Blogs

11787

Thanks to the rapidly piling amounts of Big Data, the job profile of a Big Data Engineer is peaking. In recent years, there has been such unprecedented growth in the demand for Big Data Engineers that it has become one of the top-ranking jobs in Data Science today. Since numerous companies across different industries are hiring Big Data Engineers, there’s never been a better time than now to build a career in Big Data. However, you must know how to present yourself as different from the others; you need to stand out from the crowd. Read the blog to have a better understanding of the scope of Big Data in India. And how will you do that? By designing and crafting a detailed, well-structured, and eye-catching Big Data resume! When applying for a Big Data job, or rather for the post of a Big Data Engineer, your resume is the first point of contact between you and your potential employer. If your resume impresses an employer, you will be summoned for a personal interview. So, the key is to make sure you have a fantastic resume that can get you job interview calls. Usually, Hiring Managers have to look at hundreds of resumes, be it for any job profile. However, when it comes to high-profile jobs like that of the Big Data Engineer, you must be able to grab the attention of the Hiring Manager by highlighting your skills, qualifications, certifications, and your willingness to upskill.  Let’s begin the resume-building process with the job description and key roles and responsibilities of a Big Data Engineer. Explore our Popular Software Engineering Courses Master of Science in Computer Science from LJMU & IIITB Caltech CTME Cybersecurity Certificate Program Full Stack Development Bootcamp PG Program in Blockchain Executive PG Program in Full Stack Development View All our Courses Below Software Engineering Courses Who is a Big Data Engineer? Big Data Engineers are expert professionals who develop, construct, test, and maintain the Big Data architecture and solutions within an organization. Essentially, they develop the Big Data solutions designed by the Big Data Architect. Big Data Engineers are proficient in working with Hadoop based technologies like MapReduce, Hive MongoDB, or Cassandra. Read more on 5 Essential Skills Needed to Become a Big Data Engineer Job responsibilities of a Big Data Engineer Before we dig into the main roles and responsibilities of a Big Data Engineer, let’s look at some Big Data resume samples of reputed companies in the Big Data domain.  Dell: Source Deloitte : Source Primary Responsibilities of a Big Data Engineer To designing, develop, test, and maintain Big Data solutions, data management, processing systems of an organization. To ensure that the Big Data architecture of a company meets the client/business requirements. To design and develop highly scalable, efficient, robust & fault-tolerant Big Data systems and solutions. To identify and discover new and potential data acquisition opportunities. To implement complex Big Data projects by gathering, parsing, managing, analyzing, interpreting, and visualizing large datasets to extract valuable insights and convert those insights into actionable business decisions.  To work in close collaboration with all the stakeholders involved in a Big Data project. To improve the quality, reliability, and efficiency of data, individual components, and the Big Data system as a whole. To create and innovate efficient Big Data solutions by integrating multiple programming languages and Big Data tools. To develop data models that can reduce system complexities, thereby boosting efficiency and minimizing costs. To experiment with new Big Data management tools and technologies and integrate them into the existing system to enhance efficiency and performance. Skills required for the profile of a Big Data Engineer Strong knowledge of the Hadoop ecosystem and its core frameworks, including HDFS, YARN, MapReduce, Apache, Pig, Hive, Flume, Sqoop, Oozie, Impala, ZooKeeper, and Kafka. Proficient in SQL-based technologies (MySQL, Oracle DB, etc.) as well as NoSQL technologies (Cassandra and MongoDB). Experience in working with multiple programming languages like Python, R, Java, C, C++, Scala, JavaScript, etc. Efficiency in handling both ETL and data warehousing solutions.  Experience in working with multiple Operating Systems like UNIX, Linux, Solaris, MS Windows, and macOS. Basic foundational knowledge of Mathematics and Statistics. Strong knowledge of SOA, graph database, CI/CD pipeline,  Well-versed in database architectures. Explore Our Software Development Free Courses Fundamentals of Cloud Computing JavaScript Basics from the scratch Data Structures and Algorithms Blockchain Technology React for Beginners Core Java Basics Java Node.js for Beginners Advanced JavaScript Your resume should also highlight other soft skills like communication skills, leadership skills, managerial skills, problem-solving skills, analytical, and logical thinking skills, to name a few. Together, it should present a well-rounded picture of all your skills that would make you a perfect candidate for the job profile of a Big Data Engineer.  Get a PG Certification Program in Big Data and Analytics Big Data Engineer – Resume Building Here’s everything you need to include in your Big Data Engineer resume. Specify your contact information and location : Your contact information and location (address) should follow after your name on the header. You could also include your e-mail address. This allows the recruiter to have all the essential details at hand if they wish to contact you. Source  Specify your educational qualifications You should provide a detailed account of your educational qualifications, including school, college, and university. Make sure that along with your degrees, you also mention the year you earned them, the duration of each course, and the institute from where you obtained your degrees. This is essential since potential employers may want to verify your educational qualifications. Source  Write a brief summary of your work experience This is a pivotal part of your Big Data resume. In this part, you need to present a short and concise summary of your Big Data work experience so far. It shouldn’t be too long – no more than five to six lines/bullet points describing your work experience and why you are a fit candidate for the job. Source  Source  Highlight the tools and technologies you’ve worked with  This section will present a detailed account of all the tools, technologies, and platforms you’ve worked with so far in your professional life. Make sure to highlight only genuine information. Do not list tools/technologies that you aren’t familiar only to impress employers because if put to the test, and you are unable to work with such tools, it will hamper your professional credibility. Source  Specify the company names, job titles/profiles, and duration of your work experience  While talking about professional experience, you must mention the names of all the companies you’ve worked for (and your present company as well), their locations, your job profiles in those companies, your responsibilities in each of them, and the job duration for each company. Source Include any and every certification and academic projects you’ve worked on Today, employers highly value professional certifications. In fact, advanced certifications have become a recruiting criterion for many high-profile, specialized job roles. So, if you have obtained any certification, make sure you mention it in a separate section. You can also include internships and academic projects you’ve worked on under this section. Together, they will boost your credibility. Source Now that you know how to put together your Big Data resume, here are some key points to remember while creating it : Your resume should be simple, neat, and precise. You should have a clear idea of what skills and talents you want to showcase to potential employers and design your resume around that.  Always keep your resume updated as and when you move on to other ventures or acquire new skills. Although it is time-consuming, it is crucial to keep your resume updated so you can readily apply for jobs as they come.  If you have over two years of working experience, make it a point to include and highlight only those skills, qualifications, and details that are relevant for the jobs you are applying for – it’s great if you have at least 3-4 Big Data resume samples ready for specific jobs/job profiles. Do not include unnecessary information on your resume just to lengthen and stretch it.  Usually, a candidate with less than eight years of work experience should aim for creating a one-page resume that may stretch to two pages max. Any more than two pages and the resume only becomes too lengthy, making the recruiter lose interest in it.  Avoid including minor details of every job experience – only highlight the important points and skills of your past jobs. Also, avoid design-heavy formatting. Keep the design simple and fluid.  List your work experience in reverse-chronological order. Make sure to emphasize and showcase your passion, drive, and curiosity for the job role you are applying. In-Demand Software Development Skills JavaScript Courses Core Java Courses Data Structures Courses Node.js Courses SQL Courses Full stack development Courses NFT Courses DevOps Courses Big Data Courses React.js Courses Cyber Security Courses Cloud Computing Courses Database Design Courses Python Courses Cryptocurrency Courses  If you keep these simple tips and tricks in mind while designing your Big Data resume, you’re golden!  Learn Software Engineering Courses online from the World’s top Universities. Earn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career. If you are interested to know more about Big Data, check out our Advanced Certificate Programme in Big Data from IIIT Bangalore. Check our other Software Engineering Courses at upGrad. We hope this helps! Read our Popular Articles related to Software Development Why Learn to Code? How Learn to Code? How to Install Specific Version of NPM Package? Types of Inheritance in C++ What Should You Know?

by Supriya VS

09 Jan 2021

Blogs

5335

Karan Kurani is the co-founder and CTO of DoctorC, which is the leading marketplace in India connecting consumers with easy, affordable diagnostic & lab tests. He is an alumnus of Cornell University with an overall experience of 8+ years. He has worked with GREE as a Lead Software engineer and founded two startups Shoutt and DoctorC. DoctorC is an online marketplace in India connecting consumers with easy, affordable diagnostic & lab tests. Their mission is to make health care simple, transparent and affordable. We interacted with him at a workshop for Data Science enthusiasts conducted by UpGrad in Hyderabad, where he helped us understand how Data Science and Machine learning are improving healthcare and the varied applications it has. Data Science Summarized In One Picture What is the importance of data in today’s world? How do you see this changing in the next 10 years? It’s increasingly important to always be data-driven in your decision making. So its mission critical for businesses at this point. Also, with the rise of Artificial Intelligence and Machine Learning, you can automate a lot of these decisions and have great personalization for your customers. The Artificial Intelligence and Machine Learning models are only ever as good as the quality of data passed to them. So data is the new oil is not an understatement. There will be companies worth an aggregate of trillions of dollars in the next century that are only possible to exist because of the data and the data processing power in today’s world. Tell us a social initiative you would pick up and solve with data if you had infinite time and resources. Poverty by the use of Universal Basic Income. Need a lot of data and study to prove/disprove it – but if UBI works then humanity’s suffering will end as we know it. Converting Business Problems to Data Science Problems What is the biggest threat to the data industry as a profession? Over-regulation. Look at GDPR and the fallout because of it.

by Supriya VS

13 Jul 2018

Blogs

6914

The digital and social media marketing landscape is ever-changing. It is no longer the same as it used to be in the past. While old trends must make way for the new ones, digital and social media marketers find it quite challenging to stay updated with the dynamic trends of the marketing world. Ever since Big Data has come into the limelight, it has attracted and continues to attract entrepreneurs, marketers, and brands across the world. Today, Big Data is no less than a gold mine for marketers and companies – it is the treasure trove of hidden patterns and insights that can help find solutions to all kinds of business problems. In fact, today there is only one mantra of success in the business and marketing world – if you want to make it to the top and stay ahead in the game, data is the key! In a study, Richard J. Vaughan analyzed the job listings in the top six metro areas for marketing, and he found that nearly 39% of marketing jobs demanded Big Data skills as a critical requirement. So, hear, hear, all the aspiring digital and social media marketers out there – it is time to embrace and develop data skills if you wish to become a part of the new digital marketing age! Here are the data skills that every marketer should develop: Product Innovation Brands can use Big Data tools and technology to develop and test new products while also simultaneously monitor the impact of their products on the consumers in real-time. For instance, Kraft created a strategy to involve their consumer group in their product development process actively. After monitoring and identifying two specific online trends associated with popular snacks products from consumer data- one being the requirement of portion control, and two being the concept of snacks as rewards – it released Nabisco 100-calorie packs. And within a year of launch, Nabisco raised a $100 million! Converting Business Problems to Data Science Problems Audience Segmentation and Personalization Harnessing Big Data, marketers can categorize their target audience into individual segments based on their tastes and preferences, behaviour patterns, age demographics, and so on. Audience segmentation will allow you to personalize and streamline communication channels (messages and emails), products and services, and marketing campaigns according to the specific needs of individual customer segments. This will not only boost customer experience and satisfaction, but it will also help you retain customers. Marketing Strategy In the digital age powered by Big Data, there is no room for hunches anymore. Data-driven marketing strategies are the new deal now. Leveraging Big Data, companies can optimize business operations, increase sales and revenue, boost employee productivity, and so much more. As you dive into consumer data, you begin to understand their pain points and specific needs. This allows you to make accurate decisions and create data-driven marketing strategies that hold the potential to attract consumers. Today, 51% of marketing influencers depict an inclination towards data-driven decision making. Our learners also read: Python free courses! How to Make a Bright Career in Data Explore our Popular Data Science Certifications Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Certifications Increase Sales and Revenue Big Data provides accurate insights regarding what strategy or content will be ideal for each stage of the sales cycle. Not just that, Big Data analytics help boost and improve the quality of sales leads, enhance prospecting list accuracy, territory planning, and win rates for sales strategies. Today, Big Data is also helping marketers optimize product pricing through data-driven differential pricing strategies. Eventually, as sales increases, the revenue also starts showing upwards trend. Identify Intent Signals It is not a hidden fact that companies monitoring intent signals through Big Data technology hold a competitive edge over their rivals in the market. Intent signals are generated through multiple data sources such as content, search queries, social media engagement, browsing behaviours, and user interaction with apps, to name a few. By tracking these metrics in real-time, you can make better business decisions. For instance, you can match your communication channels according to a particular audience segment’s stage in the buyer’s cycle. This will allow you to create excellent ad-driven sales and social media campaigns.   What Is Data Science? Who is a Data Scientist? What is Analytics? Top Data Science Skills to Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Programs Inferential Statistics Programs 2 Hypothesis Testing Programs Logistic Regression Programs 3 Linear Regression Programs Linear Algebra for Analysis Programs upGrad’s Exclusive Data Science Webinar for you – How upGrad helps for your Data Science Career? document.createElement('video'); https://cdn.upgrad.com/blog/alumni-talk-on-ds.mp4   While it is true that creativity is the secret sauce behind marketing and business strategies, today, it needs to be coupled with Big Data skills. Data is rapidly changing the world around us, and if you wish to keep our ideas relevant in this age, you must leverage data in creative ways. Developing the right set of data skills will help you a great deal in the long run. Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? Get data science certification from the World’s top Universities. Learn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career.

by Supriya VS

04 Jul 2018

Blogs

5243

The digital marketing landscape is an ever-changing one. New strategies keep on pouring in, making it challenging for digital marketers to keep up with the changing trends. However, just keeping yourself updated with the latest marketing trends isn’t enough. A digital marketer must be well-versed with digital marketing jargons or terminologies to successfully design and implement digital marketings strategies. Best Online Digital Marketing Courses Advanced Certificate in Brand Communication Management - MICA Advanced Certificate in Digital Marketing and Communication - MICA Performance Marketing Bootcamp - Google Ads from upGrad To explore all our certification courses on Digital Marketing, kindly visit our page below. Digital Marketing Certification Yes, digital marketing jargons can be confusing, but they’re not exactly rocket science. Let’s help you understand digital marketing jargons a little better with this informative guide! Here are a few common digital marketing jargons that every digital marketer must know: ROI and MROI Return on investment (ROI) is a term that denotes the profitability of marketing strategies. MROI or Marketing return on investment, on the other hand, measures the efficacy of your marketing strategies by comparing one marketing approach against another. Top Digital Marketing Skills Online Advertising Courses Influencer Marketing Programs SEO Optimisation Courses Performance Marketing Certification Search Engine Marketing Course Email Marketing Strategy Content Marketing Strategy Social Media Advertising Digital Marketing Analytics Website Analytics Online Display Advertising Best Affiliate Programs Learn digital marketing courses online from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career. SEO Search engine optimization (SEO) encompasses a whole bunch of techniques and strategies that are used by digital marketers to ensure that their website and web pages always remain on top of the search engine ranking ladder. For instance, digital marketers can perform SEO audit of their website, create SEO optimized landing pages, optimizing sites for mobile devices, incorporate AdWords – all of this constitute SEO strategies. Mobile Marketing – Make the Most of Smartphones and Tablets KPI KPIs or key performance indicators are used to monitor and measure the progress and success rate of your marketing tactics. Comparing your KPI metrics against the industry data insights allows you to assess how well your marketing schemes are doing with your customer base. While KPIs can be as simple as tracking your website traffic and optimizing your content with keywords, they can also be as complicated as tracking your customer-acquisition-cost. Digital Marketing Free courses to Learn Influencer marketing free course Introduction to advertising free course Influencer marketing right free course SEO basics free course SEM basics free course Email marketing free course Social media marketing introduction free course How to leverage user generated content free course Content marketing free course Fundamentals of marketing free course Brand marketing masterclass free course Media Flight Media flight refers to the pattern in which marketing ads appear as part of a business’ media schedule. A well-designed media schedule has alternating patterns of ‘flights’ and ‘hiatuses.’ While flight denotes the periods when marketing ads appear, hiatus denotes the period when ads do not appear. By leveraging a well-designed media schedule, you can reach your target audience better. PPC Pay per click (PPC) is an online advertising technique. In this method, businesses can choose to display their ads on websites, but rather than paying a lump sum amount for the ads business owners spend a stipulated amount every time a visitor on the site clicks on the ads. When visitors click on the ads, interactive links get activated automatically. Google AdSense: How it Works and How to Work Around Issues CPA Cost per Acquisition (CPA) refers to a pricing model based on which companies are charged by advertising platforms when their ads generate leads, conversions, and sales. RSS Real Simple Syndication or the RSS technology enables users to subscribe to the content suited to their tastes. It sends automatic alerts to all subscribers every time an update is added to the content. Feedly and FeedReader are two most popular RSS Readers. Advertainment As the name suggests, ‘advertainment’ is an amalgamation of advertising and entertainment. It is essentially ‘branded entertainment’ as it involves combining the different forms of entertainment such as songs and movies with advertising elements promoting a particular brand. So, while your potential consumers enjoy their favourite entertainment content, they get to know about your brand through advertisements. 360 Degree Campaign A 360-degree campaign refers to a marketing campaign that juxtaposes all the core marketing assets such as social media, emails, content, print advertising, billboards, and so on. This is a holistic approach to marketing as it allows entrepreneurs and marketers to cover an extensive base to reach customers. Key Differentiator The term ‘Key Differentiator’ refers to all the aspects that make your business unique in the industry. For instance, why should a customer favour your brand over the others? What makes your products/services stand out from the crowd? The answers to such questions make up the key differentiators of your business. A brand’s key differentiators should be actionable, practical, and accurate. Popular Digital Marketing Blogs Beginners Guide to YouTube Marketing : Complete List How to Monetize Your YouTube Channel? Top 5 Actionable Steps The Complete Guide on setting up a LinkedIn Company Page Everything You Need To Know About Digital Marketing A Complete Guide to Digital Marketing Strategy: What it is and How to create it? Digital Marketing Tutorial: A Step-by-Step Guide To Become an Expert Future of Digital Marketing: How It Goes From Here Importance of Digital Marketing: Top 10 Reasons Your Business Needs it Digital Marketing Challenges: How to Win Amidst the Challenges in Digital Marketing Organic Traffic Organic traffic refers to the traffic driving towards your website from Search Engines such as Google, Yahoo or Bing. Since the search engines generate the traffic, it is also known as “free” traffic. Viral Marketing Viral marketing is a marketing technique through which companies encourage their target audience to share their content on social media platforms, thus, promoting increased exposure. What’s the Best Type of Content to Drive Conversions? Although these are only a select few popular digital marketing jargons, knowing these terms is a must for all aspiring digital marketers. Having a thorough understanding of digital marketing jargons allows marketers and entrepreneurs to enhance their marketing strategies. Learn digital marketing courses online from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career. Featured Programs for you – Advanced Certificate in Digital Branding & Advertising from MICA upGrad’s Exclusive Digital Marketing Webinar for you – What’s new in Marketing? document.createElement('video'); https://cdn.upgrad.com/blog/rumi-ambastha.mp4  

by Supriya VS

03 Jul 2018

Blogs

7735

Big Data is the new currency of the modern age. As technology continues to massively influence our lives, our reliance on data is also increasing. According to Statista, the global data market size is predicted to rise to 42 billion USD. Big Data is everywhere. It has already started influencing everything in our lives, right from our music and TV show preferences to smart assistants who can accomplish a host of tasks for us, thereby making our lives much more convenient and comfortable.   Here’s the Big data market size revenue forecast worldwide from 2011 to 2027 (in billion U.S. dollars): Career opportunities in Big Data are on the rise. As more companies are joining the data bandwagon, higher is the demand for skilled data professionals. Which means, if you’re thinking of making a career in Big Data Engineering you are most definitely going to be in-demand. Let’s see how Big Data impacts our daily lives! 1. Online shopping Ever wondered how those personalized “recommendations” pop up in your notifications every time you browse through an online shopping platform? Well, folks, that’s the magic of Big Data. Online shopping sites like Amazon, Myntra et al dive into the vast pools of consumer data to understand and learn your shopping patterns, tastes and preferences and that’s how they’re able to create customized shopping recommendations for you. The Importance of Continuous Learning and Upskilling 2. Entertainment Thanks to Big Data technologies, platforms like Netflix and Spotify have taken entertainment to the next level. Data influences the shows you watch and also the music you listen to. Netflix produces and curates highly addictive shows by extracting the consumer behaviour and preference patterns from their database. It leverages consumer data and viewing habits to customize the watchlist according to the hottest genres, actors, and so on. Similarly, music giant Spotify taps into consumer data to specially customize the weekly playlist according to the tastes of individual users. Explore our Popular Software Engineering Courses Master of Science in Computer Science from LJMU & IIITB Caltech CTME Cybersecurity Certificate Program Full Stack Development Bootcamp PG Program in Blockchain Executive PG Program in Full Stack Development View All our Courses Below Software Engineering Courses 3. Healthcare Big Data is rapidly radicalizing healthcare for the better with data backed by innovative technologies. Gone are the days of loads of paperwork for organizing and maintaining patient health records. EMRs (Electronic Medical Records) which are powered by Big Data, allow health care providers (HCPs) to aggregate patient data within a centrally integrated platform enabling medical professionals to access them anytime, anywhere for more personalized treatment and supervision. Also, fitness sensors and wearables have allowed millions of individuals to take charge of their health. People can now monitor their health without having to rush to the clinic every time. Tracking the health of the elderly has also become easier with remote monitoring technology, another result of Big Data technology. Any fluctuation and anomaly in their health will be conveyed to HCPs in the form of alerts or messages, thus allowing doctors to prescribe treatments in real-time. Explore Our Software Development Free Courses Fundamentals of Cloud Computing JavaScript Basics from the scratch Data Structures and Algorithms Blockchain Technology React for Beginners Core Java Basics Java Node.js for Beginners Advanced JavaScript 4. Banking Big Data analytics are now helping banks to prevent financial fraud. Banks can efficiently track and trace any suspicious activity, credit card fraud, and the breach of crucial financial data by leveraging Big Data tools and technologies. This has greatly helped in fortifying the security of banks and protecting valuable customer information. Is it a Good Time to Startup in the Big Data domain In-Demand Software Development Skills JavaScript Courses Core Java Courses Data Structures Courses Node.js Courses SQL Courses Full stack development Courses NFT Courses DevOps Courses Big Data Courses React.js Courses Cyber Security Courses Cloud Computing Courses Database Design Courses Python Courses Cryptocurrency Courses 5. Crime Ever heard of ‘predictive policing?’ Thanks to Big Data analytics, the police can now monitor and prevent crimes even before they happen! Using Big Data visualization software, policemen can now predict the probability of where a crime can most likely occur and be there on time to prevent it. Usually, the software database stores the complete history of criminal data according to locations and is integrated with algorithms based on criminal behaviour patterns. This allows police to always stay alert and monitor activities in their respective areas. These are just some of the examples extracted from real life depicting how Big Data has started impacting our lives even without us realizing it. From enhanced security to healthcare, Big Data is definitely creating a wave of change around us. 15 Must-know Big Data Interview Questions Wrapping up If you are interested to know more about Big Data, check out our Advanced Certificate Programme in Big Data from IIIT Bangalore. Learn Software Development Courses online from the World’s top Universities. Earn Executive PG Programs, Advanced Certificate Programs or Masters Programs to fast-track your career.

by Supriya VS

27 Jun 2018

Blogs

5108

Behind every successful organization, there is Data. It is the latest buzzword in the industry now. Over the past few years, organizations across the globe have started leveraging data to uncover useful insights to drive business growth and power innovation. As a result, there have emerged plenty of career opportunities in data. However, to kickstart a successful career in data, you must first build the necessary skill set that the field demands, that is, a high level of proficiency with data. Individuals who have extensive knowledge about market dynamics and who know how to convert data into actionable insights using a combination of technical agility and analytical skills are the ones who have a chance to have a bright career in data. Understand The Basics The foremost requirement of beginning a career in data is to develop a compatibility quotient with key data concepts such as machine learning, probability theory, statistics, and enterprise analytics, to name a few. As a data professional you must be able to handle databases with flair and also be well-versed with programming languages such as Python, Scala, R, Java, JavaScript, Perl, and SQL. Today, many online platforms offer specialized Data Science courses for aspiring individuals seeking to start a career in data. With a little dedication and commitment, you can master Data Science with these online courses. What is Text Mining: Techniques and Applications Be Thorough With Market Dynamics The technological landscape is dynamic, with innovations being made every day. To emerge as a skilled data professional, you must keep yourself constantly updated with the latest market development dynamics. The better you understand the market dynamics, the higher will be your efficiency in leveraging advanced data tools to power innovation. Apart from following industry-related news and events, make sure to attend technological conferences. You get to connect with the best of talent in the industry and expand your network. Strengthen Your Statistics and ML Foundations Statistics and Machine Learning are two fundamental pillars of Data Science. Thus, to build a career in data, you need to strengthen your statistics and ML skills. Start off small with simple concepts such as hypothesis testing, central limit theorem, normal distribution, and make your way up towards more complex concepts like classification, probability estimation, logistics regression, linear regression, cluster analysis, decision trees, etc. What Is Data Science? Who is a Data Scientist? What is Analytics? Develop The Right Communication Skills To have a bright career in data, it is not enough to be technologically sound. A data professional cannot stop at extracting meaningful information. He/she must be able to translate the information into actionable insights and convey the data-driven solutions to the business management team in terms they can understand. Not only do you have to continually mine data to discover valuable insights but you also have to act as a communication link between the tech team and the business management team. Explore our Popular Data Science Online Certifications Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Online Certifications Our learners also read: Learn Python Online for Free Having covered all your bases, you will be all set to explore the emerging exciting and challenging positions in data jobs like that of a data scientist, data analyst, business analyst, data architect, machine learning engineer, etc. Top Data Science Skills You Should Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Online Certification Inferential Statistics Online Certification 2 Hypothesis Testing Online Certification Logistic Regression Online Certification 3 Linear Regression Certification Linear Algebra for Analysis Online Certification “How to Become a Data Scientist” Answered! upGrad’s Exclusive Data Science Webinar for you – Watch our Webinar on How to Build Digital & Data Mindset? document.createElement('video'); https://cdn.upgrad.com/blog/webinar-on-building-digital-and-data-mindset.mp4   Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? Today, demand for data professionals has spread across various industries such as banking and finance, entertainment, advertising, online shopping platforms, crime departments, agri-tech, and many more.

by Supriya VS

26 Jun 2018