Data Analyst is a promising job role that deals with Data, Analysis, Derived Information and drive to Infographics of enterprise content. This role also involves Data collection, data processing, and data analysis to identify trends, patterns, and relationships that can be used to solve problems and make informed decisions with ease !
✅ SQL for Data Analysis & Reporting
✅ Advanced Excel, Pivot Tables, Dashboards
✅ Power BI for Interactive Visualizations
✅ Data Cleaning with Power Query
✅ Python: Pandas, NumPy, Visualization
✅ Statistics, Exploratory Data Analysis (EDA)
✅ Business Intelligence & Storytelling
✅ Real-Time Projects with Case Studies
✅ Resume Building, Portfolio & GitHub Profile
✅ 1:1 Mentorship & Interview Preparation
Data Analyst Training
Module 1 : SQL Server & TSQL Queries
Ch 1: Database Intro & Job Roles
- Database Introduction
- Database Types: OLTP, DWH
- DBMS & Realtime Use
- DBMS Software & Purpose
- SQL : Purpose & Use
- SQL Server Versions, Editions
- Job Roles & Responsibilities
Ch 2: SQL Server Installations
- SQL Server 2022 Installations
- SQL Server 2019 Installations
- SSMS Tool Installation
- Server Connections, Properties
- Instance & Instance Types
- Authentication Types
- System Databases & Purpose
Ch 3: SQL Basics V1 (Commands)
- Database, Tables & Columns
- SQL Basics: Purpose
- DDL Statements
- DML Statements
- DQL Statements
- Verifications @ GUI
- Basic SELECT Queries
Ch 4: SQL Basics V2 (Operators)
- DDL Variants in MSSQL
- DML Variants in MSSQL
- INSERT & INSERT INTO
- SELECT & SELECT INTO
- Basic Operators in SQL
- Special Operators in MSSQL
- ALTER, TRUNCATE, DROP
Ch 5: Excel Data Imports
- Data Imports with Excel
- SQL Native Client
- Order By: Asc, Desc
- Order By with WHERE
- TOP & OFFSET
- UNION ALL
- UNION, Data Appends
Ch 6: Schemas & Security
- Schemas: Creation, Usage
- Schemas & Table Grouping
- Using Default Schema
- Real-world Banking Database
- Table Migrations @ Schemas
- 2 Part, 3 Part & 4 Part Naming
- Verifying Schemas in UI
Ch 7: Constraints & Keys Basics
- Need for Constraints, Keys
- Null, Not Null Constraints
- Unique Key Constraint
- Primary Key Constraint
- Foreign Key & References
- Default Constraint & Usage
- DB Diagrams & ER Models
Ch 8: Indexes Basics, Tuning
- Indexes & Tuning
- Clustered Index, Primary Key
- Non Clustered Index & Unique
- Creating Indexes Manually
- Verifying Indexes
- Composite Keys, Query Optimizer
- Composite Indexes & Usage
Realtime Case Study 1
Ch 9: Joins Basics
- Joins: Table Comaparisons
- Inner Joins & Matching Data
- Outer Joins: LEFT, RIGHT
- Full Outer Joins & Audits
- Cross Joins & Table Combinations
- Joining more than 2 tables
- Joining Tables with Aliases
Ch 10: Views & RLS
- Views: Realtime Usage
- Storing SELECT in Views
- DML, SELECT with Views
- RLS: Row Level Security
- WITH CHECK OPTION
- Database Audits & Metadata
- Important System Views
Ch 11: Stored Procedures
- Stored Procedures: Realtime Use
- Parameters Concept with SPs
- Procedures with SELECT
- System Stored Procedures
- Metadata Access with SPs
- SP Recompilations
- Stored Procedures, Tuning
Ch 12: User Defined Functions
- Using Functions in MSSQL
- Scalar Value Functions
- Inline & Multiline Functions
- Parameterized Queries
- Date & Time Functions
- String Functions & Queries
- Aggregated Functions & Usage
Ch 13: Triggers & Automations
- Need for Triggers
- DDL & DML Triggers
- For / After Triggers
- Instead Of Triggers
- Memory Tables with Triggers
- Data Replication, Automation
- Disabling DMLs & Triggers
Ch 14: Transactions & ACID
- Transaction Concepts in OLTP
- Transaction Types in Realtime
- Auto Commit, Explicit Transaction
- COMMIT, ROLLBACK
- Checkpoint & Logging
- Lock Hints & Query Blocking
- READPAST, LOCKHINT
Ch 15: Cursors & Fetch
- Cursors: Realtime Usage
- Cursor Declaration Types
- Open Cursor, Close Cursor
- Local & Global Cursors
- Scroll & Forward Only Cursors
- Static & Dynamic Cursors
- Fetch, Absolute Cursors
Ch 16: CTEs & Tuning
- CTE: Common Table Expression
- Creating and Using CTEs
- CTEs and In-Memory Processing
- Using CTEs for DML Operations
- Using CTEs for Data Retrieval
- Using CTEs for Tuning
- CTEs For Duplicate Row Deletion
Realtime Case Study 2
Ch 17: Relations, Normal Forms
- Adding PK to Tables
- Adding FK to Tables
- Cascading Keys
- Self Referencing Keys
- Database Diagrams
- Normal Forms : 1 NF, 2 NF
- 3 NF, BCNF and 4 NF
Ch 18: Self Joins, EXISTS
- Joining same table
- Correlated Queries
- Joining Tables, Queries
- Self Joins with WHERE
- Self Joins with UNION
- Self Joins with Order By
- Self Joins with Views
Ch 19: Remote Joins
- Working with Multiple Servers
- Multi Server Access from SSMS
- Linked Servers Creation, Tests
- 4 Part Naming Convention
- Remote Data Access
- RPC & RPC OUT
- Remote Joins & Data Analysis
Ch 20: Sub Queries
- Sub Queries Concept
- Sub Queries & Aggregations
- Joins with Sub Queries
- Sub Queries with Aliases
- Sub Queries with OrderBy
- Sub Queries with WHERE
- Sub Queries, Joins, Where
Ch 21: Group By Queries
- Group By, Distinct Keywords
- GROUP BY, HAVING
- Cube( ) and Rollup( )
- Sub Totals & Grand Totals
- Grouping( ) & Usage
- Group By with UNION
- Group By with UNION ALL
Ch 22: Joins with Group By
- Joins with Group By
- 3 Table, 4 Table Joins
- Join Queries with Aliases
- Join Queries & WHERE
- Join Queries & Group By
- Joins with Sub Queries
- Query Execution Order
Ch 23: Data Types & Conversions
- Integer Data Types
- Character, MAX Data Types
- Decimal & Money Data Types
- Boolean & Binary Data Types
- Date and Time Data Types
- Table, SQL_Variant Types
- Cast( ) and Convert( ) Functions
Ch 24: Window Functions, CASE
- IIF Function and Usage
- IIF with Tables, Joins
- CASE Statement Usage
- Window Functions (Rank)
- Row_Number( )
- Rank( ), DenseRank( )
- Partition By & Order By
Realtime Case Study 3
Module 2 : Power BI
Ch 1: Power BI Intro, Installation
- Power BI Eco System
- Report Types & Usage
- Power BI Tools, Cloud
- Power BI Components
- Power Query (M), DAX
- Power BI: Co-Pilot & AI
- Power BI Installations
Ch 2: Report Design Concepts
- Basic Report Design (PBIX)
- Get Data, Canvas (Design)
- Data View, Data Models
- Data Points, Aggregations
- Focus Mode, Spotlight
- PDF Exports From Power BI
- ToolTip, PBIX Reports
Ch 3: Visual Interactions, PBIT
- Data View Concepts
- Visual Interactions & Edits
- Limitations with Visual Edits
- Creating Power BI Templates
- CSV Exports & PBIT Imports
- Optimizing Power BI : Caching
- PBIX Versus PBIT
Ch 4: Grouping, Hierarchies
- Power BI : Field Values
- Field Value Groups
- Creating Groups : Lists
- Creating Groups: Bins
- List Items & Group Edits
- Bin Size & Bin Count
Ch 5: Slicer & Visual Sync
- Slicer Visual in Power BI
- Slicer: Format Options
- Single Select, Multi Select
- Slicer: Select All On / Off
- Integer, Character Slicers
- Visual Sync with Slicers
Ch 6: Hierarchies & Drill-Down
- Hierarchies: Creation, Use
- Hierarchies: Advantages
- Drill Up, Drill Down
- Conditional Drill Down
- Filtered Drill Down
- Table View of Data Points
Ch 7: Filters & Drill Thru
- Power BI Filters
- Basic, Top & Advanced
- Visual Filters, Page Filters
- Report Level Filters
- Clear Filter Options, Resets
- Drill Thru Filters & Usage
Ch 8: Bookmarks, Buttons
- Power BI Bookmarks
- Bookmarks Creation, Use
- Images: Actions, Bookmarks
- Buttons: Actions, Bookmarks
- Page to Page Navigations
- Score Cards, Master Pages
Ch 9: SQL DB Access & Big Data
- SQL DB Access , Queries
- Storage Modes: Direct Query
- Formatting & Date Time
- Storage Modes in Power BI
- Storage Modes & Formatting
- Azure (Big Data) Access
Ch 10: Power BI Visualizations
- Charts, Bars, Lines, Area
- TreeMaps & HeatMaps
- Funnel, Card, Multrow Card
- PieCharts & Waterfall
- Scatter Chart, Play Axis
- Infographics, Classifications
Ch 11: Power Query Introduction
- Power Query (Mashup)
- ETL Transformations in PBI
- Power Query Expressions
- Table Combine Options
- Merge, Union All Options
- Close, Apply & Visualize
Ch 12: Power Query : Table Tfns
- Table Duplicate, Reference
- Group By Transformation
- Aggregate, Pivot Operation
- First Row as Header
- Reverse Rows, Count Rows
- Advanced Power Query Mode
Ch 13: Power Query: Column Tfn
- Any Column Transformations
- Change Data Type
- Detect Data Type
- Rename, Replace, Move
- Fill Up, Fil Down
- Step Edits & Rollbacks
Ch 14: Power Query: Text, Date
- String / Text Transformations
- Split, Merge, Extract, Format
- Numeric and Date Time
- Add Column & Expressions
- Expressions and New Columns
- Column From Examples
Ch 15: Power Query: Parameters
- Parameters in Power Query
- Static Parameters, Defaults
- Dynamic Dropdowns, Lists
- Linking with Table Queries
- Column From Examples
- Step Edits, Type Conversions
Ch 16: Power BI Cloud: Publish
- Power BI Cloud Concepts
- Workspace Creation, Usage
- Workspace Items
- Report Publish Cloud
- Report Edits in Cloud
- Semantic Models & Usage
Ch 17: Power BI Cloud Dashboards
- Power BI Dashboards
- Dashboard Creation, Usage
- Pin Visuals
- Pin LIVE Pages
- Add Image, Video Tiles
- Q&A & Pin Tiles
Ch 18: Power BI Cloud Operations
- Report Shares, Alerts
- Subscriptions, Exploration
- Downloads & Edits
- Cloning in Cloud
- QR Codes, Web Publish
- Lineage & Metrics
Ch 19: Power BI Cloud Gateways
- Data Gateways, Data Refresh
- Install, Configure Gateways
- Data Sources Configurations
- Dataset Configurations
- Data Refresh & Scheduling
- Gateway Optimizations
Ch 20: Power BI Cloud Apps
- Power BI Apps: Creation
- App Sections & Content
- Audience Options
- App Security & Sharing
- App Updates, Favorites
- App URL, End User Access
Ch 21: Power BI Report Server
- Power BI Report Server
- Report Server Vs Cloud
- Installation, Configuration
- RS Config Tool Options
- Report Database, TempDB
- Web Service & Server URL
Ch 22: Paginated Reports
- Report Builder Tool
- Paginated Report (RDL)
- SQL Database Access
- SQL Queries For RDL
- Tablix, Chart Wizards
- Fields & Drill-Down
- RDL Report Publish
Ch 23: DAX Concepts (Basics)
- DAX Concepts (Introduction)
- DAX : Realtime Use
- DAX Columns: Creation, Use
- DAX Measures: Creation, Use
- DAX Functions: IIF, ISBLANK
- SUM, CALCULATE Functions
- DAX Cheat Sheet
Ch 24: DAX Quick Measures
- Quick Measures in Power BI
- Average & Filters
- Running Totals
- Star Rating Calculations
- DAX Measures in Data View
- DAX in Visuals
- DAX in Cloud Reports
Ch 25: Data Modelling, DAX
- Dimensions Tables
- Fact Tables & DAX Measures
- Data Models & Relations
- DAX Expressions
- Star & Snowflake Schemas
- DAX Joins & Expressions
Ch 26: DAX Joins, Variables
- CALCULATEX & Variables
- COUNT, COUNTA, etc..
- SUM, SUMX, etc..
- SELECTED MEMEBER
- Filter Context, RETRUN
- Dynamic Report with DAX
Ch 27: DAX Time Intelligence
- Need for Time Intelligence
- Date Table Generation
- Time Intelligence with DAX
- PARALLELPERIOD, DATE
- CALENDAR, Total Functions
- YTD, QTD, MTD with DAX
Ch 28: DAX – Row Level Security
- RLS: Row Level Security
- Data Modelling & Roles
- Verify Roles (Testing)
- Add Cloud Users to Roles
- Dynamic Row Level Security
- Testing RLS in Power BI
Ch 29: Analytical Reports
- Analytical Report Concepts
- Excel Data Analytics
- Excel with Power BI Cloud
- SQL, AVRO, JSON Sources
- Analyze in Excel (Cloud)
- Excel Reports to Cloud
Ch 30: Introduction to CoPilot
- AI Components in Power BI
- Need for CoPilot
- CoPilot Practical Uses
- CoPilot with Desktop
- CoPilot with Cloud
- Need for AI Analytics (Fabric)
Ch 31: Realtime Project – Phase 1
- Customer Requirement
- Requirement Analysis
- Project Planning
- Creating Data Sheets
- Creating Data Models
- Scope of the Project
- Data Sheets, Project Planning
Ch 32: Realtime Project – Phase 2
- Report Design & Modelling
- Power Query Implementation
- DAX & Data Analytics
- Power BI Cloud (Service)
- Power BI Report Server
- End User Take Aways
- Implementation Phases
Ch 33: PL 300 Exam Guidance
- PL 300 Exam Benefits
- Data Analyst Exam Pattern
- Type of Questions
- Sample Questions, Answers
- Mock Certification
- Resume Guidance
- Mock Interviews
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: Pandas Transformations
- 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 DB & 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 & 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: Realtime Case Study
SQL SCHOOL
24x7 LIVE Online Server (Lab) with Real-time Databases.
Course includes ONE Real-time Project.
Data Analyst Training FAQ's
What is Data Analyst Job Role?
Data Analyst refers to the role that focuses on data extraction, transformation, analysis, and reporting. It involves collecting data from multiple sources (Apps, Files, Databases, Forms, IoT Devices, etc..), applying data mashup operations, performing statistical evaluations, and generating business insights and reports for informed decision-making.
What are the Job Roles of a Data Analyst?
💼 Top Job Roles:
Managing Big Data & Data Analysis
Managing IAM [Identity & Access Management]
Managing Data Warehouse (DWH) Databases for Reporting
Secure & Optimize Data Warehouse (DWH) Reports
Orchestrate the Data Flow for Analytics
Data Governance, Policy Management and more .. !
What does our Data Analyst Training course contain?
The course is carefully curated with below module:
👉🏻Module 1: MSSQL & TSQL Queries
👉🏻Module 2: Power BI
👉🏻Module 3: Python Analytics
Who can join this course?
Freshers looking to start a career in data or analytics
Working professionals wanting to shift to Python, Data Science, or Data Analyst roles
Students from any background interested in tech and data
IT and Non-IT professionals aiming to upskill
Anyone with basic computer knowledge and a passion for learning
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 Data 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
