Learning Data Analytics (expanded edition)

Learning Data Analytics (expanded edition)

English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 39m | 321 MB

Every person who works with data has to perform analytics at some point. This popular training course—dramatically expanded and enhanced for 2018—teaches analysts and non-analysts alike the basics of data analytics and reporting. Robin Hunt defines what data analytics is and what data analysts do. She then shows how to identify your data set—including the data you don’t have—and interpret and summarize data. She also shows how to perform specialized tasks such as creating workflow diagrams, cleaning data, and joining data sets for reporting. Coverage continues with best practices for data analytics projects, such as verifying data and conducting effective meetings, and common mistakes to avoid. Then learn techniques for repurposing, charting, and pivoting data. Plus, get helpful productivity-enhancing shortcuts and troubleshooting tips for the most popular data analytics program, Microsoft Excel.

Topics include:

  • Defining data analysis
  • Understanding the data analyst role and other roles
  • Identifying data, data fields, and data types
  • Learning syntax
  • Finding existing data
  • Cleaning data
  • Data best practices
  • Working with business data
  • Charting data
  • Building pivot tables and charts
  • Using Excel for data analysis
Table of Contents

Introduction
1 Welcome
2 What you should know
3 How to use the exercise files

Getting Started with Data Analysis
4 Defining data analysis and data analyst
5 Discovering if you are an analyst
6 Understanding roles in data analysis
7 Discovering skills of the data analyst

Fundamentals of Data Understanding
8 Learning to identify data
9 Learning about data fields and types
10 Dealing with the data we dont have
11 Learning syntax

Key Elements to Understand When Starting Data Analysis
12 Learning to interpret existing data
13 Finding existing data
14 Understanding joins
15 Understanding data and workflow
16 Cleaning data

Getting Started with a Data Project
17 Getting started with data best practices
18 Learning about data governance
19 Understanding truths
20 Discovering common mistakes of beginners

Repurposing Data versus Remanufacturing Data
21 Repurposing data
22 Understanding source data
23 Creating reusable data
24 Building data sets to filter data

Working with Business Data
25 Understanding business rules
26 Creating a data dictionary
27 Creating read me information
28 Documenting data procedures

Chart Data Anytime and Anywhere
29 Building basic charts visual
30 Linking versus embedding charts and data
31 Setting default charts and charts shortcuts

Pivot Data Anytime and Anywhere
32 Build in basic pivots
33 Modifying pivots to make them more meaningful to read
34 Building pivot charts with slicers

Excel Tips and Tricks for Data Analysts
35 Selecting data and naming data
36 Learning to split text with delimiters
37 Removing duplicates
38 Transposing data

Conclusion
39 Next steps