Coaching Session 6 : Identify: Finding the Right Data

In this section you will learn:

1. Understand how to validate data, how to clean data, and how to prepare it for analysis
2. Master Cleaning Data for Pivot Tables
3. Data Analysts need to optimize their data so that it is ready for easy analysis.

FINDING DATA

1. Write requirements 
2. Source data
3. Clean data
4. Validate data
5. Prepare for analysis

CLEANING DATA

AKA data cleansing or data scrubbing, this is the process of identifying and correcting errors, inconsistencies, and inaccuracies in data.

The goal of data cleaning is to ensure that the data is accurate, consistent, and ready for analysis.

Data cleaning typically involves the following steps:

1. Identifying errors 
2. Correcting errors 
3. Standardizing data
4. Removing irrelevant data 
5. Verifying accuracy

PIVOT TABLES

Are used to summarize and analyze data. They are good for the following purposes:

1. Data aggregation
2. Data summarization
3. Data comparison
4. Data exploration
5. Data reporting 
6. Data analysis

MOCK DATA

Can be used in a variety of situations, but it’s important to consider the context and purpose of the data.

Mock data can be useful for:

1. Development and Testing
2. Employee Training 
3. Prototyping

Remember, mock data may not accurately reflect real-world data and therefore should not be used for making important business decisions or drawing conclusions.

Additionally, it’s important to ensure that the mock data does not contain any sensitive or personally identifiable information that could compromise the security or privacy of individuals.

AIM / DR. LEGARA

Dr. Erika Fille Legara is a Filipino physicist, complexity scientist, and data science researcher. She is currently an Assistant Professor at the Asian Institute of Management (AIM) in the Philippines and is also a member of the Complexity Science Group at the University of the Philippines Diliman. 

Her research can be particularly helpful to data analysts who are interested in using complex systems thinking to gain new insights and drive innovation in their organizations.

 

Portfolio

Email Subject: Data Analytics – Portfolio 6

1. Complete the Data Cleaning Exercise.
2. Review the assigned Excel spreadsheet and optimize the data columns and rows for easier analysis. Please submit your edited version of the spreadsheet. Once ready, run a pivot table to answer the 3 assigned questions. Answer these on a separate tab of the spreadsheet you submit.
   • Data Analytics Course HR Sample Data