Course curriculum

  • 1

    Introduction to Excel Data Cleaning

    • Introduction to the course

    • The follow through exercise

    • Attributes of a good Data-set in Excel

    • Introduction to Text Data Type Data Cleaning
  • 2

    Text Values Data Cleaning: First Name Column Values

    • First Name Column Values : The CODE() and ASCII

    • First Name Column Values : Using the CODE() to Detect Errors

    • Applying the CLEAN() function to clean non-printable characters

    • Applying the TRIM() function to clean Leading and Trailing Spaces

    • The SUBSTITUTE(), CHAR() and the TRIM() functions to clean Non-Breaking Spaces

    • The PROPER() function to format Text Values
  • 3

    Text Values Data Cleaning Exercise: Last Name Column Values

  • 4

    Text Values Data Cleaning Exercise: Address Column Values

  • 5

    Text Values Data Cleaning Exercise: Passport Column Values

    • The CONCATENATE() Function
  • 6

    Text Values Data Cleaning Exercise: Mobile Phone Column Values

    • Introduction to exercise and try it yourself exercise: RIGHT() and LEN()

    • Applying the LEN() Function to check for errors in the Phone column

    • Combination RIGHT(),LEN() ,IF(IF()) and other functions to correct phone values
  • 7

    Text Values Data Cleaning Exercise: Currency Column Values

    • =TRIM(CLEAN(SUBSTITUTE(CHAR()))) to fix Text Errors
  • 8

    Text Values Data Cleaning Exercise: Country Column Values

    • =IF(OR()) combination to fix column values
  • 9

    Text Values Data Cleaning Exercise: Airport Column Values

    • VLOOKUP() and IFERROR() in Data Cleaning

    • =IFERROR(VLOOKUP()) combination in fixing the column value Errors
  • 10

    Date Values: Data Cleaning Exercise

    • WebHD_720p (1)Date of Departure Column Values : ISNUMBER() and "TEXT TO COLUMN"

    • Date of Departure Column Values : DATE() function

    • Date of Birth Column Values: ISNUMBER()
  • 11

    Number Data Values: Data Cleaning Exercise

    • Amount Column Values: VALUE() and TEXT() Functions
  • 12

    Removing Duplicate Records

    • Conditional Formatting and Remove Duplicates Features of Excel
  • 13

    Data Normalization

    • Introduction to the Exercise

    • Add Age Column: YEAR() and TODAY() Combination

    • Add Month of Departure Column: TEXT() Function

    • WebHD_720p
  • 14

    Practice Exercises: Sample Dataset

    • Practice Exercise #1: HR Sample Dataset 1

    • Practice Exercise #2: HR Sample Dataset 2

    • Practice Exercise #3: Sales Sample Dataset
  • 15

    Review and Conclusion

    • What did you Learn?

Instructor Bio

Lead Instructor

Nasiru Musa CAMS

Meet Nasiru Musa, an accomplished professional with a diverse background in the fields of Accounting, Information Systems, and Law Enforcement Intelligence Analysis. Nasiru holds a BSc in Accounting from ABU Zaria (Nigeria), an MSc in Information Systems from the esteemed University of Liverpool, and a Postgraduate Certificate in Corruption Studies from Hong Kong University. With extensive experience spanning over 8 years at the Nigerian Financial Intelligence Unit, Nasiru has honed his expertise in Auditing, Financial Investigation, and Information Systems. Throughout his career, he has successfully led teams in high-profile cases involving Corruption, Human Trafficking, Illicit Drug Financial Investigations, Money Laundering, and Terrorist Financing. Nasiru Musa's commitment to excellence is further demonstrated by his impressive list of certifications, including the prestigious Certified Anti-Money Laundering Specialist (CAMS). From 2008 to 2015, he also held esteemed designations as a Certified Fraud Examiner (CFE), Certified Information Systems Auditor (CISA), and Certified Information Security Manager (CISM). Nasiru is passionate about sharing his wealth of knowledge and practical experience with others. As an instructor, he aims to empower students with valuable insights and skills in the realms of Financial Intelligence, Anti-Money Laundering, Fraud Examination, and Information Security. Join his courses to learn from a seasoned professional who has made a significant impact in the fields of financial investigation, and intelligence analysis.