Azure BI (Business Intelligence) is Microsoft’s cloud-based solution for end-to-end data analytics and reporting. It leverages tools like Power BI, Azure Synapse Analytics, and Azure Analysis Services for powerful insights. Professionals skilled in Azure BI can pursue roles like BI Developer, Data Analyst, and Cloud BI Consultant.
✅ Azure Synapse Warehousing
✅ Azure Data Factory for ETL/ELT
✅ Azure Analysis Services
✅ Power BI with Semantic Models
✅ Data Lake Storage for Big Data
✅ Azure Stream Analytics, IoT
✅ Security, RBAC & PySpark
✅ Azure Databricks, DLT Tables
✅ CI/CD & DevOps with Azure BI
✅ Real Time Project
Azure BI
Training Course Contents:
Module 1 : Microsoft SQL (TSQL)
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: Azure Data Engineer
Part 1: ADF & Synapse
Ch 1: ETL, DWH Introduction
- Database Introduction
- Data Warehouse (DWH)
- Data Engineering Work Flow
- Cloud Concepts: IaaS, PaaS
- SaaS & Azure Cloud Concepts
- Azure Resources & Groups
- Storage, ETL, IoT Resources
Ch 2: Azure Intro, Azure SQL
- Azure SQL Server, SQL DBA
- Azure SQL Database (OLTP)
- Azure SQL Pool (DWH)
- Connections from SSMS Tool
- Connections from ADS Tool
- Pause / Resume SQL Pool
- Source Data Configurations
Ch 3: Azure Synapse (DWH)
- Synapse Pool Architecture
- Control Node, Compute Node
- DMS & Partitioned Tables
- Creating Tables with TSQL
- Distributions: RR, Hash, Repl
- Big Data Loads with TQL
- Important DMFs & DMVs
Ch 4: Azure Data Factory (ADF)
- Need for ADF & Pipelines
- Linked Services & IRs
- Datasets, Pipelines, Triggers
- Copy Data Activity & CDT
- Data Loads Pipelines, DTUs
- Pipeline Monitoring, Edits
Ch 5: ADF Incremental Loads – 1
- File Incremental Loads
- Storage Account, Data Lake
- Binary Copy, Schema Drift
- Staging Concept in ADF
- DOCP, Logging & Consistency
- Polybase Concept & Tuning
Ch 6: ADF Incremental Loads – 2
- Implement SCD with ADF
- Self-Hosted IR: Realtime Use
- On-premise Data: Incr Loads
- Copy Method: Upsert, Keys
- Staging & ADF Optimizations
- Pipeline Runs, Activity IDs
Ch 7: ADF Data Flow – 1
- Data Flow Transformations
- Spark Clusters for Debugging
- Optimized Clusters, Preview
- Conditional Split, SELECT
- Sort, Union Transformations
- Pipelines with Data Flow
Ch 8: ADF Data Flow – 2
- Working with Multiple Tables
- Join Transform, Broadcast
- Row Filters, Column Filters
- Surrogate Keys, Derived Cols
- ETL Loads Dates, Sink Options
- Aggregated Data Loads
Ch 9: ADF Data Flow – 3
- Pivot Transformation
- Group By & Pivot Keys
- Column Pattern, Deduplicate
- Lookup, Cached Lookup
- Tuning Transformations
- Tuning Data Flow, Spark
Ch 10: Synapse Analytics – 1
- Azure Synapse Analytics
- Dedicated SQL Pools
- TSQL: Stored Procedures
- Synapse Pipelines, Tuning
- SP Activity in Pipelines, Jobs
- Comparing ADF & Synapse
Ch 11: Synapse Analytics – 2
- Serverless Pools in Synapse
- TSQL Scripts with Serverless
- ADLS Data Imports & ELT
- Synapse Aggregation, Analytics
- Synapse Optimizations
- Synapse Security & Logins
Ch 12: Synapse Analytics – 3
- Apache Spark Pool & Usage
- Synapse Analytics with Pools
- PySpark Staging, Aggregations
- Spark Queries & Python ETL
- Python Notebooks, Pipelines
- Integrating Python with DWH
Ch 13: Parameters, SCD & ETL
- ADF Templates in Realtime
- Table Incremental Loads
- Control Tables, Watermarks
- Pipeline Parameters, SPs
- Dynamic Data Sets, SCD
Ch 14: CDC @ ETL, ELT & Tuning
- Using CDC in ADF
- Control Tables (CT): Upserts
- Handling Inserts, Updates
- SCD Type 1 & Type 2
- ADF, Synapse: Limitations
Part 2: Storage, ADLS & IoT
Ch 1: Azure Intro & Storage
- Storage, ETL, IoT Resources
- Azure Storage Components
- Azure Storage Account, HNS
- Azure Data Lake Storage
- Azure Storage Explorer Tool
- Storage Explorer Config
- Storage Account Properties
Ch 2: Azure Storage Operations
- BLOB Storage: Containers
- Storage Browser, Explorer
- File & Folder Uploads, Edits
- Azure Tables: Row Key
- Partition Key, Timestamp
- Use Cases of BLOB Storage
- Use Cases of Azure Tables
Ch 3: Azure Storage Security
- Realtime use of Keys
- Access Keys & Admin Access
- SAS Keys Generation, Ips
- Creating, Using Entra Users
- Azure AD Users, Groups
- IAM & RBAC with Entra Users
- ACLs and ADLS Security
Ch 4: Azure SQL DB Migrations
- On-Premise SQL DB bacpac
- Azure SQL Deployment
- Azure Storage from SSMS
- Azure SQL DB Migration
- Migration Verifications
- Testing Migrations in SQL
Ch 5: Azure Stream Analytics
- Azure IoT Hubs & Devices
- APIs with Connection Strings
- Azure Steam Analytic Jobs
- Inputs, Outputs, SAQL Query
- LIVE Feed: JSON, AVRO Files
- Watermark & LIVE Stats
Ch 6: Azure Key Vaults
- Azure Encryptions @ REST
- SMK & CMK Encryptions
- Azure Key Vaults & Key
- Access Policies
- Automated Encryptions
- Realtime Considerations
Ch 7: Azure Metrics & Alerts
- Azure Encryptions @ REST
- Azure Key Vaults & Keys
- SMK & CMK Encryptions
- Azure Metrics: Ingress
- Egress, E2E Latency Issues
- Performance Tuning Options
Ch 8: Azure Storage Optimization
- BLOB Types & Content Types
- Hot, Cool, Cold, Archive Types
- Creating, Using Access Policies
- Immutable Storage, Rotation
- Containerization, Indexing
- Replication: LRS, ZRS, RA-GRS
Ch 9: Azure Pricing, Functions
- Azure Logic Apps: Usage
- Log Apps Usage in ETL
- Snapshots, Azure Functions
- Azure Functions Realtime Use
- ETL & DWH with Functions
- Azure Resource Pricing
Part 3: Databricks (ETL, DWH)
Ch 1: Databricks Intro
- Azure Introduction
- Azure Account & Subscription
- Open Source ETL : Spark
- Azure Databricks Resource
- Databricks Workspace
- Creating Spark Cluster
Ch 2: Spark Architecture
- Spark Clusters: Types, Policies
- Driver Node: Purpose, Compute
- Worker Node: Purpose, Compute
- Cluster Manager, Executions
- Resilent Distributed Datasets
- DAG: Directed Acyclic Graph
Ch 3: DBFS Operations
- DBFS Concepts: File Store, Tables
- DBFS File Uploads, Infer Schema
- Header Row Promotion
- Create Table using UI
- HIVE Metastore Catalog
- Spark Database & Tables
Ch 4: Notebooks Intro
- ETL & ELT Process
- Workspace Options: Notebooks
- Notebooks: SQL, Python, Scala
- When to use which Notebooks?
- Notebook Exports, Imports
- Cloning and Markdown Cells
Ch 5: Unity Catalog
- Unity Catalog & Big Data Storage
- Unity Catalog Connectors
- Catalog Explorer, HIVE Metastore
- Ubuntu VM : Azure Resource
- Cluster Size & VM Size Options
- Default Spark Database, Usage
Ch 6: Spark SQL Notebooks
- Creating Spark Databases
- Connecting to Spark Databases
- Creating Spark tables
- Data Inserts & DML Operations
- DDL Operations on Spark Tables
- SQL Notebook: Limitations
Ch 7: Python Introduction
- Python Introduction
- Python Usage in ETL, DDL, DML
- Dataframes : Purpose
- Dataframes as Spreadsheets
- Spark Environment for Python
- PySpark: Python inside Spark
Ch 8: Python Notebooks
- DBFS File Source & DataFrames
- Creating Temp View
- Dataframe Loads to TempView
- Data Filters in Temp View
- Data Aggregations in Temp View
- Creating Parquet Tables
Ch 9: Azure SQL Reads
- Azure SQL DB Connections
- Azure SQL Server & DB Names
- Connection String & URL Format
- Dataframes @ spark.read.jdbc()
- Aggregated / Incremental Tfns
- Data Loads into Spark Database
Ch 10: Azure SQL Writes
- DBFS FileStore into Dataframes
- SQL Database Connections
- Filters, Aggregations with DBFS
- Azure SQL DB Connections
- Dataframes To write.jdbc()
- Dataframes to Azure SQL DB
Ch 11: Medallion Architecture
- Medallion Architecture: Scaling
- Raw Data with Medallion
- Transformations (ETL)
- Bronze Layer : Raw Data
- Silver Layer with Temp Views
- Gold Layer with Spark Tables
Ch 12: PySpark Transformations
- Custom DataFrames
- Single List, Mixed List Options
- Concat Function & Index Options
- Removing Empty Rows
- Replacing Null Values
- Merge, Joins, Join Kind
Ch 13: Delta Tables (PySpark)
- Delta Tables : Upsert Activity
- Creating Delta Tables
- DML Operations in Delta Tables
- Upsert: Incremental Loads
- Delta Tables in HIVE Metastore
- MERGE INTO Statement (Spark)
Ch 14: Python Widgets (PySpark)
- Widgets: Notebook Parameters
- dbutils.widgets.text()
- dbuitls.widget.get()
- Reading Widgets into Variables
- Using Variables in Notebook
- Aggregated Loads with Widgets
Ch 15: Workflows (PySpark)
- Python Notebook Schedules
- Adding Tasks to Jobs
- Job Clusters & Cluster Sizes
- High Performance Cluster
- Unlimited Clusters
- Job Notifications, Verifications
Ch 16: Security
- IAM : Creating AD Users, Groups
- RBAC Concepts: IAM Roles
- Databricks Resource Security
- Databricks Workspace Security
- Notebook Job Level Security
- Job Level Security, Sharing
Ch 17: Spark Data Analytics
- Access Tokens & API Access
- JDBC Connections: Server Host
- HTTP Path & Port: Server URL
- Power BI Desktop : Get Data
- Spark Cluster Connections
- Data Access & Test Connection
Ch 18: Databricks Tuning
- Databricks Tuning: Caching
- Job Clusters & Cloud Computing
- Photon Acceleration
- Spot Instance & Unity Catalog
- Auto Scaling & Cluster Nodes
- Performance Optimizations
Ch 19: Scala Notebooks – V1
- Scala Notebooks: Realtime Use
- JVM and Scala Notebooks
- Creating Data Frames in Scala
- Creating Temp Tables in Scala
- Medallion Architecture
- Parquet Tables & Delta Tables
Ch 20: Scala Notebooks – V2
- Working with Widgets in Scala
- Variables and Parameters
- Dynamic Connections
- Format String (F String) Options
- Using SQL DB Connections in Scala
- Python Versus Scala in Realtime?
Databricks Certification Exam
Fabric Cloud Concepts
Fabric Cloud Migrations
Module 3: 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
