Complete Guide to Excel 365: Validating, Cleaning, & Performing Lookups on Data

Excel Office 365    |    Intermediate
  • 13 Videos | 1h 35m
  • Includes Assessment
  • Earns a Badge
Excel is not only used for aggregating and analyzing data, but also for data cleansing. There are several data cleaning, validation, and checking techniques available, some of which are among Excel's most well-known and widely-used functions. In this course, you'll start by using various string and data manipulation functions to clean data and fill in missing values. Next, you'll perform simple data validation based on specific numeric thresholds and text lengths, before moving on to validation using lists. You'll then combine data validation to implement a formidable, dynamic data validation mechanism using named ranges and the INDIRECT formula. Finally, you'll use one-dimensional lookups - the classic HLOOKUP and VLOOKUP worksheet functions - as well as more complex, two-dimensional lookups utilizing a combination of INDEX and MATCH. 

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    Use absolute and relative cell references in worksheet formulae, lock cell references using the $ symbol and named ranges, and use the trace error feature to debug formula errors  
    analyze data using the Subtotal feature, specify when the subtotal function should be applied, compute group summaries and grand totals, and remove changes to the workbook made by the Subtotal menu 
    use the Filter feature from the Data menu to focus on specific subsets of data, illustrate how Filter and Subtotal differ in making changes to a workbook; identify and avoid circular references using Excel Error Checking  
    perform conditional analysis using the IF() function, and combine logical conditions using the AND() and OR() functions
    use conditional aggregate functions, such as COUNTIF() and COUNTIFS(), to perform aggregate operations based on specific conditions and recognize the semantics of predicates created from strings for use within these functions  
    utilize VLOOKUP() and HLOOKUP() functions for one-dimensional lookups that join data ranges based on a common column, then use relative cell references for the lookup value and absolute cell references for the lookup range 
  • use the INDEX() and MATCH() functions to perform two-dimensional lookups and nest two calls to MATCH() within a single call to INDEX() to match on both row and column  
    implement common data-cleaning operations, such as eliminating duplicates via the Data menu, use CLEAN() to remove unwanted whitespace characters, correctly interpret numbers stored as text, and use CONVERT() for an extensive range of unit conversion operations  
    work with external hyperlinks and parse them using string functions, such as RIGHT(), LEFT(), MID(), SUBSTITUTE() and LEN(), and fill in blank/missing values using the Find & Select menu option and the Go To Special feature  
    specify data validation constraints, configure bounds on acceptable values, create user-friendly error messages, and validate data based on decimal, whole number, text length, and date/time values  
    create lists for use in data validation and use named ranges and the INDIRECT() function to create a robust and dynamic data validation mechanism  
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    2m 8s
    UP NEXT
  • Playable
    2. 
    Using Absolute Cell References and the $ Symbol
    7m 29s
  • Locked
    3. 
    Using the Subtotal Feature
    5m 55s
  • Locked
    4. 
    Using the Filter Feature
    8m 6s
  • Locked
    5. 
    Checking Conditions Using IF()
    8m 24s
  • Locked
    6. 
    Using Conditional Aggregates
    6m 47s
  • Locked
    7. 
    One-dimensional Lookups With VLOOKUP() and HLOOKUP()
    11m 26s
  • Locked
    8. 
    Two-dimensional Lookups Using INDEX() and MATCH()
    12m 1s
  • Locked
    9. 
    Cleaning Data
    8m 4s
  • Locked
    10. 
    Parsing Strings
    4m 15s
  • Locked
    11. 
    Performing Simple Data Validation
    8m 14s
  • Locked
    12. 
    Performing Complex Data Validation
    5m 20s
  • Locked
    13. 
    Course Summary
    1m 21s

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