Free Demo on #Microsoft #SQLServer & #T-SQL with #Azure from SQL School

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Complete Practical; Real-time Job Oriented Training
Azure Data Engineer
PLAN A PLAN B PLAN C
Applicable For (Resume Plan) Azure Data Engineer SQL & T-SQL Queries
Azure Data Engineer
SQL & T-SQL Queries
Azure Data Engineer
Power BI
ADF : Azure Data Factory ✓ ✓ ✓
ADF : Data Imports, ETL ✓ ✓ ✓
ADF : Data Flows, Wrangling ✓ ✓ ✓
ADF : Transformations, ETL ✓ ✓ ✓
Synapse: Configuration, Loads ✓ ✓ ✓
Synapse: ETL with ADF, DWH ✓ ✓ ✓
Synapse: MPP, DWH, Tuning ✓ ✓ ✓
Storage: ADLS Gen 2, BLOB ✓ ✓ ✓
Storage: Az Tables, Shares, ACL ✓ ✓ ✓
Azure Stream Analytics & Jobs ✓ ✓ ✓
IoT Hubs and Event Hubs, ETL ✓ ✓ ✓
ADB : Azure Data Bricks ✓ ✓ ✓
ADB : Architecture, Data Loads ✓ ✓ ✓
ADB : Run Spark Jobs, Pools ✓ ✓ ✓
ADB : Workspace, Delta Tables ✓ ✓ ✓
TSQL: Database Basics, T-SQL X ✓ ✓
TSQL : Constraints, Joins, Queries X ✓ ✓
TSQL: Views, Group By, Self Joins X ✓ ✓
Power BI: Report Design, Visuals X X ✓
Power BI: M Lang, DAX for ETL X X ✓
Power BI: Cloud, Apps, Tenant X X ✓
Power BI: Report Server, Project X X ✓
DP 203, DA 100 Exams Guidance X X ✓
Total Duration 6 Weeks 8 Weeks 12 Weeks
Trainer : Mr. Sai Phanindra T [17+ Yrs of Real-time Exp]. Profile @ linkedin.com/in/saiphanindra

Training Module Duration Plan A Plan B Plan C
Module 1 Azure Data Engineer (DP 203)
[Azure Funda, Azure Migrations, ADF,
Synapse DWH, ADLS Storage, Spark SQL,
Databricks, ASA, IoT, Real-time Project]
6 W   
Module 2 SQL Basics, T-SQL Queries 2 W X  
Module 3
Power BI & Big Data Analytics (DA 100)
[Power BI Cloud Service, Report Server,
REST API, Dashboards, Power Query,
DAX, Real-time Project, Resume Guide]
4 W X X 
Total Duration 6 W 8 W 12 W
Module 1: Azure Data Factory [ADF], Synapse
Applicable for All Plans
Chapter 1: Cloud Introduction & Azure Basics
Azure Implementation: IaaS, PaaS, SaaS, Benefits of Azure Cloud Environment, Azure Data Engineer: Job
Roles, Azure Storage Components, Azure ETL & Streaming Components, Need for Azure Data Factory
(ADF), Need for Azure Synapse Analytics, Azure Resources and Resource Types, Resource Groups in Azure
Portal, Azure SQL Server [Logical Server], Firewall Rules and Azure Services, Connections with SSMS &
ADS Tools, DB Migration: OnPremise to Azure, Schema Migration & Data Migration;
Chapter 2: Synapse SQL Pools
Dedicated SQL Pools in Azure; Enterprise Data Warehouse with Synapse; DWU: Data Warehouse Units,
Resources; Massively Parallel Processing (MPP); Control Nodes and Compute Nodes; SQL Pool Access
from SSMS Tool; T-SQL Queries @ SQL Pools; Start/Resume/Pause, Scaling Options; Creating Tables in
Azure SQL Pool; Compression, MAX DOP & Indexes; Distributions: Round Robin, Hash; Distributions:
Replicate and Usage; Data Imports; Dynamic Views with PDW; Data Loads Monitoring, Resource Class;
Chapter 3: Azure Data Factory Concepts
Azure Data Factory (ADF) Concepts; Hybrid Data Integration at Scale; ADF Pipeline Components & Usage;
Configure ADF Resource in Azure; Understanding ADF Portal and IR; Linked Services and Connections;
Datasets and Tables / Files for ETL; ADF Pipelines: Design, Publish & Trigger; ADF Pipeline with Copy Data
Tool; Creating Azure Storage Account; Storage Container, BLOB File Uploads; Data Loads with Azure BLOB
Files; DIU Allocations & Concurrency; Linked Services, Datasets; Pipeline Trigger, Author and Monitor;
Chapter 4: ADF Pipelines & Polybase
Copy Data Tool For ETL Operations; Azure SQL DB to Synapse Data Loads; Working with Multi Tables Data
Loads; Query Options for Source Datasets; Transformations with Copy Data Tool; Rename, Rearrange &
Remove Options; Pipeline Execution: DTU & DOCP; ADF Pipeline Monitoring Options; ADF Pipelines:
Execution Settings; ADF Logging Options & Storage Account; Compression Option, DOP and DOCP; ETL
Staging & Performance; Staging with Storage Account, Container; ADF Pipeline Monitoring; Polybase;
Chapter 5: OnPremise Data Loads with ADF
On-Premise Data Sources with Azure; Self Hosted Integration Runtime (IR); Access Keys, Remote Linked

Services; Synapse SQL Pool (DW) with OnPremise; Staged Data Copy and Performance; Pipeline
Executions and Monitoring; Pipeline RunIDs and Audits / Tracing; Incompatible Rows Skips, Fault
Tolerance; Incremental Loads with Files (BLOB); Pipeline Executions and Schedules; Regular Schedules
and Tumbling Window; Execution Retry and Delay Options; Binary Copy, Last Modified Date in Blob;
Automated Loops and Trigger Schedules; Incremental Loads Verification Tests;
Chapter 6: ADF Data Flow - 1
Limitations with Copy Data Tool; Data Flow Task, Data Flow Activity; Transformations with Data Flow;
Spark Cluster For Debugging; Cluster Node Configurations; Data Preview Options with DFT; SELECT
Transformation & Options; JOIN Transformation and Usage; Conditional Split Transformation; Aggregate
& Group By Transformations; Synapse Sink Options with DFT; DFT Optimization Techniques; Pipeline
Debug Runs and ETL Testing; Spark Cluster For Pipeline Executions; Pipeline Monitoring & Run IDs;
Chapter 7: ADF Data Flow - 2
ADF Pipelines For ETL Operations; Data Flow Tasks and Activities in Synapse; Pivot Transformation For
Normalization; Generating Pivot Column, Aggregations; Pivot Transformation and Pivot Settings; Pivot
Key Selection, Value and Nulls; Pivoted Columns and Column Pattern; Column Prefix, Help Graphic &
Metadata; Window Functions & Usage in Data Flow; Rank / DenseRank / Row Number; Over Clause and
Input Options; Derived Column Transformations; Exists & Lookup Transformations; Reusing Data Flow
Tasks in Synapse; Pipeline Validations & Executions;
Chapter 8: Azure Synapse Analytics
Azure Synapse Analytics Resource; Azure Synapse Analytics Workspace; Managed Resource Group, SQL
Account; SQL Admin Account and its Purpose; Operations with Synapse Workspace; ADLS Gen 2 Storage
Account, Container; Synapse Studio (Synapse Portal); Dedicated SQL Pools & Spark Pools; Creating
Dedicated SQL Pools; Synapse Tables, Data Loads with T-SQL; COPY INTO Statements with T-SQL;
Clustered Column Store Indexes; Compressions; Aggregation with Data Loads in Azure Synapse;
Chapter 9: Synapse Analytics with Spark
Apache Spark Pool in Azure Synapse; Spark Cluster Nodes: Vcores, Memory; Creating Spark Clusters @
Synapse Studio; Python Notebooks For Remote Access; Creating Databases in Apache Spark Pool; Data
Loads from Dedicated SQL Pools; Table Creations, Aggregation Operations; PySpark Code for Data
Operations, Writes; Serverless Pool in Azure Synapse; Connections, Usage with Serverless Pool; Using
Azure OpenDatasets in Synapse; OPENROWSET and BULK Data Loads; Azure Storage Account : Data
Analysis; Working with Parquet Files in Synapse; Python Notebooks (Pyspark) in Synapse;
Chapter 10: Incremental Loads @ Synapse
Incremental Loads with Synapse Studio; Multi Table Merge Operations; On-Premise Data Sources &
Timestamps; Azure SQL DB Destinations, Watermarks; Watermark Table Usage & Audits; Stored
Procedures for Timestamp Updates; Table Data Type and Dynamic MERGE; SQL Queries for Datasets and
Fetch; Lookup Activity and its Usage un Synapse; Expressions in ADF Portal for Lookup; Expressions in
ADF Portal for Source; Output Pipeline Expression, Data Window; Concat Function, Run IDs Expressions;
JSON Parameters, Pipeline Scheduling; Pipeline Validation, Trigger and Monitoring;
Chapter 11: Optimizations, Power Query
ADF ETL with GUI : Power Query; Power Query Resource Creation, Use; Source Data Configurations &
Settings; Rename, Remove, Pivot, Group By, Order; Index, Filter, Remove Error Rows; Using Power Query
Activity, ADF Pipelines; Spark Cluster Configurations for Pipelines; Concurrency, Big Data

Recommendations; Storage Optimization Techniques; ETL Optimization Techniques; SQL Pool (Synapse)
Optimizations; Indexes, Partitions, Distributions, DOP; Pipeline Optimization Techniques; Partitions,
DOCP, Compressions, DIU; Staging, Polybase and Core Counts;
Chapter 12: Pipeline Monitoring, Security
Azure Monitor Resource and Usage; Pipeline Monitoring Techniques; ADF: Pipeline Monitoring and
Alerts; Synapse: Pipeline Monitoring and Alerts; Synapse: Storage Monitoring and Alerts; Conditions,
Signal Rules and Metrics; Email Notifications with Azure; Concurrency, Big Data Recommendations; Azure
Active Directory (AAD) Users, Groups; IAM: Identity & Access Management; Synapse Workspace Security
with RBAC; ADF Security with RBAC: Owner, Contributor; Azure Synapse SQL Pool Security: Logins; Users,
Roles and Resource Classes (RC); Assigning RCs to Users. Object Level Security;
Azure Storage & Stream Analytics
Chapter 1: Azure Storage & Containers
Storage Components in Microsoft Azure; Azure Storage Services and Types - Uses; High Availability,
Durability & Scalability; Blob: Binary Large Object Storage; General Purpose: Gen 1 & Gen 2 Versions;
Blobs, File Share, Queues and Tables; Data Lake Gen 2 Operations with Azure; Azure Storage Account
Creation; Azure Storage Container: Usage; Azure Data Explorer: Operations; File Uploads, Edits and
Access URLs; Azure Storage Explorer Tool Usage; Azure Account Options in Explorer; Directory Creation,
File Operations; End User Access Options With Files; Data Explorer Vs Storage Explorer Tool;
Chapter 2: Azure Migrations, BLOB Imports
SQL Server (On-Premise) to Azure Migration; Source Database Scripts & Validations; BACPAC File
Generation From SSMS Tool; Azure Data Lake Storage and SSMS Access; Azure Storage Container,
BACPAC Files; Azure SQL Server Creation From Portal; Azure SQL DB Imports, Storage SAS Keys; Azure
SQL Database Migrations, Verification; BLOB Data Access from On-Premise; Data Imports From Excel and
CSV Files; BLOB Data Imports using T-SQL Queries; SAS - Shared Access Signature Generation; CSV File -
Uploads, Downloads, Edits, Keys; Master Keys, Credentials, External Sources; BULK INSERT Statement and
Data Imports; T-SQL Imports : Practical Limitations;
Chapter 3: Azure Tables, Shares
Azure Tables - Real-time Usage; Schema-less Design and Access Options; Structured and Relational Data
Storage; Tables, Entities and Properties Concepts; Azure Tables: Creation and Data Inserts; Azure Tables
in Portal - GUI and Data Types; Azure Tables: Data Imports in Explorer; Data Edits, Queries & Delete
Operations; Azure Files - SMB Protocol, Creation, Usage; Shared Access, Fully Managed & Resiliency;
Performance, Size Requirements for Shares; Azure Storage Explorer Tool for File Shares; Azure Queues:
Message Queues, Limitations; Adding Messages, Queuing and De-Queuing; Data Access & Clear Queue
from Explorer; End Points for Azure Message Queues;
Chapter 4: Azure Storage Security, Admin
Azure Data Lake Storage Security Options; Shared Access Keys - Primary, Secondary Keys; SAS Key
Generation: Container, Tables, Files; SAS Key Permissions, Validation Options; Access Keys: Account
Level Permissions; Azure Active Directory (AAD): Users, Groups; Azure AD Security: RBAC with IAM, ACLs;
Owner Role, Contributor and Reader Role; Azure Admin Operations: Replication Options; Azure Regions

and Azure Zones, Availability; Locally & Geo Redundant Storage: LRS, GRS; Read Access (RA-GRS) & Geo
Zone (GZRS); Classic Deployment Model, Encryption at REST; CORS Support (Cross Origin Resource
Sharing); Auditing Access and Network Access Rules; Firewalls and Advanced Threat Protection;
Chapter 5: Azure Monitoring, Power BI
Azure Monitor, Metrics & Logs; Monitoring Azure Storage Namespaces; Add KQL Metrics; Account, Blob
and File; Total Ingress and Egress Metrics: Charts; Average Latency, Transaction Count; Request
Breakdowns, Signal Logic Options; Azure Alerts and Conditions, Notifications; Signal Logic Conditions and
Emails; Power BI Desktop Tool Installation; Binary Data and Record Data Access; Azure Data Lake Storage:
Access Keys; Azure Data Lake Storage with Power BI; BLOB File Access with Power BI; Azure Tables
Creation and File Imports; Azure Table Access with Power BI;
Chapter 6: Azure Stream Analytics, IoT
Azure Steam Analytics: Real-time Usage; Real-time Data Processing, Event Tracking; Ingest, Deliver and
Analysis Operations; Azure Stream Analytics Jobs Concept; Understanding Input & Output Options; SAQL
Queries for Stream Analytics Jobs; IoT: Internet Of Things For Real-time Data; Need for IoT Hubs and
Event Hubs; Creating IoT Device for Data Inputs; Creating Azure Stream Analytics Resource; Stream
Analytics Jobs for Historical Data; Azure SQL Database Options for ASA Jobs; SAQL: Query Formatting and
Validation; Historical Data Uploads, ASA Job Execution; Stream Analytics Job Monitoring Options;
Chapter 7: IoT Hubs & Event Hubs
Azure Stream Analytics For API Data; IoT Hubs & IoT Devices, Connection Strings; Raspberry APP
Connections with IoT Hub; Azure Storage Account and Container; Creating Azure Stream Analytics Job;
Configuring Input Aliases with IoT Hub; Configuring Output Alias with ADLS Gen 2; SAQL Query and Job
Executions; Monitoring; Azure Event Hubs and Event Instances; Event Hub Namespaces, Partition Counts;
Access Policies, Permissions & Defaults; RootManageSharedAccessKey & Options; Connection Strings &
Event Service Bus; Telco App Installation, Executions. LIVE Data; On-Premise Integration with ASA Jobs;
Chapter 8: Azure Stream Analytics Security
Securing Azure Stream Analytics Resource; RBAC: Role Based Access Control & IAM; Owner, Contributor,
Reader, Resource Owner; Network Level and IP Address Security; Virtual Machine and Virtual Network
Options; Port Level Configuration and Stream Apps; Data Feed Security for Event Hub, IoT Hub; Azure
Virtual Machine (VM) Security Options; Azure Key Vaults & ADLS [Data Lake] Security; Azure Passwords,
Keys and Certificates; Azure Key Vaults - Name and Vault URI; Inbuilt Managed Key and Azure Key Vault;
Standard Type, Premium Type Azure Key Vaults; Secret Page, Key Backups and Key Restores; Adding Keys
to Azure Vaults. Key Type, Size;
Azure Databricks & SparkSQL
Chapter 1: Azure Intro, Azure Databricks
Cloud Introduction and Azure Basics For Databricks; IaaS, PaaS, SaaS; Benefits of Azure Cloud
Environment; Storage, ETL and Streaming Components; Need for Azure Databricks (ADB); ETL and Data
Storage Components; Databricks File System (DBFS) and Usage; Azure Databricks Service Creation; Azure
Databricks Workspace Operations; Spark Cluster Configurations & Capacity; Driver Nodes and Worker
Nodes in Spark; Master Node & Cluster Creation Process; Databricks Runtime Service & DBUs; File

Uploads into DBFS; Table Creations; Promoting Headers, Data Type Changes; DBFS Storage Navigations;
Chapter 2: SQL Notebooks & Python
Notebooks: Concept, Usage Options; Creating SQL Notebooks in Databricks; Using DBFS Tables in SQL
Notebooks; Data Access and Analytics Options; SparkSQL Queries: SELECT, GROUP BY; SparkSQL
Queries: Aggregates, Conditions; Notebook Operations: Download, Clone; Notebook Operations:
Upload, Reuse; SQL Notebooks with Python Code; Using DBFS Sample Data Sources (CSV); Dataframes:
Creation and Real-time Use; Pandas Dataframe, Virtual Table Creation; Dataframe Data Access, Caching
Options; Take() and Display() Functions in PySpark; Temporary View Creation and Access; SparkSQL
Queries, Analytics, Chart Reports;
Chapter 3: Python Notebooks
Azure SQL Server Configurations; Azure SQL Database Creation; Azure Firewall Rules and IP Address;
Allow Azure Services, Remote Access; Connection Tests with SSMS Tool; Python Notebooks with Azure
Databricks; Data Imports and Table Creations (Code); Parquet Files and Usage in Databricks; Using
Dataframes for Data Operations; SparkSQL Queries with SELECT, TOP; Establishing Connections to Azure
SQL DB; JDBC Connection Strings, DataframeWriter; JDBC Properties, Port Settings & Options; Data
Extraction, SQLContext & Dataframes; Pandas Data Frame for Big Data Analytics; JDBC URL Options &
PySparkSQL Modules;
Chapter 4: Scala Notebooks, Transformations
Scala Notebooks with Azure Databricks; Azure SQL Database Connections with Scala; Util Properties,
Connection Settings For Driver; Connection Settings for Worker Node @ Spark; Dataframe Creation and
Data Access in Scala; Display Options and Data Transformations; Data Loads to Azure SQL Database
Tables; Data Reads from Azure SQL DB & Analytics; Databricks Jobs : Creation Options, Usage; Job Limits,
Workspace & Concurrency Limits; Notebooks with and without Parameters; Jobs with Default
Parameters, Executions; Interactive, Automated Clusters for ADB Jobs; Job Schedules and Manual
Executions; Active Jobs, Recently Run Jobs & Monitoring; Job Execution Reports & Workspace Options;
Chapter 5: ADB with Virtual Network
Azure Virtual Network Configuration; Azure VNets, Address Spaces & Range; Subnet and Subnet Address
Range; Azure Databricks Deployments with VN; CIDR Range and IP Addresses; Public Subnet and Private
Subnet; Spark Cluster Creation with ADB; End User Access using Virtual Network; Spark Cluster
Notebook Operations; Notebook Exports, Imports, ReUse; SparK Cluster Configuration Changes; Power
BI Connections, JDBC, User Token;Notebook Scheduling and Jobs; Interactive Clusters and Real-time
Use; All Purpose Clusters and Advantages;
Chapter 6: DeltaLakes & ADF Integration
Azure Delta Lake Implementation; ACID Properties and Upsert Advantages; Delta Engine Optimizations
& Uses; Pipeline Creation with JSON Files in DBFS; Delta Tables Creation, Data Loads; Spark Cluster
Settings: Auto Optimize; Auto Compact and Delta Table Optimize; Delta Locations; Data Retrieval,
Versions; Azure Databricks Integrations with ADF; Defining Scala Notebooks in ADB; Using Notebooks in
Azure Data Factory; spark.conf.set & fs.azure.account.key; spark.read.format, Option() and Head();
dbutils() with wasbs & BLOB Data Sources; ADF Pipelines and Trigger Schedules;
Chapter 7: Databricks Integrations
Azure Databricks with Data Lake Storage; Handling Unstructured Data in Azure; Data Preparation and
Staging Operations; Azure App (Service Principal) Registration; Azure Key Vault Creation & Key Usage;
Service Principal Permissions @ Data Loads; Tenants and Authorization Settings; Client Credentials,

Token Provider Options; Azure Databricks Clusters, Spark Notebooks; Dynamic Connections and Blob
Access; Data Preparation & Big Data Ingestion; Data Extraction and ADLS Storage; show(),
transformations, wasbs; Azure SQL Server & Synapse; Incremental Changes & Data Loads;
Real-time Project (End to End)
Online Retail Database Data Source; Azure Migrations and ETL Concepts; Azure SQL Pool (Synapse
DWH) Tables; Apache Spark Pool : Databases, Tables; Azure Data Lake Storage (ADLS Gen 2); Azure
Stream Analytics Jobs with IoT; Azure Data Bricks and DBFS, Notebooks; Big Data Analytics & Power BI
Reports;
Project Requirement; Project Solution; Project FAQs; Concept wise FAQs; Resume Guidance; Mock
Interviews; DP 203 Certification Guidance;
Module 2: Database Basics, SQL, T-SQL Queries
Applicable for Azure Data Engineer Plans B, C
Chapter 1: SQL SERVER INTRODUCTION
Data, Databases and RDBMS Software; Database Types : OLTP, DWH, OLAP; Microsoft SQL
Server Advantages, Use; Versions and Editions of SQL Server; SQL : Purpose, Real-time Usage
Options; SQL Versus Microsoft T-SQL [MSSQL]; Microsoft SQL Server - Career Options; Database
Engine Component and OLTP; BI Components, Data Science Components; ETL, MSBI and Power
BI Components; Course Plan, Resume, Project; 24 x 7 Lab; Software Installation Pre-Requisites;
Chapter 2: SQL SERVER INSTALLATIONS
System Configuration Checker Tool; Versions and Editions of SQL Server; SQL Server Pre-
requisites : S/W, H/W; SQL Server 2016 / 2017 Installation; SQL Server 2019 Installation;
Instance Name; Instances : Types; Default Instance, Named Instances; Port Numbers; Service
and Service Account; Authentication Modes and Logins; FileStream, Collation Properties;
Chapter 3: SSMS Tool, SQL BASICS - 1
SQL Server Management Studio; Local and Remote Connections; System Databases: Master and
Model; MSDB, TempDB, Resource Databases; Creating Databases : Files [MDF, LDF]; Creating
Tables in GUI; Data Insertion & Storage; SQL : Real-time Usage; DDL, DML, SELECT, DCL and TCL
Statements; Data Storage, Inserts - Basic Level; SELECT; Table Data Retrieval;
Chapter 4: SQL BASICS - 2
Creating Databases & Tables in SSMS; Single Row Inserts, Multi Row Inserts; Rules for Data
Insertion Statements; SELECT Statement @ Data Retrieval; SELECT with WHERE Conditions;
AND and OR; IN and NOT IN; Between, Not Between; LIKE and NOT LIKE; UPDATE Statement;
DELETE & TRUNCATE; Logged and Non-Logged Operations; ADD, ALTER and DROP Statements;
Chapter 5: SQL BASICS - 3, T-SQL Introduction
Schemas : Group Tables in Database; Using Schemas for Table Creation; Using Schemas in Table

Relations; Table Migrations across Schemas; Default Schema : "dbo"; Import and Export Wizard;
Bulk Operations; Excel File Imports / Exports; SQL Server Native Client; Executing SSIS Packages,
Data Loads; Local and Global Temporary Tables; # & ## Prefix; Temporary Vs Permanent Tables;
Chapter 6: CONSTRAINTS & INDEXES BASICS
Constraints and Keys - Data Integrity; NULL, NOT NULL Property on Tables; UNIQUE KEY
Constraint; PRIMARY KEY Constraint; FOREIGN KEY Constraint, References; CHECK Constraint;
DEFAULT Constraint; Identity Property : Seed & Increment; Database Diagrams and ER Models;
Relationships Verification and Links; Indexes : Basic Types and Creation; Index Sort Options,
Search Advantages; Clustered and Non Clustered Indexes; Primary Key and Unique Key Indexes;
REAL-TIME CASE STUDY - 1 (SALES & RETAIL)
Chapter 7: JOINS and TSQL Queries : Level 1
JOINS - Table Comparisons; INNER JOINS For Matching Data; OUTER JOINS For (non) Match
Data; Left Outer Joins; Right Outer Joins - Example Queries; FULL Outer Joins; One-way and Two
Way Comparisons; "ON" Conditions; Join Unrelated Tables; NULL, IS NULL in Joins; CROSS JOIN
and CROSS APPLY; Join Options: Merge, Loop and Hash Joins; Performance Advantages;
Chapter 8: GROUP BY, T-SQL Queries : Level 2
GROUP BY Queries and Aggregations; Group By Queries with Having Clause; Group By Queries
with Where Clause; Using WHERE and HAVING in T-SQL; Rollup : Usage and T-SQL Queries;
Cube : Usage and T-SQL Queries; UNION and UNION ALL Operator; EXISTS Operator, Query
Conditions; Sub Queries; Joins with Group By Queries; Nested Sub Queries; UNION and UNION
ALL; Nested Sub Queries with Group By, Joins; Comparing WHERE, HAVING Conditions;
Chapter 9: JOINS & T-SQL Queries : Level 3
GetDate, Year, Month, Day Functions; Date & Time Styles, Data Formatting; DateAdd and
DateDiff Functions; Cast and, Convert Functions in Queries; String Functions: SubString,
Relicate; Len, Upper, Lower, Left and Right; LTrim, RTrim, CharIndex Functions; MERGE
Statement - Comparing Tables; WHEN MATCHED and NOT MATCHED; Incremental Load with
MERGE Statement; IIF() Function for Value Compares; CASE Statement : WHEN, ELSE, END;
ROW_NUMBER() and RANK() Queries; Dense Rank and Partition By Queries;
Chapter 10: View, Procedure, Function Basics
Views : Types, Usage in Real-time; System Predefined Views and Audits; Listing Databases,
Tables, Schemas; Functions : Types, Usage in Real-time; Scalar, Inline and Multi-Line Functions;
System Predefined Functions, Audits; DBId, DBName, ObjectID, ObjectName; Variables &
Parameters; User & System Predefined Procedures; Parameters; Sp_help, Sp_helpdb and
sp_helptext; sp_pkeys, sp_rename and sp_help; When to use Which Database Objects;
Chapter 11: Triggers & Transactions
Triggers - Purpose, Real-world Usage; FOR/AFTER Triggers; INSTEAD OF Triggers; INSERTED,
DELETED Memory Tables; DML Automations using Memory Tables; Read Only Tables using DML
Triggers; Enable Triggers and Disable Triggers; Database Level, Server Level Triggers;
Transactions & ACID Properties; Auto Commit; EXPLICIT & IMPLICIT; COMMIT and ROLLBACK; Open
Transaction; Query Blocking Scenarios @ Real-time; NOLOCK and READPAST Lock Hints;

Chapter 12: ER MODELS, NORMAL FORMS
Normal Forms for Entity Relationships; First, Second, Third Normal Forms Usage; Boycee-Codd Normal
Form: BNCF : Usage; 4 NF, EKNF, ETNF. Functional Dependency; Multi-Valued, Transitive Dependencies;
Composite Keys and Composite Indexes; 1:1, 1:M, M:1, M:M Relationship Types; SQL Queries Access in
Reporting Tools; Storing SQL Queries into Views; Creating Office Data Connection Files; Excel Pivot
Reports and Reports; SQL Queries (Auto Generated) in BI Tools; FETCH OFFSET, NEXT ROWS; Data
Refresh (Manual, Automated);
REAL-TIME CASE STUDY - 2 (Sales & Retail), EXCEL INTEGRATION
Module 3: Power BI (Reports, Cloud, Server, Analytics)
Applicable for Azure Data Engineer Plan C
Chapter 1 : POWER BI BASICS
Power BI Job Roles in Real-time; Power BI Data Analyst Job Roles; Business Analyst - Job Roles; Power BI
Developer - Job Roles; Power BI for Data Scientists Comparing MSBI and Power BI; Comparing Tableau
and Power BI; DA 100 Exam Guidance; Types of Reports in Real-World; Interactive & Paginated Reports;
Analytical & Mobile Reports; Data Sources Types in Power BI; Licensing Plans; Power BI Training : Lab
Plan; Power BI Dev, Prod Environments;
Chapter 2 : BASIC REPORT DESIGN
Power BI Desktop Installation; Data Sources & Visual Types; Canvas, Visualizations and Fields; Get Data
and Memory Tables; In-Memory xvelocity Database; Table and Tree Map Visuals; Format Button and
Data Labels; Legend, Category and Grid; PBIX and PBIT File Formats; Visual Interaction, Data Points;
Disabling Visual Interactions; Edit Interactions - Format Options; SPOTLIGHT & FOCUSMODE; CSV and
PDF Exports. Tooltips; Power BI EcoSystem, Architecture;
Chapter 3 : VISUAL SYNC, GROUPING
Slicer Visual : Real-time Usage; Orientation, Selection Properties; Single & Multi Select, CTRL Options;
Slicer : Number, Text and Date Data; Slicer List and Slicer Dropdowns; Visual Sync Limitations; Disabling
Slicers; Grouping : Real-time Use, Examples; List Grouping and Binning Options; Grouping Static / Fixed
Data Values; Grouping Dynamic / Changing Data; Bin Size and Bin Limits (Max, Min); Bin Count and
Grouping Options; Grouping Binned Data, Classification;
Chapter 4 : HIERARCHIES, FILTERS
Creating Hierarchies in Power BI; Independent Drill-Down Options; Dependant Drill-Down Options;
Conditional Drilldowns, Data Points; Drill Up Buttons and Operations; Expand & Show Next Level
Options; Dynamic Data Drills Limitations; Show Data and See Records; Filters : Types and Usage in Real-
time; Visual Filter, Page Filter, Report Filter; Basic, Advanced and TOP N Filters; Category and Summary
Level Filters; DrillThru Filters, Drill Thru Reports; Keep All Filters" Options in DrillThru; CrossReport
Filters, Include, Exclude;
Chapter 5 : BOOKMARKS, AZURE, MODELING
Drill-thru Filters, Page Navigations; Bookmarks : Real-time Usage; Bookmarks for Visual Filters;
Bookmarks for Page Navigations; Selection Pane with Bookmarks; Buttons, Images with Actions;
Buttons, Actions and Text URLs; Bookmarks View & Selection Pane; OLTP Databases, Big Data Sources;
Azure Database Access, Reports; Import &Direct Query with Power BI; Enter Data; Data Modeling :

Currency, Relations; Summary, Format, Synonyms; Web & Mobile View in PBI;
Chapter 6 : VISUALIZATION PROPERTIES
Stacked Charts and Clustered Charts; Line Charts, Area Charts, Bar Charts; 100% Stacked Bar and Column
Charts; Map Visuals: Tree, Filled, Bubble; Cards, Funnel, Table, Matrix; Scatter Chart : Play Axis, Labels;
Series Clusters; Waterfall Chart; ArcGIS Maps; Infographics; Color Saturation, Sentiment Colors; Column
Series, Column Axis in Lines; Join Types : Round, Bevel, Miter; Shapes, Markers, Axis, Plot Area; Data
Colors; Series, Custom Series and Legends;
Chapter 7 : POWER QUERY LEVEL 1
Power Query Architecture and M Language; Data Types, Literals and Values; Power Query
Transformation Types; Table & Column; Text & Number Transformations; Date, Time and Structured
Data; List, Record & Table; let, source, in statements @ M Lang; Power Query Functions, Parameters;
Invoke Functions; Get Data, Table Creations, Edit; Merge and Append Transformations; Join Kinds,
Advanced Editor, Apply; ETL Operations with Power Query;
Query Duplicate, Query Reference; Group By and Advanced Options; Aggregations with Power Query;
Transpose, Header Row Promotion; Reverse Rows and Row Count; Data Type Changes & Detection;
Replace Columns: Text, NonText; Replace Nulls: Fill Up, Fill Down; PIVOT, UNPIVOT; Move Column and
Split Column; Extract, Format; Date & Time Transformations; Deriving Year, Quarter, Month, Chapter;
Add Column : Query Expressions; Query Step Inserts and Step Edits;
Creating Parameters in Power Query; Parameter Data Types, Default Lists; Static/Dynamic Lists For
Parameters; Removing Columns and Duplicates; Convert Tables to List Queries; Linking Parameters to
Queries; Parameters and PBI Canvas; Multi-Valued Parameter Lists; Creating Lists in Power Query;
Converting Lists to Table Data; Advanced Edits and Parameters; Data Type Conversions, Expressions;
Columns From Examples, Indexes; Conditional Columns, Expressions;
Chapter 10 : DAX Functions - Level 1
DAX : Importance in Real-time; Real-world usage of Excel, DAX; DAX Architecture, Entity Sets; DAX Data
Types, Syntax Rules; DAX Measures and Calculations; ROW Context and Filter Context; DAX Operators,
Special Characters; DAX Functions, Types in Real-time; Vertipaq Engine, DAX Cheat Sheet; Creating,
Using Measures with DAX; Creating, Columns with DAX; Quick Measures; SUM, AVERAGEX, KEEPFILTERS;
Dynamic Expressions, IF in DAX;
Chapter 11 : DAX Functions - Level 2
Data Modeling Options in DAX; Detecting Relations for DAX; Using Calculated Columns in DAX; Using
Aggregated Measures in DAX; Working with Facts & Measures; Modeling : Missing Relations; Modeling :
Relation Management; CALCULATE Function Conditions; CALCULATE & ALL Member Scope; RELATED &
COUNTROWS in DAX; Slicing; Dynamic Expressions, RETURN; Date, Time, Text Functions; Logical,
Mathematical Functions; Running Total, EARLIER Function;
Chapter 12 : DAX FUNCTIONS - Level 3
1:1, 1:M and M:1 Relations; Connection with CSV, MS Access; AVERAGEX and AVERAGE in DAX;
KEEPFILTERS and CALCUALTE; COUNTROWS, RELATED, DIVIDE; PARALLELPERIOD, DATEDADD;
CALCULATE & PREVIOUSMONTH; USERELATIONSHIP, DAX Variables; TOTALYTD , TOTALQTD; DIVIDE,

CALCULATE, Conditions; IF..ELSE..THEN Statement; SELECTEDVALUE, FORMAT; SUM, DATEDIFF
Examples; TOCHAPTER, DATE, CHAPTER with DAX; Time Intelligence Functions;
Chapter 13 : POWER BI CLOUD - 1
Power BI Service Architecture; Power BI Cloud Components, Use; App Workspaces, Report Publish
Related Datasets Cloud; Creating New Reports in Cloud; Report Publish and Report Uploads; Dashboards
Creation and Usage; Adding Tiles to Dashboards; Pining Visuals and Report Pages; Visual Pin Actions in
Dashboards; LIVE Interaction in Dashboard; Adding Images, Custom Links; Videos & Embed Links; API
Data Sources; Streaming Dataset Tiles (REST API);
Chapter 14 : POWER BI CLOUD - 2
Dashboards Actions, Report Actions; DataSet Actions: Create Report; Share, Metrics and Exports; Mobile
View & Dashboard Themes; Q & A [Cortana], Pin Visuals; Export, Subscribe, Subscribe; Favourite,
Insights, Embed Code; Featured Dashboards and Refresh; Gateways Configuration, PBI Service; Gateway
Types; Gateway Clusters, Data Refresh : Manual, Automatic; PBIEngw Service; DataFlows, Power Query
Expressions; Adding Entities, JSON Files;
Chapter 15 : EXCEL, ROW LEVEL SECURITY
Import and Upload Options in Excel; Excel Workbooks and Dashboards; Datasets in Excel and
Dashboards; Using Excel Analyzer in Power BI; Using Excel Publisher in PBI Cloud; Excel Workbooks, PINS
in Power BI; Excel ODC Connections, Power Pivot; Row Level Security (RLS) with DAX; Need for RLS in
Power BI Cloud; Data Modelling; DAX Roles Creation and Testing; Power BI Users to Roles; Custom
Visualizations; Histogram, Gantt Chart, Info graphics;
Chapter 16: REPORT SERVER, REPORT BUILDER
Need for Report Server in PROD; Install, Configure Report Server; Report Server DB, Temp Database;
Webservice URL, Webportal URL; Creating Hybrid Cloud with Power BI; Using Power BI DesktopRS;
Uploading Interactive Reports; Report Builder; Report Builder For Power BI Cloud; Designing Paginated
Reports (RDL); Deploy to Power BI Report Server; Data Source Connections, Report; Power BI Report
Server to Cloud; Tenant IDs; Mobile Report Publisher;
Chapter 17: AZURE BI INTEGRATIONS WITH POWER BI
Power BI with SQL Server Source; Power BI with Azure SQL Database; Power BI with Azure Data
Warehouse (Synapse); Power BI with Azure Data Lake; Power BI with Azure Databricks; Power BI with
Azure Cosmos DB; Power BI with Azure BLOB Storage; Azure AD Authentication;
Chapter 18: Real-time Project [Sales & Customers]
Resume, Project Oriented FAQs and Solutions
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