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#Business Analyst

Business Analyst is a promising job role that deals with Business Operations, Business Life Cycle, Data and Analysis  driven over a specific process drive the customers with rich Infographics of entire enterprise content as well as provide life cycle implementation plan.

✅ SQL & Excel for Business Analysis
✅ Real-time On-Job Challenges
✅ Power BI & Tableau Dashboards
✅ BRD/FRD Documentation
✅ Agile & Scrum Methodologies
✅ Process Modeling: UML, BPMN
✅ Data Visualization & Storytelling
✅ Python Basics for Data-Driven Insights
✅ Use Case Scenarios For Job Work
✅ 1:1 Mentorship, Interview Guidance

Business Analyst
Training Course Contents:

Module 1 : SQL Server & TSQL Queries

Ch 1: SQL SERVER INTRODUCTION

  • Database Introduction
  •  Types of Databases
  •  Need for & ETL, DWH
  •  BI Implementations
  •  SQL Server Advantages
  •  Version, Editions of MSSQL
  •  Data Analyst Job Roles

Ch 2: SQL SERVER INSTALLATIONS

  • SQL Server 2019, 2017
  • SSMS Tools Installation
  • Database Engine (OLTP)
  • SCM, Configuration Tools
  • Instance Types, Uses
  • Authentication Modes
  • Collation, File Stream

Ch 3: SQL BASICS – 1

  • Need for Databases, Tables
  • Need for SQL Commands
  • DDL, DML & DQL Statements
  • Database Creation @ GUI
  • Data Operations @ GUI
  • Session ID, SQL Context
  • DB, Tables, Data @ SQL

Ch 4: SQL BASICS – 2

  • DDL Variants in MSSQL
  • DML Variants in MSSQL
  • INSERT & INSERT INTO
  • SELECT & SELECT INTO
  • Basic Operators in SQL
  • Special Operators in MSSQL
  • ALTER, ADD, TRUNCATE, DROP

Ch 5: Data Imports, Schemas

  • Data Imports with Excel
  •  ORDER BY & UNION
  • UNION ALL For Sorting Data
  •  Creating, Using Schemas
  •  Real-world Banking Database
  •  Table Migrations @ Schemas
  •  2 Part, 3 Part & 4 Part Naming

Ch 6 : Constraints, Index Basics

  • Need for Constraints, Keys
  •  NULL, NOT NULL, UNIQUE
  •  Primary Key & Foreign Key
  •  RDBMS and ER Models
  •  Identity Property, Default
  •  Clustered Index, Primary Key
  •  Non Clustered Index, Unique

Ch 7: Joins & Views Basics

  • JOINS: Purpose. Inner Joins
  • Left / Right / Full Outer Joins
  • Cross Joins, Query Tuning
  • Creating & Using Views
  • DML, SELECT with Views
  • RLS : WITH CHECK OPTION
  • System Views & Metadata

Ch 8: Functions(UDF), Data Types

  • Using Functions in MSSQL
  •  Scalar Value Functions
  • Inline & Multiline Functions
  • Date & Time Functions
  • String, Aggregate Functions
  • Data Types : Integer, Char, Bit
  • SQL Variant, Timestamp, Date

Ch 9: Stored Procedures,Models

  • Stored Procedures & Usage
  • Creating, Testing Procedures
  • Encryption, Deferred Names
  • SPs for Validations, Analysis
  • System SPs, Recompilation
  • Normal Forms & Types
  • Data Models, Self-References

Ch 10: Triggers, Temp Tables

  • Need for Triggers
  • DDL & DML Triggers
  • Using Memory Tables
  • Data Replication, Automation
  • Local & Global Temp Tables
  • Testing & Using Temp Tables
  • SELECT .. INTO & Bulk Loads

Ch 11: DB Architecture, Locks

  • Planning VLDBs : Files, Sizing
  • Filegroups, Extents & Types
  • Log Files : VLF, Mini LSN
  •  Table Location, Performance
  • Schemas, Transfer, Synonyms
  • Transactions Types, Lock Hint
  •  Query Blocking Scenarios

Ch 12 : Cursors & CTEs, Links

  • Cursors : Realtime Use
  • Fetch & Access Cursor Rows
  • CTEs for SELECT, DML
  • CTEs: Scenarios & Tuning
  • Linked Servers, Remote Joins
  • Linked Servers: MSDTC, RPC
  • Tuning Remote Queries

Ch 13: Merge, Upsert & Rank

  • Need for Merge in ETL
  • Incremental Loads with SQL
  • MERGE and RANK Functions
  • Window Functions, Partition
  • Identify, Remove Duplicates

Ch 14: Grouping & Cube

  • Group By & HAVING
  • Cube, Rollup & Grouping
  • Joins with Group By
  • 3 Table, 4 Table Joins
  • Query Execution Order

Ch 15: Self Joins, Excel Analysis

  • Self Joins & Self References
  •  UNION, UNION ALL
  •  Sub Queries with Joins
  •  IIF, CASE, EXISTS Statements
  •  Excel Analytics, Pivot Reports

Module 2 : Power BI With AI

Ch 1 : Power BI Introduction

  • Reporting Basics & Types
  • Interactive,Analytical Reports
  • Paginated Reports (RDL)
  • Power BI Eco System
  • Power BI Tools,Service,Server
  • Need for Power Query (M)
  • Need for DAX & Cloud

Ch 2: Power BI Basic Reports

  • Power BI Desktop Installation
  • Basic Report Design (PBIX)
  • Data View, Data Models
  • Data Points, Aggregations
  • Focus Mode, Spotlight, Exports
  • ToolTip, PBIX and PBIT
  • Visual Interactions & Edits

Ch 3 : Grouping, Hierarchies

  • Creating Groups in Power BI
  • Groups : Creation & Usage
  • Group Edits Options
  • Bins & Bin Size, Bin Count
  • Hierarchies: Creation, Use
  • Drill Down, Drill Up
  • Conditional Drill Down

Ch 4 : Visual Sync, Filters

  • Slicer & Single Select
  • Multi Select Options
  • Integer, Character Slicers
  • Visual Sync with Slicers
  • Filters: Visual, Page, Report
  • Drill Thru Filters & Usage
  • Basic, Top & Advanced
  • Clear Filter Options, Resets

Ch 5 : Bookmarks, Big Data

  • Bookmarks Creation & Usage
  • Visual Interactions, Bookmarks
  • Images : Actions, Bookmarks
  • Big Data Access with Power BI
  • Storage Modes: Direct Query
  • Import & Performance Impact
  • Formatting & Data Refresh
  • Summary, Date Time Formats

Ch 6 : Power BI Visualizations

  • Chart and Bar Visuals
  • Line and Area Charts
  • Maps, TreeMaps, HeatMaps
  • Funnel, Card, Multrow Card
  • PieCharts & Settings
  • Waterfall, Sentiment Colors
  • Scatter Chart, Play Axis
  • Infographics, Classifications

Ch 7 : Power Query Level 1

  • Power Query (Mashup)
  • ETL Transformations in PBI
  • Power Query Expressions
  • Table Combine Options
  • Merge, Union All Options
  • Table Transformations

Ch 8 : POWER QUERY LEVEL 2

  • Any Column Transformations
  • String / Text Transformations
  • Numeric Analytics & Mashup
  • Date Time Transformations
  • Add Column Transformations
  • Expressions and New Columns

Ch 9 : POWER QUERY LEVEL 3

  • Parameters in Power Query
  • Static Parameters, Defaults
  • Dynamic Dropdowns, Lists
  • Linking with Table Queries
  • Column From Examples
  • Step Edits, Type Conversions

Ch 10 : Power BI Cloud – 1

  • Power BI Cloud Concepts
  • Workspace Creation, Usag
  • Report Publish & Edits
  • Semantic Models in Realtime
  • Dashboard Creation, Usage
  • Clone, Share, Subscribe
  • Q&A, Lineage, Settings

Ch 11 : Power BI Cloud – 2

  • Data Gateways, Data Refresh
  • Data Source Configurations
  • Data Refresh & Scheduling
  • Gateway Optimizations
  • Semantic Model Optimizations
  • Report Optimizations
  • Dashboard Optimizations

Ch 12 : Power BI Cloud – 3

  • Power BI Apps, Shares
  • App Sections & Options
  • App Updates, Security
  • Excel Analytics
  • Data Explorer Option
  • Sharing, Subscriptions
  • Alerts, Metrics, Insights

Ch 13 : Report Server & DAX

  • Power BI Report Server
  • Report Database, TempDB
  • Web Service & Server URL
  • Paginated Reports (RDL)
  • Report Builder Tool Usage
  • DAX : Purpose, Realtime Use

Ch 14: DAX Level 2

  • DAX Measures Creation, Use
  • DAX Functions: IIF, ISBLANK
  • SUM, CALCULATE Functions
  • DAX Cheat Sheet : Examples
  • Quick Measures in Power BI
  • Running Totals, Filters

Ch 15 : DAX Level 3

  • Star Rating Calculations
  • Data Models & DAX
  • Star & Snowflake Schemas
  • Dimensions, Fact Tables
  • DAX Expressions & Joins
  • DAX Variables, Usage

Ch 16 : DAX Level 4

  • Dynamic Report with DAX
  • SELECTED MEMEBER
  • Time Intelligence with DAX
  • PARALLELPERIOD, DATE
  • DAX with Big Data
  • Big Data Analytics

Ch 17 : Realtime Project Phase 1

  • Project Requirement Spec
  • Understanding Data, Formats
  • Report Pattern Design
  • Report Design & Modelling
  • Power Query, DAX, Insights
  • Analytical Reports in Cloud

Ch 18 : Realtime Project Phase 2

  • Complete Project Solution
  • Project FAQs, Key Roles
  • Real-world Considerations
  • Power BI Admin Concepts
  • Resume Points, FAQs
  • PL 300 Exam Guidance

Module 3 : Python Analytics

Ch 1. Python Introduction

  • Need for Data Analytics
  • Python in Data Analysis
  • History of Python
  • Python Versions
  • Python Implementations
  • Python Installations
  • Python IDE & Usage
  • Jupyter Notebooks

Ch 2. Python Basics, Architecture

  • Python Scripting Options
  • Basic Operations in Python
  • Python Scripts, Print()
  • Single, Multiline Statements
  • Adding Cells, Saving Notebook
  • Single, Multi Line Comments
  • Python : Internal Architecture
  • Compiler Versus Interpreter

Ch 3. Data Types & Variables

  • Integer / Int Data Types
  • Float & String Data Types
  • Boolean, Binary Types
  • Sequence Types: List, Tuple
  • Range, Complex & memview
  • Retrieving Data Type: type()
  • Multi Assignments & Casting
  • Unpack Collection, Outputs

Ch 4. Python Operators

  • Arithmetic, Assignment Ops
  • Comparison Operators
  • Logical, Identity Operators
  • Member, Bitwise Operators
  • Operator Precedence
  • If … Else Statement, Pass
  • Short Hand If, OR, AND
  • ELIF and ELSE IF Statements
  • Expressions, Ternary OPs

Ch 5: Python Loops, Iterations

  • Python Loop & Realtime Use
  • Python While Loop Statement
  • Break and Continue Statement
  • Using Print with While()
  • Iterations & Conditions
  • Exit Conditions & For Loops
  • Break, Continue & Range
  • __iter__() and __next__()
  • iter() and Looping Options

Ch 6: Python Collections

  • Python Collections (Arrays)
  • list() Constructor, print()
  • Python Tuples, Tuple Items
  • tuple() Constructor, Usage
  • Python Sets : Syntax Rules
  • Duplicates, Types, Ordered
  • Python Dictionaries: Usage
  • Changeable, Ordered Data
  • Dictionary Construct, type()

Ch 7: Python Functions

  • Python Functions & Usage
  • Function Parameters
  • Arguments, **kwargs
  • Default & List Parameters
  • Python Lambda Functions
  • Anonymous Functions
  • Recursive Functions, Usage
  • Return & Print @ Lamdba

Ch 8: Python Classes & Arrays

  • Python Classes & Objects
  • __init__() Function
  • __str__() Function
  • Self Parameters & Objects
  • Python Inheritance & Classes
  • Parent & Child Classes
  • __init__() & super() Function
  • Polymorphism in Python

Ch 9: Python Modules

  • import Python Modules
  • Variables in Modules
  • Built In Modules & dir
  • datetime module in Python
  • Date Objections Creation
  • strftime Method & Usage
  • imports & datetime.now()
  • Using Python Constructors

Ch 10: : Python JSON & RegEx

  • JSON Concepts, Usage
  • Dictionary & import json
  • Python Objects into JSON
  • Formatting & Ordering
  • json.dumps, print options
  • Python Regular Expressions
  • RegEx Module & Function
  •  search() & span() , Strings
  • Using RegEx with JSON

Ch 11: Python User Inputs & TRY

  • Try Except, Exception Handling
  • NameError Resolution
  • Python Finally Block, Usage
  • Raise an exception method
  • TypeError, Scripting in Python
  • Python User Inputs
  • Python Index Numbers
  • Named Indexes, Usage
  • input() & raw_input()

Ch 12: Python File Handling

  • File Handling, Activities
  • r, a, w, x modes
  • t, b Operations
  • Read Only Parts
  • Loop, Write, Close Files
  • Appending, Overwriting
  • import os, path.exists
  • f.open, f.write
  • f.read, f.close

Ch 13: Data Analytics – Pandas

  • Python Modules & Pandas
  • Pandas Codebase & Usage
  • Installation of Pandas
  • import pandas.DataFrame
  • Checking Pandas Version
  • Pandas Series, arrays
  • Labels : Creation, Use
  • series(), print()

Ch 14: Data Analytics – DataFrames

  • Indexes & Named Options
  • Locate Row and Load Rows
  • Row Index & Index Lists
  • Load Files Into a DataFrame
  • pd.read_csv() Function
  • pd.options.display.max_rows
  • df.to_string() Function
  • tail() & null() Function

Ch 15: Data Analytics – Pandas

  • Pandas – Cleaning Data
  • Replace, Transform Columns
  • Data Discovery & Column Fill
  • Identify & Remove Duplicates
  • dropna(), fillna() Functions
  • Pandas – Data Correlations
  • Good & Bad Correlation
  • Data Plotting & matlib Lib

Ch 16: : SQL Server & Python – 1

  • SQL & Databases
  • Azure Data Studio Tool
  • sp_execute_external_script
  • Input Data & Result Sets
  • DDL & DML with Python
  • SQL_out, SQL_in
  • Variables & Parameters
  • Versions, Package List
  • WITH RESULT SETS Options

Ch 17: SQL Server & Python – 2

  • pandas.Series with SQL DBs
  • Indexing Methods in Realtime
  • Convert series to data frame
  • Output values into data.frame
  • pymssql package in SQL Server
  • pip list & Package Manager
  • Python runtime, Py Package
  • pymssql.connect & Usage
  • Cursor Variables & Usage

Ch 18: Power BI with Python

  • Using Python Script Visual
  • PyScript Options & Tuning
  • Settings, Labelling Options
  • Running and Testing Scripts
  • Data Validations in Power BI
  • Power BI: ipynb Scripts
  • Interactive Reports
  • Data Formatting with Python
  • End to End Realtime Projects

Module 4 : Tableau

Ch 1: Tableau Intro, Installation

  • Introduction to Reports, Tableau
  •  Report Types, Data Sources
  •  Basic Understanding, Workflow
  •  Tableau as a Self-Service BI Tool
  •  Tableau Features, Advantages
  •  Tableau Public Desktop Tableau Prep Tools – Modelling
  •  Tableau Training Course Plan, Lab
  •  Study Material, Certifications

Ch 2: Basic Report Design

  •  Tableau Public Desktop
  •  Worksheet Creation, Options
  •  Row Shelf & Column Shelf
  •  Text, Detail, Tooltip, Colours
  •  VizQL , Dimension, Measures
  •  Marks, Shelves, Axis
  •  Grouping on Static Data
  •  Dynamic Data Grouping
  •  Hierarchies: Real-time Use

Ch 3: Architecture, Joins

  •  Drilldown Reports
  •  Data Sources, Connectors
  •  Tableau Server Components
  •  VizQL Server, Data Engine
  •  Fast Data Engine, Gateway
  •  Alias, Bins, Bookmarks
  •  Dashboards, Data Pane
  •  Data Source and Dimensions
  •  Using Joins in Tableau

Ch 4 : Big Data Access, Blending

  •  Azure SQL Database Access
  •  Remote Data Sources and Joins
  •  Using SQL Queries in Tableau
  •  Use Azure SQL Warehouse
  •  Data Blending in Tableau
  •  Reports with Multiple Sources
  •  Data Combination, Aggregation
  •  Show Data & Data Grouping
  •  Tableau Operators and Functions
  •  Tableau Calculations and Formats
  •  Calculations From Shelves

Ch 5: String, Date Functions

  •  ASCII, CHAR, LEN, ENDSWITH
  •  FIND, FINDNTH,LEFT, CONTAINS
  • LOWER, UPPER, LTRIM, RTRIM
  • MID, MIN, REPLACE, RIGHT
  •  SPACE, SPLIT, UPPER, MAX
  •  STARTSWITH, AND, CASE
  •  ELSE, ELSEIF, END, IF, IIF
  •  IFNULL, ISDATE, ISNULL, MAX
  •  MIN, NOT, OR, THEN, WHEN
  •  DATEPART, DATETRUNC, CH
  •  ISDATE, MAKEDATE, MONTH
  •  NOW, QUARTER, TOCH, YEAR

Ch 6: Table, LOD Calculations

  •  Custom Calculations, Appends
  •  Custom Date, Time Formatting
  •  Calculations Reuse and Edits
  • Date and Time Conversions
  •  Two Digit Conversions
  •  Table Functions with Tableau
  •  Running Total, Row Number
  •  Case, FIRST, LOOKUP
  •  Calculations, Level of Details
  •  Partitioning, LOD
  •  FIXED, INCLUDE, EXCLUDE

Ch 7: Tableau Viz – Level 1

  • Tableau Visualizations – Types
  •  Tableau Bar Charts and Types
  •  Horizontal, Coloured Bar Charts
  •  Stacked Bar Charts, Measures
  •  Side By Side Bar Charts and Use
  •  Interactive Bar Charts & Filters
  •  Continuous & Discrete Charts
  •  Dual, Area, Stacked, Combined

Ch 8: Tableau Viz – Level 3

  • Pie, Stacked Pie Charts
  • Side By Side Pie Charts
  •  Reverse and Row Count
  •  Donut Charts and Angle
  •  CrossTab Charts, Drill Downs
  •  Conditional Formatting
  •  Quick Calculations, Wishker
  •  Heat Maps in Real-time

Ch 9: Tableau Viz – Level 3

  •  Treemaps, Nested Rectangles
  •  Marks Type, and Label
  •  Treemaps with Bars & Tables
  •  Circle View Visualization
  •  Scatter Plot, Packed Bubbles
  •  Symbol Maps, Filled Maps
  •  Histograms, Motion Charts
  •  Bullet Graphs, Dimensions

Ch 10 : Tableau Filters

  • Tableau Filters – Types & Usage
  • Extract Filters, TDE (hyper)
  •  Data Source Filters (twb Files)
  •  Extract History, TDE Files
  •  Context Filters and Performance
  •  Measure Filters and Aggregations
  •  Filters Scope and Quick Filters

Ch 11: Parameters & Sets

  • Tableau Parameters
  •  Link Parameters, Calculations
  •  Calculations in Fields/View
  •  Dynamic Filters & Dimension
  •  Dynamic Measure, Parameters
  •  Sets: IN and OUT, Filters
  •  Sets & Groups & Hierarchies

Ch 12: Forecasts, Actions

  • Trend Lines, Reference Lines
  •  Forecasts, Smoothing
  •  Adding / Editing Bookmarks
  •  Data Analytics in Tableau
  •  Tableau Actions and Types
  •  Filter Actions: Static/Dynamic
  •  Highlights, Dynamic Types

Ch 13: Dashboards & Stories

  • Dashboards and Stories
  •  Building Dashboards
  •  Dashboard Size, Views, Objects
  •  Legends and Quick Filters
  •  Tiles, Layouts, Containers
  •  Dashboard Extensions, APIs
  •  Story Points, Bollinger Bands
  •  Data Cleansing – Tableau Prep

Ch 14: Tableau Server

  • Tableau Server – Architecture
  •  Tableau Server – Installation
  •  Publish Workbook, Shares
  •  Device & Custom Layouts
  •  Java Script API in Server
  •  Tableau Online Vs Server
  •  Security Advantages
  •  Adding Custom Layout

Ch 15: Tableau Online

  • Tableau Online: LIVE Reports
  •  Projects and Workbooks
  •  Tableau Report Views
  •  Custom Views, Comments
  •  Downloads, Exports
  •  Share, Subscribe, favourites
  •  Web Authoring, Publish Online
  •  Alerts,Snapshots,Phone Marks

Ch 16: Collaborate Tableau

  • Collaborate Tableau Server
  •  Account Settings, Drill Down
  • Custom Views, Comments
  •  Downloads and Exports
  •  Sharing, Subscription
  •  Web Authoring, Edits
  • Data Driven Alerts
  •  Stacked Bars, Alerting Views
  •  Navigations, Snapshots
  •  Interacting with Content

Ch 17: Manage Tableau

  • Administration Concepts
  •  Tableau Sites, Users, Groups
  •  Permissions & Locking
  •  Data Security & Filters
  •  Access Roles, Extraction
  •  Tableau Services Manager
  • Browser, Maintenance, CLI
  •  TSM Backups and Restores
  •  TSM Upgrades for Tableau
  •  Tabcmd & Realtime Use

Ch 18th: Realtime Project

  • Phase 1:
    Tableau Report Design;
    Visualizations; Analytics, Formatting;
  • Phase 2:
    Data Modelling, Tableau Prep;
    Dynamic Connections, Azure DB;
    Parameters and VizQL Scripts
  • Phase 3:
    Cloud and Server;
    Project FAQs and Solutions

Module 5 : Advanced Excel & Agile

Ch 1: Basic Functions

  • Excel Analytics
  •  SUM, AVERAGE, AGGR
  •  COUNT, COUNTA
  •  Absolute, Mixed
  •  Relative Referencing

Ch 2: Formatting and Proofing

  • Currency Format
  •  Format Painter
  •  Formatting Dates
  •  Custom and Special Formats
  •  Formatting Cells

Ch 3: Functions

  •  SUMIF, SUMIFS, COUNTIF
  •  COUNTIFS, AVERAGEIF
  •  AVERAGEIFS, NESTED IF
  •  IFERROR STATEMENT
  •  AND, OR, NOT

Ch 4: Protecting Excel

  • File Level Protection
  •  Workbook
  •  Worksheet Protection
  •  Security Concepts
  •  Realtime Issues, Solutions

Ch 5: Text Functions

  • Upper, Lower, Proper
  •  Left, Mid, Right
  •  Trim, Len, Exact
  •  Concatenate
  •  Find, Substitute

Ch 6: Adv. Techniques

  • Paste Formulas
  •  Paste Formats
  •  Paste Validations
  •  Transpose Tables
  •  Excel Analytics
  •  Excel Expressions

Ch 7: New in Excel & 365

  • Charts – Tree map & Waterfall
  •  Sunburst, Box and whisker Charts
  •  Combo Charts – Secondary Axis
  •  Adding Slicers Tool in Pivot & Tables
  •  Using Power Map and Power View
  •  Forecast Sheet, park lines E

Ch 8: New in Excel & 365

  •  Using 3-D Map
  •  New Controls in Pivot Table
  •  Various Time Lines
  •  Auto complete a data range
  •  Quick Analysis Tool
  •  Smart Lookup manage Store

Ch 9: Printing Workbooks

  • Setting Up Print Area
  •  Customizing Headers
  •  Templates
  •  Print Titles – Repeat Rows
  •  Real-world Considerations

Ch 10: Sorting and Filtering

  • Filtering on Text
  •  Numbers & Colours
  •  Sorting Options
  •  Advanced Filters
  •  Filter Criteria

Ch 11: What If Analysis

  • Goal Seek
  •  Scenario Analysis
  •  Data Tables
  •  PMT Function
  •  Solver Tool

Ch 12: Logical Functions

  • If Function
  •  How to Fix Errors – if error
  •  Nested If
  •  Complex if
  •  Excel Functions
  •  Excel Math Options

Ch 13: Data Validation

  • Number, Date & Time
  •  Text and List Validation
  •  Custom validations formulas
  •  Dynamic Dropdowns
  •  Realtime Considerations
  •  Smooth User Interface

Ch 14: Lookup Functions

  • V lookup / H Lookup
  •  Index and Match
  •  Nested V Lookup
  •  Reverse Lookup
  •  Worksheet linking
  •  V lookup with Helper Column

Ch 15: Pivot Tables – 1

  • Creating Simple Pivot Tables
  •  Classic Pivot table
  •  Choosing Field
  •  Filtering PivotTables
  •  Modifying PivotTable Data
  •  Grouping
  •  Calculated Fields

Ch 16: Pivot Tables – 2

  •  Array with IF, LEN
  •  MID function formulas.
  •  Array with Lookup functions.
  •  Various Charts
  •  SLICERS, Filter data
  •  Manage Primary Axis
  •  Manage Secondary Axis

Ch 17: Excel Dashboard

  •  Planning a Dashboard
  •  Adding Tables
  •  Charts to Dashboard
  •  Dynamic Contents
  •  Dashboard URLs
  •  Dashboard Shares
  •  Dashboard in Cloud

Ch 18: Agile Features

  • Using Agile
  •  Business Analytics Options
  •  BA Job Roles
  •  BA Job Requirements
  •  Technical Specifications
  •  RFPs and process
  •  Realtime Job Roles

SQL SCHOOL

24x7 LIVE Online Server (Lab) with Real-time Databases.
Course includes ONE Real-time Project.

Business Analyst Training FAQ's

What is Business Analyst Job Role?

A Business Analyst (BA) is responsible for bridging the gap between business needs and technology solutions. BAs gather, analyze, and document requirements, define business processes, and collaborate with stakeholders, developers, and testers to ensure solutions meet business objectives. Business Analysts play a key role in driving digital transformation, process improvements, and data-driven decision-making.

What are the Job Roles of a Business Analyst?

💼 Top Job Roles:

1️⃣ Gather, document, and validate business and functional requirements
2️⃣ Analyze and model business processes using tools like BPMN, UML
3️⃣ Create use cases, user stories, and functional specifications
4️⃣ Work with project managers, developers, testers, and stakeholders
5️⃣ Conduct gap analysis, feasibility studies, and impact assessments
6️⃣ Support user acceptance testing (UAT) and change management and more…!

What does our Business Analyst Training course contains?

The course is carefully curated with below module:
👉🏻Module 1: SQL Server & TSQL Queries
👉🏻Module 2: Power BI
👉🏻Module 3: Python Analytics
👉🏻Module 4: Tableau
👉🏻Module 5: Advanced Excel & Agile

Who can join this course?

  • Freshers aspiring to start a career as a Business Analyst

  • IT professionals / Developers / Testers transitioning to BA roles

  • Project coordinators / team leads expanding to analysis functions

  • Domain experts (banking, insurance, retail, etc.) looking to move into IT BA roles

  • Anyone interested in business process improvement and IT solution delivery

No prior coding experience is required. All concepts are taught from scratch

What training modes are available?

Option 1:        LIVE Online Training  (100% Interactive, step by step, assignments)

Option 2:        Self Paced Videos (100% practical, step by step with concept wise assignments)

You may choose any one of these options, same curriculum!

I (Trainer) shall be available for doubts and clarifications, assignment check and review.

Why should I choose SQL School for Business Analyst training?

👉🏻 Every session is Practical, Step by Step with Concept wise FAQs !!

👉🏻 100% results with on-time practice.  Daily Tasks for every session.

👉🏻 Concept wise tasks be submitted before next class for Job Waiters / Starters.

👉🏻 Concept wise tasks due for submission by Weekends for Working Professionals.

Why Choose SQL School

  • 100% Real-Time and Practical
  • ISO 9001:2008 Certified
  • Concept wise FAQs
  • TWO Real-time Case Studies, One Project
  • Weekly Mock Interviews
  • 24/7 LIVE Server Access
  • Realtime Project FAQs
  • Course Completion Certificate
  • Placement Assistance
  • Job Support
  • Realtime Project Solution
  • MS Certification Guidance