This Business Analyst course from SQL School will transform you into a Business Analyst expert. In this Business Analyst course, you will learn the latest analytics tools and techniques, how to work with SQL databases, the art of creating data visualizations, and how to apply statistics and predictive analytics in a business environment in addition to Mock Interviews, Resume Guidance, Concept wise Interview FAQs and ONE Real-time Project.
| PLAN A | PLAN B | PLAN C | |
|---|---|---|---|
| Course includes | 1. T-SQL 2. Power BI |
1. T-SQL 2. Power BI 3. Python Analytics |
1. T-SQL 2. Power BI 3. Python Analytics 4. Adv Excel |
| Total Duration | 7 Weeks | 11 Weeks | 15 Weeks |
| Power BI Report Design | ✔ | ✔ | ✔ |
| Power BI Desktop, Custom Visuals | ✔ | ✔ | ✔ |
| Data Modelling with Power Query | ✔ | ✔ | ✔ |
| Data Modelling with DAX | ✔ | ✔ | ✔ |
| Power BI Cloud, Excel Analysis | ✔ | ✔ | ✔ |
| Power BI Mobile, R, REST API | ✔ | ✔ | ✔ |
| PL 300 Exam Guidance | ✔ | ✔ | ✔ |
| Real-Time Project in Power BI | ✔ | ✔ | ✔ |
| SQL Database, T-SQL Queries | ✔ | ✔ | ✔ |
| Normal Forms, Joins, Query Tuning | ✔ | ✔ | ✔ |
| Sub Queries, Stored Procedures | ✔ | ✔ | ✔ |
| Excel Pivot Tables, Pivot Charts | ✔ | ✔ | ✔ |
| Python Data Analytics | ❌ | ✔ | ✔ |
| Python DataFrames | ❌ | ✔ | ✔ |
| Pandas & BigData | ❌ | ✔ | ✔ |
| Excel Formulas & Conditions | ❌ | ❌ | ✔ |
| Excel Statistical Functions | ❌ | ❌ | ✔ |
| Lokup & Reference Functions | ❌ | ❌ | ✔ |
| Text,Date & Time Functions | ❌ | ❌ | ✔ |
| Formula Based Formattting | ❌ | ❌ | ✔ |
| Dynamic Array Formulas | ❌ | ❌ | ✔ |
| Total Course Fee ( Payable in Installments)* |
INR 17000 USD 215* |
INR 26000 USD 325* |
INR 33000 USD 415* |
| SQL Server & T-SQL Schedules | ||||
| S No | Time (IST, Mon - Fri) | Start Date | ||
|---|---|---|---|---|
| 1 | 6 AM - 7 AM | Apr 2nd | Register | |
| 2 | 8 AM - 9 AM | Apr 24th | Register | |
| 3 | 9 AM - 10 AM | Mar 19th | Register | |
| 4 | 6 PM - 7 PM | Apr 15th | Register | |
| 5 | 8 PM - 9 PM | Apr 9th | Register | |
| 6 | 9 PM - 10 PM | Mar 12th | Register | |
| Power BI Training Schedules | |||
| S No | Time (IST, Mon - Fri) | Start Date | |
|---|---|---|---|
| 1 | 8 AM - 9 AM | Apr 2nd | Register |
| 2 | 8 PM - 9 PM | Mar 14th | Register |
| Python Analytics Training Schedules | |||
| S No | Time (IST, Mon - Fri) | Start Date | |
|---|---|---|---|
| 1 | 8:30 AM - 9:30 AM | Mar 14th | Register |
| 2 | 7:30 PM - 8:30 PM | Mar 27th | Register |
If above schedules does not work for you, please register for Business Analyst Training Videos
Ch 1: DATABASE INTRODUCTION
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Ch 5: SQL Basics - 3, TSQL INTRO
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Ch 9: Functions, Procedures Basics
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Ch 2: SQL SERVER INSTALLATION
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Ch 6: Constraints, Index Basics
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Ch 10: TRIGGERS & TRANSACTIONS
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Ch 3: SSMS Tool, SQL BASICS - 1
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Ch 7: Joins Basics, TSQL Queries
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Ch 11: Normal Forms, Cursors
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Ch 4: SQL BASICS - 2
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Ch 8: Group By in TSQL, Views Basics
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Ch 12: TSQL Queries, SQL Analytics
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Case Study 1: Database Design with Tables, Constraints, Keys & Relations |
Case Study 2: Joins with Group By, Sub Queries, Views, Excel Analytics |
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Part 1: Power BI Report Design |
Part 2: Power Query, Cloud (Service) |
Part 3: DAX & Report Server |
Ch 1: POWER BI INTRODUCTION
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Ch 7: POWER QUERY LEVEL 1
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Ch 13: DAX Functions - Level 1
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Ch 2: Basic Report Design
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Ch 8: POWER QUERY LEVEL 2
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Ch 14: DAX Functions - Level 2
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Ch 3: Visual Interaction, Visual Sync
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Ch 9: POWER QUERY LEVEL 3
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Ch 15: DAX Functions - Level 3
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Ch 4: Grouping & Hierarchies
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Ch 10: POWER BI CLOUD - 1
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Ch 16: DAX Functions - Level 4
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Ch 5: Filters & Bookmarks
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Ch 11: POWER BI CLOUD - 2
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Ch 17: Power BI Report Server
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Ch 6: Big Data Access, Visuals
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Ch 12: POWER BI CLOUD - 3
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Ch 18: Power BI Admin & AI
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Power BI : Realtime Project (Sales - Retail) |
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Phase 1 : Basic Report Design
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Phase 2 : SME Level
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Phase 3: Deployments (Cloud, Server)
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Part 1: Python Fundamentals |
Part 2: Python For Data Analytics - 1 |
Part 3: Python For Data Analytics - 2 |
Ch 1: Data Analytics Intro & Python
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Ch 7: Python Functions
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Ch 13: Data Analytics - Pandas
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Ch 2: Basic Operations with Python
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Ch 8: Python Classes & Arrays
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Ch 14: Data Analytics - DataFrames
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Ch 3: Data Types & Variables
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Ch 9: Python Modules
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Ch 15: Data Analytics - Pandas
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Ch 4: Python Operators, Conditions
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Ch 10: Python JSON & RegEx
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Ch 16: SQL Server with Python - 1
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Ch 5: Python Loops, Iterations
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Ch 11: Python User Inputs & TRY
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Ch 17: SQL Server with Python - 2
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Ch 6: Python Collections
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Ch 12: Python File Handling
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Ch 18: Power BI with Python
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