Analytics Certification Program. It lasts for three months only and is completely online. There’s also our Job-ready Program in Business Analytics. This program lasts for 5.5 months and offers more than 70 hours of live sessions and 5+ case studies and assignments. Another excellent short-term course is Global Master Certificate in Business Analytics which lasts for six months and gives you a certification from Michigan State University, the #32 ranking public university in the US. You can also check out IIT Delhi Business Analytics Course. IIT Delhi is one of the top institutes in India and also one of the oldest IIT’s and is always excelled in giving highly industry-relevant courses, Now IIT Delhi has partnered with upGrad to get these top IIT Delhi courses online. They have a variety of other programs like Machine Learning, Executive Management Programme in Strategic Innovation, Digital Marketing and Business Analytics etc. Our learners also read: Learn Business Analytics Free Final Thoughts Figuring out the difference between business analytics and data analytics can be challenging. However, we’re certain that the above points illustrated the notable distinctions between these two sectors. Business analytics will be helpful to you if you want to pursue a career in management as it focuses on gathering insights for decision-making. Having this skill will make your job as a business leader much easier. On the other hand, data analytics will be useful for you if you want to pursue a career in the tech sector. It focuses on analyzing and interpreting data to get insights. Usually, data analytics professionals deal with a huge quantity of data so they use advanced tools such as machine learning.

by Rohit Sharma

17 Feb'21