This course will teach you how to use large data sets to make critical decisions. This program was created for analysts, digital marketers, sales managers, product managers, and data novices looking to learn the essentials of data analysis. You’ll use industry tools, Excel, SQL, and Tableau to analyze large real-world data sets and create dashboards and visualizations to share your findings. Data Analytics culminates in a portfolio-grade presentation of your analysis and insights to your classmates and instructional team here
Advanced Excel
Introduction to Data Analytics
- Describe the objectives, deadlines, and logistics
- Determine the traits of a successful data analyst, including their mindset
- Discuss data formats and data ethics as they relate to the field of data analytics
Introduction to Microsoft Excel
- Excel Interface
- The Ribbon
- Quick Access Toolbar
- Excel views
- Create and Opening Workbooks
- Use Templates
- Format Data
- Save and Share Workbook
Data Cleaning and Formulas
- The structure of an Excel Function
- Working with the SUM() Function
- Working with the MIN() and MAX() Functions
- Working with the AVERAGE() Function
- Working with the COUNT() Function
- Adjacent Cells Error in Excel Calculations
- Using the AutoSum Command
- Use recommended data cleaning methods
Aggregating Data with PivotTables
- Utilize standard tables and charts to analyze datasets.
- Understanding Excel PivotTables
- Creating an Excel PivotTable
- Formatting PivotTable Data
- Modifying Excel PivotTable Calculations
- Use Excel's aggregation features for datasets
Building Charts with Excel
- Creating an Excel Column Chart
- Working with the Excel Chart Ribbon
- Adding and Modifying Data on an Excel Chart
- Formatting an Excel Chart
- Moving a Chart to another Worksheet
- Working with Excel Pie Charts
Project 1: Real World Application of Project
SQL
Querying and Organizing Data with SQL
- Introduction to databases.
- Create Databases
- Drop Databases
- Use Databases
- Introduction to Tables
- The Basic Data Types
- Create Your Own Tables
- Drop Tables
- Practice writing and executing SQL queries, including SELECT, FROM, WHERE and ORDER BY statements.
- Work with logical and comparison operators in SQL.
- Write complex queries with AND/OR.
- Practice writing aggregate functions: MIN, MAX, SUM, AVG, and COUNT
MySQL CRUD Commands
- Insert Data
- Multiple INSERT
- MySQL Warnings
- NULL and NOT_NULL
- Set Default Values
- A Primer On Primary Keys
- Table Constraints
- Introduction to CRUD
- Preparing Our Data
- Official Introduction to SELECT
- Introduction to WHERE
- Introduction to Aliases
- The UPDATE Command
- Introduction to DELETE
Subqueries in SQL
- Query IN subqueries.
- Construct subqueries for multi-step operations
- Identify subquery use cases for various businesses. scenarios
Power BI
Overview
- Brief about PowerBI
- PowerBI Architecture
- 8 Components of Power BI
- Building Blocks of Power BI
Power BI Desktop
- Overview of Power BI Desktop
- Working with Data Model
- Setting up Relationships
- Working with different Visualizations
- Implementing Drill through
- Working with Tooltips
- Slicers & Filters
- Working with Bookmarks
- Custom Visuals
- Data Visualizations (For details please refer data visualization section below)
Data Visualizations
- Table & Matrix Usage
- Card and Multicard
- Working with Slicers
- Working with various Chart types (Clustered column chart, line, area etc.,) in Power BI
- Map Visualizations (Bing Map, Map Box)
- Color palettes in Charts
- Loading Shapes, text boxes, and images
- Custom visuals
- Power BI Q&A
Data Analysis Expressions (DAX)
- Why DAX
- DAX Syntax
- Data types in DAX
- Types of calculations
- DAX tables and Filtering
- Other DAX functions (Calculate, Filter, Lookup, SUM, SUMX, EARLIER, etc.,)
Power Query Editor
- Introduction to Power Query Editor
- Adding New columns / New Columns from Examples
> Playing with different transformations for Data Cleanse
> Conditional column, Duplicate Column
- Statistical / Standard functions
- Merge / Append Queries
Power BI Service
- Introduction to Power BI Service
- Publishing reports to Workspace
- Dashboard vs. Reports
- Creating Dashboards
- Quick Insights
- Working with different options in Power BI Service
- Creating Workspace
- Working with Apps
- Setting up Data Gateway
- Scheduled data refresh.
- Sharing reports with other users
Tableau
Introduction to Tableau
- Introduction to Tableau
- Importance of Tableau
- How Tableau fits with computing, learning and analysis today
- Data Structuring
Data Manipulation in Tableau
- Connect to the numerous data sources
- Create calculated fields to analyze data
- Create calculated tables
- Explore time-based data
Reports and Dashboards in Tableau
- Explore Tableau Desktop
- Connect to data sources
- Get data from Excel
- Transform data to include in a report
- Combine data from multiple sources
- Clean data to include in a report
- Visualize data
- Build a dashboard
- Collaborate and share
Project 2: This will be a real world project which will integrate all the learnings
Python
Python and Fundamentals of Programming
- Understanding what IDEs and text editors are and how they are used
- Creating variables and understanding data types
- Understanding operators and operations
- Writing basic input and output statements
- Handling strings
Flow
- Understand and explain the uses of logical operators
- Understand boolean values and create boolean expressions
- Build conditional statements to determine control flow
Loops and Functions
- Create and manipulate lists using methods
- Understand the for loop and explore its use cases
- Create and use functions
Introduction to Data and Data Analytics
- Understand what data is and its usefulness
- Explore the various sources and types of data available
- Discuss the value of data analytics
- Making a case for problem-solving with data
- Discuss the framework for data analytics
- The 3 stage process: Clean, Extract and Visualize
- Setting up Jupyter for data analytics
Data Cleaning with Python
- Understand the differences between categorical and numerical data
- Introduction to the pandas library
- Designing and manipulating Dataframes
- Joining datasets
- Understand common features of dirty data
- Handling missing values
- Scaling and normalization
- Parsing dates
- Text processing
Extracting insights using Python
- Understand and use the aggregation functions in pandas
- Generate summary statistics for data frames
- Explore the relationships between columns
- Basic Text Analytics
Advanced Python
Compound data types and their methods List, Tuples, Dictionary and sets
Concept of looping
Concept of control flow in loops If, if-else, if-elif-else statements Nested if statements
- For loop
- While loop
- Break, continue and pass statements
Functions
- Global, local and non-local functions
- Arguments
- Recursion function
I/O operations
- Concept of Input and output operations in Python
- File exception
- Directory and file management
- Exception handling in Python
Pandas in Python
- Panda basic operations
- Data types in Pandas
- Read and write operation in pandas
- Data manipulation
- Data Wrangling
Numpy in Python
- Concept of array
- Array manipulation using Numpy