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EBOOK
Data Analytics Explained
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- PDF eBook
- 300+ Pages
- 1-click download
- High Quality Data Analytics Book
- Easy language, to-the-point concepts
- Easy PDF download
Why Buy This Book?
Practical Application: Emphasize hands-on learning with real-world examples.
Data Visualization Mastery: Highlight the importance of effective data visualization skills.
Industry Applications: Illustrate how analytics is applied in specific industries.
Data-driven Decision Making: Emphasize the role of data in making informed business decisions.
Table of content
1. Introduction to Excel for Data Analysis
● Overview of Excel interface
● Basics of navigating and working with sheets
● Introduction to cells, rows, columns, and ranges
● Understanding basic functions (SUM, AVERAGE, COUNT)
● Working with mathematical and statistical functions
● Introduction to text functions for data manipulation
2. Advanced Formulas and Functions
● Working with logical functions (IF, AND, OR)
● Exploring lookup functions (VLOOKUP, HLOOKUP, INDEX, MATCH)
● Introduction to array formulas
● Identifying and handling missing data
● Removing duplicates and dealing with errors
● Text-to-columns and data splitting techniques
3. Data Formatting and Visualization
● Formatting data for analysis
● Creating basic charts and graphs
● Tips for effective data presentation
● Introduction to PivotTables for dynamic data analysis
● Creating PivotCharts for visual insights
● Customizing and formatting PivotTables and PivotCharts
4. Time-saving shortcuts and productivity hacks
● Time-saving shortcuts and productivity hacks
● Excel with AI
5. Introduction to SǪL and Database Fundamentals
● Overview of SǪL and its applications
● Introduction to relational databases
● Basic SǪL syntax and structure
● Creating and modifying tables with CREATE and ALTER
● Understanding data types and constraints
6. Retrieving Data with SELECT Statements
● Basics of SELECT statements
● Filtering data with WHERE clause
● Sorting results with ORDER BY
7. Aggregation and Grouping
● Understanding aggregate functions (SUM, AVG, COUNT)
● Grouping data with GROUP BY
● Working with complex WHERE conditions
● Using operators (AND, OR, NOT, etc)
8. Window Functions and Analytic Ǫueries
● Introduction to window functions
● Performing analytic queries with OVER clause
7. Joins and Subqueries
● Performing INNER and OUTER joins
● Using subqueries for complex queries
9. Case Statements and CTE Ǫueries
● Understanding and using CASE statements in SǪL
● Applying CASE statements in data analysis scenarios
● Introduction to Common Table Expressions
● Using CTEs for recursive queries and data manipulation
10. Time-saving shortcuts and productivity hack
● Optimization of queries
● Optimization of queries using AI
● Interview based SǪL queries
11. Working on live project
● Working on industry orient data
● Problem solving using SǪL on industrial data
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