Module 1: Introduction to Excel for Analytics

Overview of Excel as an analytics tool

Importance of Excel in data analysis

Excel interface and basic navigation

Module 2: Essential Excel Functions for Data Analysis

Understanding and using basic functions (SUM, AVERAGE, COUNT)

Working with mathematical and statistical functions

Text functions for data cleaning and manipulation

Logical functions (IF, AND, OR)

Module 3: Data Import and Cleaning in Excel

Importing data from various sources (CSV, Excel, databases)

Data cleaning techniques and best practices

Handling missing data

Module 4: Data Visualization in Excel

Creating basic charts (bar charts, line charts, pie charts)

Formatting and customizing charts

Using sparklines for trend analysis

Module 5: PivotTables and PivotCharts

Introduction to PivotTables

Creating PivotTables for data summarization

Building PivotCharts for visual analysis

Module 6: Advanced Excel Functions for Analytics

VLOOKUP and HLOOKUP for data retrieval

INDEX and MATCH functions

Advanced IF statements and nested functions

Using array formulas

Module 7: Data Analysis with Excel Tables

Introduction to Excel Tables

Sorting and filtering data in tables

Using structured references

Module 1: Introduction to Databases and SQL

Understanding Databases

Definition and types of databases

Relational databases

Non-relational databases

Introduction to SQL

What is SQL?

SQL history and evolution

Importance of SQL in the industry

Module 2: Basic SQL Commands

SELECT statement

Retrieving data from a single table

Filtering data using WHERE clause

Sorting data using ORDER BY clause

INSERT, UPDATE, DELETE statements

Adding, modifying, and deleting data

Data integrity considerations

Module 3: Data Types and Operators

Common SQL data types

Working with text, numeric, and date data

Arithmetic and comparison operators

Module 4: Advanced Querying

JOIN operations

INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN

Cross join and self-join

Subqueries

Nested queries

Correlated subqueries

Set operations

UNION, INTERSECT, EXCEPT

Module 5: Data Filtering and Aggregation

GROUP BY clause

HAVING clause

Aggregate functions (SUM, AVG, COUNT, MIN, MAX)

Module 6: Data Modification

Transactions

COMMIT and ROLLBACK statements

Constraints (PRIMARY KEY, FOREIGN KEY, UNIQUE, CHECK)

Module 7: Views and Indexes

Creating and managing views

Indexes and their impact on performance

Module 8: Stored Procedures and Functions

Creating stored procedures

Input and output parameters

User-defined functions

Module 9: Database Security

User roles and permissions

GRANT and REVOKE statements

Securing sensitive data

Module 10: Best Practices and Optimization

Writing efficient queries

Indexing strategies

Query optimization techniques

Module 11: Introduction to NoSQL Databases

Overview of NoSQL databases

Contrasting SQL and NoSQL

Module 12: Case Studies and Real-world Applications

Analyzing real-world scenarios

Building practical solutions with SQL

Module 1: Introduction to Tableau

Overview of Tableau

Understanding the Tableau interface

Connecting to data sources

Data source considerations and best practices

Module 2: Data Preparation and Cleaning in Tableau

Importing and cleaning data

Managing metadata

Joins and relationships

Data blending

Module 3: Basic Visualization Techniques

Creating basic charts (bar charts, line charts, scatter plots)

Building maps and geographic visualizations

Using size and color in visualizations

Dual-axis charts and combo charts

Module 4: Intermediate Visualization Techniques

Working with calculated fields

Building hierarchies

Creating sets and groups

Trend lines and reference lines

Module 5: Advanced Visualization Techniques

Advanced chart types (treemaps, heat maps, box plots)

Dashboard design principles

Storytelling with data

Interactive dashboards and actions

Module 6: Data Analysis and Calculations

Aggregations and granularities

Window functions

Level of Detail (LOD) expressions

Table calculations

Module 7: Mapping and Spatial Analysis

Geographic data in Tableau

Customizing maps

Spatial analysis and calculations

Module 8: Integrating Tableau with Other Tools

Connecting Tableau with Excel, databases, and other data sources

Web data connectors

Tableau integration with R and Python

Module 9: Data Security and Permissions

User roles and permissions in Tableau

Securing data in Tableau Server and Tableau Online

Module 10: Tableau Server and Tableau Online

Deploying and managing Tableau Server

Publishing to Tableau Online

Collaboration and sharing in Tableau

Introduction to Business Analytics:

Overview of business analytics and its applications

Role of analytics in decision-making

Historical development and current trends

Statistical Foundations:

Descriptive and inferential statistics

Probability distributions

Hypothesis testing and confidence intervals

Data Management and Warehousing:

Data collection and cleaning

Data integration and transformation

Database management systems

Data warehousing concepts

Data Exploration and Visualization:

Exploratory data analysis (EDA)

Data visualization techniques

Dashboard design principles

Predictive Analytics:

Regression analysis

Time series analysis

Forecasting methods

Machine learning algorithms (e.g., linear regression, decision trees, clustering)

Prescriptive Analytics:

Optimization techniques

Simulation methods

Decision analysis