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#DP 800 Exam Training

This Job Oriented Course is 100% practical, step by step. Carefully planned to make you understand the concepts with Basic to Advanced Level of Microsoft SQL with AI, use case scenarios and realtime project. This SQL with AI Course will make you Job Ready, help you to secure your job with ease.

Master DP-800 Certification with Real-Time Training

✅ Microsoft Fabric Core Concepts & Architecture
✅ Lakehouse Design & Delta Lake Fundamentals
✅ Data Ingestion, Pipelines & Orchestration
✅ Dataflows, Notebooks & Spark Transformation
✅ Fabric Data Warehouse & SQL Analytics
✅ Real-Time Intelligence & Event Streaming
✅ Power BI Reports & Semantic Layer in Fabric
✅ Data Security, Governance & Purview Basics
✅ DP-800 Exam Preparation & Practice Test

LIVE ONLINESelf-Paced Videos

Module 1: Database Concepts, MSSQL & TSQL Queries

Ch 1: SQL Database Job Roles

  • Introduction to Data
  • Database Job Roles
  • Database Intro, Types (OLTP, DWH, OLAP..)
  • SQL & MSSQL Introduction

Ch 2: Database Intro & Installations

  •  SQL Server 2025 Installations
  • SSMS Tool Installation
  •  AI Components
  • AI Workloads
  • Instance Concept
  • Authentications, Collations
  • Server Connections
  •  Version Checks

Ch 3: SQL Basics V1 (Commands)

  • Creating Databases (GUI)
  • Creating Tables, Columns (GUI)
  • SQL Basics (DDL, DML, etc..)
  • Creating Databases, Tables
  • Data Inserts (GUI, SQL)
  • Basic SELECT Queries

Ch 4: SQL Basics V2 (Commands, Operators)

  • DDL: Create, Alter, Drop, Add, modify, etc..
  • DML: Insert, Update, Delete, select into, etc..
  • DQL: Fetch, Insert… Select, etc..
  • SQL Operations: LIKE, BETWEEN, IN, etc..
  • Special Operators

Ch 5: Excel Data Imports

  •   Data Imports with Excel
  • Order By: Asc, Desc
  • Order By with WHERE
  • TOP & OFFSET
  • UNION, UNION ALL

Ch 6: Data Types

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  • Integer Data Types
  • Character, MAX Data Types
  • Decimal & Money Data Types
  • Boolean & Binary Data Types
  • Date and Time Data Types
  • SQL_Variant Type

Ch 7: Schemas & Batches

  • Schemas: Creation, Usage
  • chemas & Table Grouping
  • Real-world Banking Database
  • 2 Part, 3 Part & 4 Part Naming
  • Batch Concept & “Go Command

Ch 8: Constraints, Keys & RDBMS

  •   Null, Not Null Constraints
  • Unique Key Constraint
  • Primary Key Constraint
  • Foreign Key & References
  • Default Constraint & Usage
  •  DB Diagrams & ER Models

Ch 9: Normal Forms & Modeling

  •   Normal Forms: 1 NF, 2 NF
  • 3 NF, BCNF and 4 NF
  • Self Referencing Keys
  • Cascading Keys
  • Adding PK to Tables
  • Adding FK to Tables

Ch 10: Joins & Queries

  • Joins: Table Comparisons
  • Inner Joins & Matching Data
  • Outer Joins: LEFT, RIGHT
  • Full Outer Joins & Aliases
  • Cross Join & Table Combination
  • Joining more than 2 tables

Ch 11: Group By & Join Queries

  •  Group By, Distinct Keywords
  • GROUP BY, HAVING
  • Cube( ) and Rollup( )
  • Sub Totals & Grand Totals
  • Grouping( ) & Usage
  • Group By with Joins

Ch 12: Sub Queries & Joins

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  • Sub Queries Concept
  •  Sub Queries & Aggregations
  • Joins with Sub Queries
  • Sub Queries with Aliases
  • Sub Queries, Joins, Where
  • Correlated Queries
  • Joins with Sub Queries

Query Execution Order
Ch 13: Views & Data Analytics

  •  Views: Realtime Usage
  • Storing SELECT in Views
  • DML, SELECT with Views
  • Using Views with Excel
  • Excel Pivot Tables
  • Excel Pivot Charts
  • Important System Views

Ch 14: Stored Procedures – 1

  • Stored Procedures: Realtime Use
  • Parameters Concept with SPs
  • Procedures with SELECT
  • System Stored Procedures
  • Metadata Access with SPs
  • SP Recompilations
  • Stored Procedures, Tuning

Ch 15: Stored Procedures – 2

  •  Merge Statement
  • Upsert Operations with Merge
  • Merge with OLTP & DWH
  • Matched and Not Matched
  • Merge Statement inside SPs

Ch 16: User Defined Functions

  •  Using Functions in MSSQL
  • Scalar Functions in Real-world
  • Inline & Multiline Functions
  • Parameterized Queries
  • Date & Time Functions
  • String Functions & Queries
  • Aggregated Functions & Usage

Ch 17: Window Functions, CASE

  •  IIF Function and Usage
  • CASE Statement Usage
  • Window Functions (Rank)

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  •  Row_Number( )
  • Rank( ), DenseRank( )
  • Partition By & Order By

Ch 18: Triggers & Automations

  • Need for Triggers in Real-world
  • DDL & DML Triggers
  • For / After Triggers
  • Instead Of Triggers
  •  Memory Tables with Triggers
  • Disabling DMLs & Triggers

Ch 19: Transactions & ACID

  • Transaction Concepts in OLTP
  • Auto Commit Transaction
  • Explicit Transactions
  • COMMIT, ROLLBACK
  •  Checkpoint & Logging
  • Lock Hints & Query Blocking
  •  READPAST, LOCKHINT

Ch 20: Indexes Basics, Tuning

  •  Indexes & Tuning
  • Clustered Index, Primary Key
  •  Non Clustered Index & Unique
  • Creating Indexes Manually
  • Composite Keys, Query Optimizer
  •  Composite Indexes & Usage

Ch 21: CTEs & Tuning

  • Common Table Expression
  • Creating and Using CTEs
  • CTEs, In-Memory Processing
  • Using CTEs for DML Operations
  • Using CTEs for Tuning
  • CTEs: Duplicate Row Deletion

Ch 22: Cursors & Fetch

  •  Cursors: Realtime Usage
  •  Local & Global Cursors
  •  Scroll & Forward Only Cursors
  •  Static & Dynamic Cursors
  •  Fetch, Absolute Cursors

Ch 23: Temporary Tables

  •  TempDB: Realtime Use
  •  Local Temporary Tables
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  • Global Temporary Tables
  • Testing & Using Temp Tables
  •  Temp Tables across Sessions
  •  Auto Create Tables using Select
  •  SELECT .. INTO & Bulk Loads

Ch 24: Linked Servers

  •  Creating Linked Servers
  •  Testing Linked Servers
  •  Remote Joins Correlated Queries
  •  Remote DB Access
  • 4 Part Naming Conventions

Ch 25: Server Architecture

  •  Database Engine Components
  •  Parser, Compiler & Optimizer
  •  Protocols and Query Processing
  •  MDAC, CLR & Memory
  •  Parsing and Compilation
  • SQL OS Components

Ch 26: Realtime Case Study: Healthcare Scenario (Design)
Ch 27: Realtime Case Study: Healthcare Scenario (Queries)

Module 2: TSQL Programming

Ch 1: Variables & Try..Catch

  •  Variables: Declaration & Usage
  •  Assigning Values to Variables
  • SELECT & SET Operations
  •  Using Variables in SPs
  •  Variables Versus Parameters
  •  Try.. Catch Block with Variables
  • THROW Statement, Error Handling

Ch 2: Updatable Views

  •  Using Triggers with Views
  •  Updatable Views, DML
  •  Views & Stored Procedures
  •  Data Distributions in Tables
  •  Transactions with Procedures
  •  Conditional Commits in SPs
  •  Rollback Options in Realtime

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Ch 3: Stored Procedures & TVPs

  •  Using TVP with Procedures
  •  Creating User Defined Types
  • Big Data Copy & Transactions
  • Using SPs & Table Variables
  •  Transactional Integrity with SPs
  •  Conditional Commits, Rollbacks
  • Procedure Recompilations

Ch 4: Stored Procedures, Cursors

  •  Cursors Types: Local, Global
  •  Using Procedues with Cursors
  •  Formatting Queries, Nvarchar
  •  WHILE Loop: @Fetch Status
  •  Variables with Dynamic SQL
  •  sp_executesql Extended SP
  • Dynamic SQL Programming

Ch 5: SPs & Recursive CTEs

  •  CTEs: Common Table Expression
  •  CTEs For DML Operations
  •  Defining Recursive CTEs
  •  Anchor Element: Realtime Use
  •  Termination Checks and Loops
  •  Defining SPs with CTEs
  • Cautions with Recursive CTEs

Ch 6: Functions & Loops

  •  Inline, Table Line Functions
  •  Multi Line Table Functions
  •  Using LOOPs in Functions
  •  Variables & Return Values
  •  Table Generation Logic
  •  Date & Time Data Types
  • Calendar Data Generations

Ch 7: OpenRowSet, Debugging

  •  Reading JSON Data
  •  Using OPENROWSET( )
  •  OpenRowSet with Variables
  •  Debugging Stored Procedures
  •  Debugging Types in TSQL
  •  Debugging Techniques with SSMS
  •  Debug Options with Variables

Ch 8: PIVOT, UNPIVOT

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  • Reading Denormalized Data
  • Normalizing Table Data
  • PIVOT Operation with TSQL
  • PIVOT with Aggregates
  • FOR and IN Operators
  • UNPIVOT with TSQL
  • PIVOT with Functions, SPs

Ch 9: Temporary Tables

  • TempDB: Realtime Use
  •  Local Temporary Tables
  •  Global Temporary Tables
  •  Testing & Using Temp Tables
  • Temp Tables across Sessions
  • Auto CreateTables using Select
  • SELECT .. INTO & Bulk Loads

Ch 10: Change Data Capture

  •  CDC Concept
  •  Database Level CDC
  •  Table Level CDC
  •  CT Tables (Change Tracking)
  •  __$operation fields
  •  DDL & DML Tracking

Ch 12: DB Architecture (VLDB)

  •  Planning Large Databases
  •  Primary, Secondary Data Files
  •  Filegroups, Spacing and Sizing
  •  Log File: Usage and Precautions
  •  Creating Tables with Filegroups
  •  Pages and Extents for Storage
     VLF, MiniLSN & Checkpoint

Module 3: TSQL Tuning

Ch 1: Tuning: Audits, AM Tool

  •  Activity Monitor Tool
  •  Perfmon Tool & Counters
  •  Query Audits: DMVs, DMFs
  •  Plan Handle, Execution Time
  •  Long Running Queries
  •  Query Store & Buffer Cache
  •  Data Flush, Stats Collection

Ch 2: Tuning : Indexes

  •  Indexes : Sort Locations
  •  Clustered & Online Indexes
  •  Non Clustered, Column Store
  •  Included Indexes in Realtime
  •  Filtered Indexes & Usage
  •  Covering Index & Selectivity
  •  Indexed Views (Materialized)

Ch 3: Tuning: Partitions

  •  Partitions: Performance Tuning
  •  Partition Functions & Schemes
  •  Partition Un-partitioned Tables
  •  Compressions: ROW, PAGE
  •  Auditing Partitions
  •  Partitions Limitations in OLTP
  •  Partitions with DWH

Ch 4: Statistics & Tuning

  •  Statistics: Realtime Usage
  •  Index & Column Statistics
  •  Statistics & Key Purpose
  •  Verifying, Using Stats
  •  Statistics Versus Indexes
  •  Stats Updates on Tables
  •  Stats Updates on Views

Ch 5: Index Management

  •  Index Management Options
  •  Index Rebuilds, Re-Organize
  •  Database Maintenance Plans
  •  Page Count and Index Conditions
  •  Degree Of Parallelism Settings
  •  Resumable & Online Indexes
  •  PAUSE, RESUME in Rebuilds

Ch 6: Tuning Tools

  •  Tuning Tools: Workload Files
  •  Profiler Tuning, Events
  •  DTA, Profiler Options
  •  Physical Design Structures
  •  PDS Recommendations
  •  Query Execution Cache
  •  Tuning Tools: Precautions

Ch 7: Execution Plans

  •  Execution Plan Analysis
  •  IO Cost and CPU Cos
  • SubTree & Operator Cost
  • NUMA Nodes, Processor Affinity
  • Thread Count, DOP
  • Table & Index Scan, Index Seek
  • Index Selectivity & Tuning

Ch 8: Lock Management

  •  Open Transactions in Realtime
  •  Open Transaction, Blocking
  •  LOCKS: Types & Audits
  •  S, X, IX, U and MD Locks
  •  Sch-M and Sch-S Locks
  •  SP_WHO2, SP_LOCK
  •  sysprocesses & Lock Waits

Ch 9: Isolation Levels

  •  Lock Hints and Isolation Levels
  •  Read Committed, Uncommitted
  •  Serializable, Repeatable Read
  •  Snapshot Isolation, Versioning
  •  Read Committed Snapshot
  •  sysprocesses & sp_who2
  •  Choosing Correct Isolation Level

Ch 10: Deadlocks, LIVE Locks

  •  Deadlocks in Real-world
  •  Profiler Tool & Deadlocks
  •  Lock Management: Deadlocks
  •  Deadlock Graphs & Events
  •  Deadlock Avoidance, Prevention
  •  Deadlock Prevention
  •  sysprocesses & sp_who2

Module 4: Azure SQL Dev

Ch 1: Cloud Basics, Azure Funda

  •  Cloud Fundamentals
  •  Cloud Concepts, Benefits
  •  IaaS, PaaS, SaaS Cloud Types
  •  Azure Cloud Concepts
  •  Azure Resources & Usage
  •  Azure Services & Purpose
  •  Azure Account & Subscription

Ch 2: Azure SQL Deployments

  •  Azure SQL Services
  • Azure SQL Server Creation
  • Azure SQL Databases
  • Azure Firewall : Rules
  • Test Connections from SSMS
  • SSMS Tool : Test Connections
  • ADS Tool : Installation, use

Ch 3: Azure SQL DB Operations

  •  Azure SQL : DDL Statements
  •  Azure SQL: DML Statements
  •  Azure SQL: DQL Statements
  •  TCL & DCL Commands
  •  Differences with OnPrem
  •  Azure SQL DB Advantages

Ch 4: Azure SQL DB Migrations

  •  SQL DB Migration Options
  •  Data Migration Assistant: DMA
  •  DMA Tool, Migration Options
  •  On-Premises DB Export
  •  Azure SQL Database Import
  •  Azure Storage Account
  •  Linking SSMS with Azure

Ch 5: Azure SQL DB Licensing

  •  Azure SQL DB Licensing
  •  Per Database Licensing
  •  DTUs: Basic, Standard Types
  •  VPU and Plan Types
  •  DTU Versus VPU Licensing
  •  Elastic DTUs (eDTU) Usage
  •  Elastic Query Processing

Ch 6: Azure SQL DB Metrics

  •  Azure SQL DB Metrics
  •  CPU, Memory, Log Metrics
  •  Data File Metrics, Alerts
  •  Action Groups & Emails
  •  Query Performance Insight
  •  Automated Tuning Options
  •  Query Recommendations

Ch 7: Azure SQL DB Tuning, AI

  •  Automated Tuning Options
  • Manual Tuning Options
  • Server Level Tuning
  • Database Level Tuning
  • Create Index Option
  • Drop Index, Seek Options
  • Built-In Intelligence

Ch 8: Azure AI Search

  •  AI Search Service, Tuning
  •  AI Indexes, Practical Use
  •  Watermark Columns
  •  Triggers & Timestamp
  •  Filterable, Searchable
  •  Sortable, FaceTables
  •  Indexer & Data Refresh

Module 5: Azure Functions with TSQL

Ch 1: Azure Storage Account Concepts

  •  Azure Storage Accounts
  •  Standard & ADLS Accounts
  •  Containers & File Uploads
  •  File Operations
  •  Access Tiers

Ch 2: Azure Tables & ADF

  •  Azure Tables
  •  Entities and Properties
  •  Storage Service Operations
  •  OData Queries & Filters
  •  Data Loads with ADF

Ch 3: Azure Key Vaults

  •  Azure Encryptions at REST
  •  SMK & CMK Encryptions
  •  Azure Key Vaults & Keys
  •  Key Access Policies
  •  Rest, Transit Encryptions
  •  Realtime Considerations

Ch 4: Azure Logic Apps

  •  Azure Logic Apps
  •  Consumption Logic
  •  Standard Logic
  •  Logic App Connectors
  • Triggers & Parallel Branches
  • Schedules & Automations
  • Data Governance

Ch 5: Azure Functions

  •  Azure Functions
  •  Creating, Using Functions
  •  Azure Functions with TSQL
  •  TSQL Debugging
  •  Testing Azure Functions

Module 6: Fabric SQL (TSQL)

Ch 1: Fabric Introduction

  •  Need for Fabric, Big Data
  •  Fabric Data Engineering Model
  •  Fabric Components (Items)
  •  Microsoft Fabric: Advantages
  •  Cloud Warehouse & AI
  •  AI with CoPilot
  •  Azure Versus Fabric DWH

Ch 2: Fabric Account, Workspace

  •  Need for Fabric Workspace
  •  Workspace Creation Process
  •  Pins and New Items
  •  Item Categorization
  •  ETL, Storage, Analytical
  •  Streaming, Monitoring
  •  Compute & Separation

Ch 3: Fabric Architecture

  •  Intelligent Data Foundation
  •  Polaris Distributed Engine
  •  Stateless & Stateful
  •  Cache, Metadata, Xact & Data
  •  Fabric Tasks, Inputs & DAG
  •  State Machine & Statistics
  •  Hot Spot Recovery

Ch 4: Fabric Warehouse

  •  Fabric Warehouse Creation
  •  Fabric Warehouse Features
  •  Fabric Warehouse Properties
  • Fabric Warehouse Limitations
  • DWH Internal Operations
  • Default Schemas & Objects

Ch 5: Fabric Data Types

  •  Realtime use of Fabric Houses
  •  Exact, Approximate Numbers
  •  Date and Time Data Types
  •  Fixed & Variable Length
  •  Binary & String Data Types
  •  Fabric Type Limitations

Ch 6: SSMS Connections

  •  Warehouse SQL Connection
  •  Database Engine Server
  •  Multi Factor Authentication
  •  Warehouse Artifacts
  •  Executing .SQL Scripts
  •  Testing Fabric Artifacts

Ch 7: Fabric Caching

  •  Fabric Caching Process
  •  In-memory Cache, Disk Cache
  •  Cache Types: LRU /MRU
  •  Cold Cache / Cold Run
  •  Realtime use of Caching
  •  Performance Advantages
  •  Warehouse Optimizations

Ch 8: Fabric Statistics

  •  Query Engine Options
  •  Statistics Types
  •  Leverage Statistics
  •  Auto, Manual Statistics
  •  Update Statistics
  •  Statistics Consistency
  •  Statistics Lists & Reports

Ch 9: Time Travel

  •  Continuous Data Protection
  •  Data Storage, Retention
  •  FOR TIMESTAMP AS OF
  •  Time Travel Scenarios
  •  Time Travel Implementation
  • Time Travel on Queries
  • Time Travel Limitations

Ch 10: Aggregated Data Store

  •  Options for Data Aggregations
  •  Save As table, Save As View
  •  Single Table Aggregations
  •  Multi Table Aggregations
  •  Dynamic Conditions
  •  Parameterized Aggregations

Ch 11: Zero Copy Cloning

  •  User Layer, Storage Layer
  •  Cloning & Parquet Files
  •  Synapse Data Warehouse
  •  Data History Retention
  •  Point In Time , Schema Level
  •  Zero Copy Cloning Limitations

Ch 12: Fabric Security

  •  Workspace Security
  •  Warehouse Security
  •  Item Security & Roles
  •  Adding AD Users
  •  Item Security Limitations
  •  MFA & Client Security

Ch 13: Regular Expressions

  •  REGEXP_LIKE
  •  REGEXP_REPLACE
  •  REGEXP_SUBSTR
  •  REGEXP_INSTR
  •  REGEXP_COUNT
  •  REGEXP_MATCHES
  •  REGEXP_SPLIT_TO_TABLE

Ch 14: Fuzzy Logic & JSON

  •  EDIT_DISTANCE
  •  EDIT_DISTANCE_SIMILARITY
  •  JARO_WINKLER_DISTANCE
  •  MATCH Operator
  •  JSON_OBJECT
  •  JSON_ARRAY
  • JSON_ARRAYAGG
  • JSON_CONTAINS
  • OPENJSON
  • JSON_VALUE

Module 7: CoPilot & Git Hub

Ch 1: AI Concepts

  •  AI Introduction
  •  AI Concepts
  •  AI in SQL Server
  •  AI Workloads
  •  CoPilot Concepts

Ch 2: CoPilot Concepts

  •  CoPilot Architecture
  •  CoPilot with TSQL
  •  CoPilot in Fabric
  •  Model Context Protocol (MCP)
  •  GitHub Copilot
  •  MCP End Points

Ch 3: Security Concepts

  •  CoPilot & Security
  •  Always Encrypted
  •  Column Level Encryption
  •  Keys & Certificates
  •  Row Level Security
  •  GraphQL, REST, MCP endpoints

Ch 4: Data Events

  •  Event Management
  •  Change Event Stream (CES)
  •  Change Data Capture (CDC)
  •  Change Tracking
  •  Azure Functions
  •  Fabric Integrations

Module 8: DP 800 Exam Guidance

  •  DP 800 Exam Guidanc
  • DP 800 Exam Sample
  • DP 800 Exam Mock

 

Azure Data Engineer roadmap with Azure Data Factory, Databricks, Spark, and Delta Lake

DP-600 Training FAQ's

What is DP-600 Job Role?

A DP-600 certified professional is an Azure Enterprise Data Analyst Associate who designs, builds, and deploys end-to-end analytics solutions using Microsoft Fabric. The role focuses on working with lakehouses, warehouses, dataflows, pipelines, data models, and Power BI to deliver enterprise-grade data analytics solutions. DP-600 professionals ensure data is integrated, secured, modeled, and visualized effectively for business insights.

What are the Job Roles of a DP-600 Certified Fabric Data Analyst?

💼 Top Job Roles:

1️⃣ Design and implement lakehouse and warehouse data models in Fabric
2️⃣ Build and manage data pipelines and dataflows for ingestion and transformation
3️⃣ Create enterprise semantic models for Power BI reporting
4️⃣ Implement security, governance, and compliance in analytics solutions
5️⃣ Optimize performance of Fabric data solutions and reports
6️⃣ Collaborate with data engineers, architects, and business stakeholders and more..!

What does our DP-600 Training course contains?

The course is carefully curated with below module:
👉🏻Module 1: MSSQL & TSQL Queries
👉🏻Module 2: Power BI

Who can join this course?

  • Freshers aspiring for Azure Database Administrator roles

  • SQL DBAs moving to cloud database administration

  • On-prem DBAs upgrading to Azure SQL solutions

  • IT professionals seeking DP-300 certification

  • Anyone wanting to manage cloud-based SQL workloads

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 DP-600 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.

Training Modes

LIVE Online Training

Instructor Led

Self Paced Videos

 On-Demand

Corporate Training

With 100% Hands-On

Placement Partners

SQL School Fabric Data Analyst training certificate of completion issued in January 2026 with verification ID