Learning Data Analytics Part 2: Extending and Applying Core Knowledge

Learning Data Analytics Part 2: Extending and Applying Core Knowledge

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 3h 23m | 774 MB

It’s one thing to work with data. It’s another to provide quality data sets and accurate visualizations for decisions to be made. If you are considering a course emphasis or a career in data analytics, this course can help you get off to a good start. Robin Hunt, CEO and co-founder of ThinkData Solutions, shares practical skills to help you get the most from your data and jumpstart your career in data. Robin discusses business rules, filtering out the noise in the data we all deal with, and how to deliver what decision-makers want. She covers how to create data sets with queries, joins, and appends, then goes into building aggregate data with total queries. Robin goes over pivots, how to use pivots to build basic dashboards and visualizations, and how to use Power Query for data transformations. She concludes with best practices for meetings and taking your work to the next level for your organization.

Table of Contents

1 Extending your data analysis skills
2 What you should know
3 Required software

1. Working with Business Data
4 Understanding business rules
5 Understanding noise in data
6 Breaking down the ask
7 Challenge Getting started
8 Solution Getting started

2. Building Data Sets with Queries
9 Understanding queries
10 Building basic select queries
11 Building distinct queries
12 Building queries with Joins
13 Building append queries
14 Building total queries
15 Challenge Total number of orders by customer
16 Solution Total number orders by customer

3. Chart Data Anytime and Anywhere
17 Ad hoc reporting
18 Building basic charts visual
19 Visuals using conditional formatting
20 Setting templates and default charts
21 Linking verus embedding charts and data
22 Challenge Ad hoc presentation
23 Solution Ad hoc presentation

4. Pivot Data Anytime and Anywhere
24 What are pivots
25 Build basic pivot tables
26 Modifying pivots for readability
27 Visualizing pivot tables
28 Using pivots to filter data sets
29 Challenge Best customer year
30 Solution Best customer year

5. Building in Power BI Desktop
31 Building dashboards
32 Building a matrix and visuals
33 Use cards for numbers
34 Using visuals in Power BI for filters
35 Publishing visuals and data sets
36 Challenge Product dashboard
37 Solution Product dashboard

6. Power Query Tips and Tricks for Data Analysts
38 Using column profile to learn the data
39 Appending data by leveraging folders
40 Duplicate or reference data sets
41 Unpivoting data from existing reports
42 Custom sorting in Power BI
43 Challenge Custom sort by education
44 Solution Custom sort by education

7. Presenting Data in Meetings
45 Consider how to present data in meetings
46 What to do before going company wide
47 Leveraging PowerPoint for presentations
48 Documenting data procedures
49 Challenge Highlight dashboard using PowerPoint
50 Solution Highlight dashboard using PowerPoint

51 Continuing on with data analysis