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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.

Training Highlights

✅ 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

Modules We Learn

✅ Database Concepts, MSSQL & TSQL Queries
✅ Module 2: TSQL Programming
✅ Module 3: TSQL Tuning
✅ Module 4: Azure SQL Dev
✅ Module 5: Azure Functions With TSQL
✅ Module 6: Fabric SQL (TSQL)
✅ Modules 7: Copilot & Git Hub
✅ Module 8: DP 800 Exam Guidance

Course Duration: 2 Months

Mr. Sai Phanindra Tholeti, SQL Trainer with 20+ years of expertise, promoting SQL Developer Training at SQL School

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

What is the DP-800 Certification?

The Microsoft DP-800 is the Fabric Analytics Engineer Associate certification exam. It validates your ability to design, build, and manage end-to-end analytics solutions using Microsoft Fabric — including Lakehouses, Data Warehouses, Pipelines, Notebooks, Spark, Real-Time Intelligence, and Power BI. Earning this certification demonstrates expertise in both data engineering and analytics within the Fabric ecosystem.

What are the Job Roles after DP-800 Certification?

✅ Fabric Analytics Engineer
✅ Microsoft Fabric Data Engineer
✅ Azure Data & Analytics Consultant
✅ Fabric BI Developer
✅ Cloud Data Engineer (Microsoft Stack)
✅ Data Platform Engineer (Fabric + SQL)

DP-800 certified professionals are in high demand across MNCs, product companies, and cloud service providers hiring on the Microsoft Fabric stack.

What does the DP-800 Training at SQL School cover?

👉 Module 1: MSSQL & TSQL Queries
👉 Module 2: TSQL Programming
👉 Module 3: TSQL Tuning
👉 Module 4: Azure SQL Development
👉 Module 5: Azure Functions with TSQL
👉 Module 6: Fabric SQL (TSQL) — Lakehouse, Warehouse, Spark, Security
👉 Module 7: CoPilot, GitHub & AI Integration
👉 Module 8: DP-800 Exam Guidance, Sample & Mock Tests

Every module is 100% practical, step-by-step, and mapped to real-world use cases.

Who can join the DP-800 Training?

This course is suitable for:

Freshers looking to build a career in Microsoft Fabric & Cloud Analytics
SQL Developers / DBAs upgrading to Fabric and Azure
Data Engineers working on Azure who want to add Fabric expertise
BI Developers expanding into data engineering with Fabric
IT Professionals targeting Microsoft certification in analytics

What training modes are available for DP-800?

Option 1: LIVE Online Training — Instructor-led, fully interactive, step-by-step with assignments after every session.

Option 2: Self-Paced Videos — Pre-recorded, 100% practical sessions you can watch at your own pace with concept-wise assignments.

Both options follow the same curriculum. The trainer is available for doubt clarification, assignment reviews, and exam guidance in both modes.

How does SQL School prepare me for the DP-800 Exam?

SQL School provides dedicated DP-800 Exam Guidance as a separate module covering:

DP-800 Exam Strategy & Topic Weightage
DP-800 Sample Questions walkthrough
DP-800 Mock Tests with detailed explanations
Concept-wise practice tasks mapped to exam objectives
Real-time scenario-based Q&A sessions

This ensures you are exam-ready alongside being job-ready.

Why should I choose SQL School for DP-800 Training?

Every session is practical, step-by-step with concept-wise FAQs
100% results with consistent on-time practice and daily tasks
Trainer with 20+ years of real-world SQL & Azure expertise
Concept-wise task submissions reviewed before next class
Placement support with top MNC partners including Accenture, TCS, HCL, Tech Mahindra, and more
Both LIVE Online and Self-Paced options to suit working professionals and freshers