Tutorial Playlist
68 Lessons1. Excel Tutorial
2. Excel Worksheet for Practice
3. Google Sheets Vs. Excel
4. Excel Shortcut Keys
5. Excel Keyboard Shortcuts
6. Excel AutoSum Shortcut
7. Redo Shortcut in Excel
8. Charts in Excel
9. Pivot Charts in Excel
10. Excel Sum Formula
11. Excel Percentage Formula
12. Excel Age Calculation Formula
13. Excel Range Formula
14. Round Off Formula in Excel
15. VLOOKUP Formula in Excel
16. Excel Transpose Formula
17. Average Equation in Excel
18. How to Use DATEDIF Formula in Excel
19. IRR Formula in Excel
20. Standard Deviation Formula
21. Excel Age Calculation Formula
22. Excel MAX Function
23. Excel LEFT Function
24. Excel RIGHT Function
25. Trim Function In Excel
26. LookUp function in Excel
27. Columns in Excel
28. How To Sort Data In Excel
29. How To Freeze Panes in Excel
30. Page Setup in Excel
31. How to Recover an Unsaved Excel File
32. Concatenate in Excel
33. Count In Excel
34. IF Condition In Excel
35. H LOOK UP in Excel
36. How Do You Move Columns in Excel
37. Split Cells in Excel
38. Remove Blank Rows in Excel
39. How To Lock Cells in Excel
40. Data Validation in Excel
41. How to Insert Checkbox in Excel
42. How To Highlight Duplicates in Excel
43. Fill Series in Excel
44. How to Create Excel Drop-Down List
45. What-If Analysis in Excel
46. How to Use SUMIFS Function in Excel
47. INDIRECT Function in Excel
48. Pivot Table in Excel
49. Slicers in Excel
50. How to Create a Dashboard in Excel
51. Excel Data Cleaning
Now Reading
52. Data Analysis In Excel
53. Goal Seek in Excel
54. Solver in Excel
55. Power Query in Excel
56. Macros In Excel
57. How To Make Graph in Excel
58. How To Make Histogram In Excel
59. How To Convert PDF to Excel Without Software
60. Barcode Font For Excel
61. Gantt Chart in Excel
62. Excel RANK function
63. AND Function in Excel
64. How to Calculate NPV
65. Format Painter in Excel
66. Count Colored Cells in Excel
67. Amortization Schedule in Excel
68. Master Cell References in Excel
Data cleaning includes repairing or deleting data that is incorrect, corrupted, poorly formatted, repetitive, or incomplete within a dataset. In my line of work as a data scientist, there is no one-size-fits-all method for prescribing exactly what to do in the data cleaning process. This is because Excel data cleaning techniques differ from dataset to dataset.
However, it is important to create a template for your data cleaning process so that you can ensure you perform it correctly every time. Hence, to help you out, I have curated this beginner-friendly guide on data cleaning with Excel.
Note: This tutorial is meant for learners who already know their way around Excel. If you have no idea how to navigate this software, consider going through an easy Excel tutorial and make sure you get lots of practice!
Some of the most common processes and techniques of data cleansing are:
Excel provides some techniques to easily clean data. The most widely used techniques are:
Delete any repetitive or irregular observations, as well as any unwanted observations. In most cases, duplicate observations occur most frequently when you're collecting data.
For example, if you integrate data sets from various sources, scraped data, or obtained data from clients, your sheet will end up with duplicated data. Whenever I encounter something similar, I use re-duplication.
Irrelevant observations only occur when you discover data that do not apply to the specific topic you're trying to analyze.
Data cleansing tools in Excel help improve analysis efficiency and minimize distractions from your core goal, as well as offer a more manageable and perfromant dataset.
These are errors that occur during data transfer, measurements, and other challenges resulting from poor data management. The most frequent issues with structural errors include inconsistent typos, punctuations, and mislabeled classes.
If you see such errors, it means you need to use Excel data cleaning techniques to clean your data.
If you use Excel as your main source of data gathering, you will often run into one-time observations that don't appear to fit into the data that you're examining.
If there is a valid cause to delete an outlier, such as inaccurate data entry, it will help you improve the dataset you're working with.
Remember that just because an outlier shows up doesn't mean that it is incorrect. You need to filter unwanted outliers to determine the accuracy of the data value. I recommend deleting the outlier if it is unrelated to the observations or is just incorrect.
You simply can't overlook missing data since many algorithms reject missing values. However, there are a few approaches to dealing with missing data; neither is ideal, but you should take a look at them
As part of the Excel data cleaning techniques, you should be able to validate the following questions at the end of the cleaning process
In many cases, wrong conclusions because of inaccurate or bad data can influence bad decision-making and business strategy. Incorrect conclusions might be awkward as you will learn that your data doesn't pass the scrutiny.
I recommend that you establish a culture of excellent data in your business. To accomplish this, you need to document the tools you can use to promote this culture and understand how you tackle data quality.
Data quality is a vital essence for any business that relies heavily on data to function. For example, when dealing with multiple clients, you have to ensure that accurate invoices are emailed to the correct client.
You can boost your brand's value by prioritizing data quality to make the best use of client data.
The following are some benefits of Excel data cleaning techniques:
Excel data cleaning is the most effective option to cut down on costs incurred due to processing mistakes, fixing wrong data, or troubleshooting in general.
Businesses that maintain their databases in good shape can create prospect lists based on accurate and updated data. This can help you improve customer acquisition and reduce costs.
Excel data cleaning allows you to smoothly manage multi-channel client data and allows your business to identify potential marketing campaigns and new ways to reach your targeted customer base.
If you want to improve your decision-making process, you should stick with clean data. Accurate and updated data will help you enable your business intelligence and analytics. Clean data offers businesses resources for better decision-making.
When working with Excel, it is important to manage clean and well-maintained databases. It will help you increase your staff productivity by helping them with various methods, such as client acquisition and resource planning. Businesses that proactively increase the accuracy and consistency of data also see an increase in revenue and response rate.
Data cleansing tools in Excel offer a great way to clean data, but they do come with various challenges. I have outlined them below:
Data backup is the process of copying data from one location to another to secure it in case of accidents and cyber thefts. These days, most small businesses rely significantly on data. As a small business owner myself, losing any amount of useful data can severely affect and cause issues in daily activities.
For example, with a large customer base and didn't back up the data on a different server or machine, I would risk losing every client detail if I fell victim to a malicious online attack. In case of redundant data, you can address them during the Excel data cleaning process.
However, if you can't find any effective backup plan, you might lose your data. Hence, backing up your data is a challenge during the data cleaning.
As you might already know, data comes in various forms, and one strategy to help facilitate Excel data cleaning techniques is to ensure that you use specific data cleaning techniques for specific data types. For example, text-based cleansing won't work when working with visuals, and vice versa.
As a result of this, you might find yourself spending a lot of time trying to segregate data based on the data-cleaning technique applicable to them.
Excel data cleaning is a vital feature as it can help you fix various errors, such as an incorrect date, a typo, or even a minute detail, like punctuation. Data cleaning helps maintain the integrity of your data sheet and helps prevent expensive mistakes.
Speaking from experience, it ultimately improves vital decision-making processes and can, in the long run, add to brand growth. Speaking of experience, if you are here trying to get an idea of data cleaning, you are probably at the threshold of starting your career. Here’s a pro-tip. Try taking up a professional data science course from upGrad.
1. Can you automate data cleaning in Excel?
Yes, you can automate Excel data cleaning by using the Power Query tool.
2. What is the data cleaning add in for Excel?
There isn't a specific "data cleaning add-in" for Excel, but there are third-party add-ins available for Excel that specialize in data cleaning tasks. They make cleaning data easier by offering tools for removing duplicates, parsing text, and formatting cleanup.
3. What are the data cleaning techniques?
Excel data cleaning techniques include removing duplicates, removing irrelevant data, fixing errors, converting data types, and more.
4. How do I clear data from Excel?
You can clear data in Excel by selecting the cells that you need to clean and click “Clear All.”
5. How do I run a clean function in Excel?
You can run a clean function in Excel by choosing your preferred cell and typing ‘CLEAN.’ Then, provide a text argument to use the function.
6. What is automated data cleaning?
Automated data cleaning is exactly what it sounds like; you can automate data cleaning in Excel using software or Data cleansing tools in Excel.
7. What are the 5 concepts of data cleaning?
The answer to this question has been discussed thoroughly in this tutorial.
8. What is data cleaning with an example?
Data cleaning is the process of fixing inconsistencies in your datasheet. For example, fixing typos, fixing syntax errors, or fixing wrong numerical entries.
Devesh
Passionate about Transforming Data into Actionable Insights through Analytics, with over 3+ years of experience working in Data Analytics, Data V…Read More
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upGrad does not grant credit; credits are granted, accepted or transferred at the sole discretion of the relevant educational institution offering the diploma or degree. We advise you to enquire further regarding the suitability of this program for your academic, professional requirements and job prospects before enr...