IBM-Course-Excel-Basics-for-Data-Analysis

Week 1

Learning Objectives

• Describe the fundamentals of a spreadsheet application.
• Access Excel on the Web.
• Navigate around an Excel worksheet and workbook.

Week 2

Learning Objectives

• View, enter, and edit data in a worksheet.
• Move, copy, and fill data in a worksheet.
• Describe the fundamentals of formulas.
• List some of the common functions used by a data analyst.
• Reference data in formulas.

Week 3

Learning Objectives

• Explain the importance of data quality.
  • 5 Traits of good data:
    • Accuracy
    • Completeness
    • Timliness
    • Reliability
    • Relevance
• Import file data in to Excel.
• Describe the fundamentals of data privacy.
  • Fundamentals of Data Privacy:
    • Confidentiality
      • PI
      • PII
      • SPI
    • Collection and Use
      • GDPR
      • LGPD
      • CCPA
      • HIPAA
    • Compliance
• Remove duplicate data, inaccurate data, and empty rows in Excel.
  • It’s important to remove any duplicated or inaccurate data, and it’s important to remove any empty rows in your dataset.
  • There are several other types of data inconsistency that you may need to resolve, in order to properly clean your data:
    • Change the case of text
    • Fix date formatting errors
    • Trim whitepace from your data
  • You can use the Flash Fill and Text to Columns features in Excel to manipulate and standardize your data, and functions can also be used to help manipulate and standardize your data.
• Resolve inconsistencies in data.
• Manipulate and standardize data using the Flash Fill and Text to Columns features in Excel.

Week 4:

Learning Objectives

• Describe the fundamentals of analyzing data using a spreadsheet
• Filter and sort data in a worksheet.
• Employ some of the most useful Excel functions for data analysis.
  • Excel Functions:
    • Mathematical
    • Statistical
    • Logical
    • Financial
    • Date & Time
    • Common functions for a data analyst include IF, IFS, COUNTIF, SUMIF, VLOOKUP, HLOOKUP.
• Implement the VLOOKUP and HLOOKUP functions to reference data.
• Create pivot tables in Excel.
• Utilize pivot table features. -Format data as a table
  • Create a Pivot Table and use fields to arrange data in a Pivot Table
  • Perform calculations using Pivot Table data
  • Use the Recommended Charts feature (does not work with the 'Basic' Office for the web plan.)
  • Use the Filters feature
  • Use the Slicers feature
  • Use the Timelines feature

Week 5: Final Project

Learning Objectives

• Demonstrate hands-on skills to clean, prepare, and analyze data for a business scenario.
• Apply data cleansing and analysis techniques in an Excel spreadsheet.
• Evaluate the data analysis project developed by your peers using the provided rubric and grading scheme

Part 1

In this final assigment, I will be following the scenario of a recently hired Junior Data Analyst in a local government office, who has been tasked with importing some data from another department which relates to inventory information about their fleet of vehicles. The data is in comma-separated value (CSV) format and the data also needs cleaning up before I can start to run any kind of analysis on it.

Part 2

In this final assigment, I will be following the scenario of a recently hired Junior Data Analyst in a local government office, who has been tasked with sorting and analyzing fleet inventory data that was previously imported and cleaned. I plan to use pivot tables to analyze the data in preparation for the results to be visualized in a dashboard and added to a data findings report later.