Azure Data Engineer Classroom Training

Complete Practical and Real-time Training on Azure Data Engineer. This Job Oriented Certification Course includes : Azure Fundamentals, Azure Active Directory, Azure SQL Databases, Azure Migrations, Azure Azure Data Factory (ADF), Azure Synapse, Azure Databricks (ADB), Azure Cosmos DB, Azure Stream Analytics, Azure Data Lake Storage, Azure Data Lake Analytics, Azure Key Vaults and Azure Data Share. Also includes End to End Real-time Project with Power BI Integrations including Storage Explorer Tool, Data Explorer Tool, Python/R/Scala Notebooks and Big Data Analytics.

This Azure Data Engineer Classroom Training course is applicable for DP 200 and DP 201 Microsoft Certification Examinations.

Azure Data Engineer Training Plans

  PLAN A PLAN B PLAN C
  Azure
Data Engineer
T-SQL, Azure
Data Engineer
T-SQL, Power BI, Azure
Data Engineer
Total Duration 6 Weeks 8 Weeks 12 Weeks
ADF : Azure Data Factory
ADF : Data Imports, ETL
ADF : Data Flows, Wrangling
ADF : Transformations, ETL
Synapse: Configuration, Loads
Synapse: ETL with ADF, DWH
Synapse: Performance Tuning
Synapse: MPP, cDWH, DIUs
ADB : Azure Data Bricks
ADB : Architecture, Data Loads
ADB : Run Spark Jobs, Pools
ADB : Workspace, Delta Tables
Cosmos : Configurations
Cosmos: Distribute Data, ETL
Cosmos: Integration with ADF
Cosmos: Structured Streaming
SQL: Database Basics, T-SQL
SQL : Constraints, Joins, Queries
T-SQL : Queries, SProcs, Lock Hints
SQL: Views, Group By, Self Joins
Power B: Report Design, Visuals
Power BI: M Lang, DX for ETL
Power BI: Report Server, Admin
Total Course Fee *
*Course Payable in Installments
INR 24,000
USD 325
INR 28,000
USD 379
INR 36,000
USD 487

Trainer: Mr. Sai Phanindra T

All Session Are Completely Practical & Real Time


Schedules for SQL Server & T-SQL
S No Timings (IST) Start Date  
  Regular Schedules [Mon - Fri]
1 6 AM - 7 AM Dec 29th Register
2 8 AM - 9 AM Jan 19th Register
3 10 AM - 11 AM Jan 4th Register
4 6 PM - 7 PM Jan 25th Register
5 8 PM - 9 PM Dec 3rd Register
6 9 PM - 10 PM Dec 14th Register
Azure Data Engineer Training Schedules
S No Timings (IST) Start Date  
  Regular Schedules [Mon - Fri]
1 9 AM - 10 AM Dec 8th Register
2 7 PM - 8 PM Dec 14th Register
  Weekend Schedules [Sat & Sun]
3 8 AM - 10 AM Dec 12th Register

If above schedule does not work, opt for Azure Data Engineer Training Videos

Azure Data Engineer Training Highlights :

✔ Azure Fundamentals ✔ Azure AD
✔ Azure SQL Concepts ✔ Azure Migrations
✔ Azure AD ✔ Azure Key Vaults
✔ Azure Monitor ✔ Azure Functions
✔ Azure Data Factory ✔ Azure Synapse
✔ Azure Synapse ✔ Azure Strorage
✔ Data Lake Storage ✔ Data Lake Analytics
✔ Stream Analytics ✔ IoT, Event Hubs
✔ Azure Cosmos DB ✔ Azure Databricks
✔ Azure Notebooks ✔ U-SQL & NoSQL
✔ Python, Scala ✔ Spark Clusters
✔✔ End to End Real-time Project @ Resume
 

Azure Data Engineer Training Course Contents:

Ch 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
  • SQL Server Components and Usage
  • Database Engine Component and OLTP
  • BI Components, Data Science Components
  • ETL, MSBI and Power BI Components
  • Course Plan, Concepts, Resume, Project
  • 24 x 7 Online Lab for Remote DB Access
  • Software Installation Pre-Requisites

Ch 5: SQL Basics - 3, T-SQL INTRO

  • Database Objects : Tables and Schemas
  • Schemas : Group Tables in Database
  • Schemas : Security Management Object
  • Creating Schemas & Batch Concept
  • Using Schemas for Table Creation
  • Data Storage in Tables with Schemas
  • Data Retreival and Usage with Schemas
  • Table Migrations across Schemas
  • Import and Export Wizard in SSMS
  • Data Imports with Excel File Data
  • Performing Bulk Operations in SSMS
  • Temporary Tables : Real-time Use
  • Local and Global Temporary Tables
  • # and ## Prefix, Scope of Usage

Ch 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

Ch 2: SQL SERVER INSTALLATIONS

  • System Configuration Checker Tool
  • Versions and Editions of SQL Server
  • SQL Server and SSMS Installation Plan
  • SQL Server Pre-requisites : S/W, H/W
  • SQL Server 2016 / 2017 Installation
  • SQL Server 2019 Installation
  • Instance Name and Server Features
  • Instances : Types and Properties
  • Default Instance, Named Instances
  • Port Numbers, Instance Differences
  • Service and Service Account Use
  • Authentication Modes and Logins
  • Windows Logins and SQL Logins
  • FileStream and Collation Properties

Ch 6 : CONSTRAINTS,INDEXES Basics

  • Constraints and Keys - Data Integrity
  • NULL, NOT NULL Property on Tables
  • UNIQUE KEY Constraints: Importance
  • PRIMARY KEY Constraint: Importance
  • FOREIGN KEY Constraint: Importance
  • REFERENCES, CHECK and DEFAULT
  • Candidate Keys and Identity Property
  • Database Diagrams and ER Models
  • Relationships Verification and Links
  • Indexes : Basic Types and Creation
  • Index Sorting and Search Advantages
  • Clustered and NonClustered Indexes
  • Primary Key and Unique Key Indexes
  • Need for Indexes - working with Keys

Ch 10: VIEW, SPs, 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 in SQL Server
  • Procedures : Types, Usage in Real-time
  • User & System Predefined Procedures
  • Parameters and Dynamic SQL Queries
  • Sp_help, Sp_helpdb and sp_helptext
  • sp_pkeys, sp_rename and sp_help
  • Important System Objects and Metadata

Ch 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 User Interface
  • Data Insertion & Storage. Limitations
  • SQL : Purpose and Real-time Usage
  • SQL Versus T-SQL : Basic Differences
  • DDL, DML, SELECT, DCL and TCL
  • Creating Tables using SQL Scripts
  • Data Storage, Inserts - Basic Level
  • Table Data Verifications with Select
  • SELECT Statement for Table Retrieval

Ch 7: JOINS, T-SQL Queries : Level 1

  • JOINS - Table Comparisons Queries
  • INNER JOINS For Matching Data
  • OUTER JOINS For (non) Match Data
  • Left Outer Joins with Example Queries
  • Right Outer Joins with Example Queries
  • FULL Outer Joins - Realtime Scenarios
  • Join Queries with "ON" Conditions
  • Join Unrelated Tables in SQL Server
  • NULL, IS NULL Operators in Joins
  • CROSS JOIN and CROSS APPLY
  • CROSS JOIN Versus CROSS APPLY
  • One-way & Two Way Data Comparisons
  • Important Join Queries in T-SQL
  • Join Options: Merge, Loop, Hash

Ch 11: Triggers & Transactions

  • Triggers - Purpose, Real-world Usage
  • FOR/AFTER Triggers - Real time Use
  • INSTEAD OF Triggers - Real time Use
  • INSERTED, DELETED Memory Tables
  • Using Triggers for Data Replication
  • Enable Triggers and Disable Triggers
  • Database Level, Server Level Triggers
  • Transactions : Types, ACID Properties
  • Transaction Types and AutoCommit
  • EXPLICIT & IMPLICIT Transactions
  • COMMIT and ROLLBACK Statements
  • Open Transaction Scenarios & Cause
  • Query Blocking Scenarios @ Real-time
  • NOLOCK and READPAST Lock Hints

Ch 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
  • Batch Concept and Go Statement
  • AND and OR Operators Usage
  • IN Operator and NOT IN Operator
  • Between, Not Between Operators
  • LIKE and NOT LIKE Operators
  • UPDATE Statement & Conditions
  • DELETE & TRUNCATE Statements
  • Logged and Non-Logged Operations
  • ADD, ALTER and DROP Columns
  • ALTER & DROP Table Statements

Ch 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 and Alternatives to Joins
  • Using Joins with Group By Queries
  • Using Joins with Nested Sub Queries
  • Sub Queries with Joins and Group By
  • Using UNION and UNION ALL in Queries
  • Nested Sub Queries with Group By, Joins
  • Comparing WHERE, HAVING Conditions

Ch 12 : ER MODELS, NORMAL FORMS

  • Normal Forms for Entity Relationships
  • First Normal Form and Atomocity
  • Second Normal Form, Candidate Keys
  • 3rd Normal Form Multi Value Dependancy
  • Boycee-Codd Normal Form : BNCF
  • Fourth Normal Form Realtime Advantages
  • Self Joins & Self Reference Keys
  • 1:1, 1:M, M:1, M:M Relationship Types
  • Joins with Group By Queries
  • Joins with Sub Queries, Formating
  • Office Data Connections, Excel Reports
  • Excel Pivot Reports and Reports
  • SQL Queries (Auto Generated) in BI Tools
  • FETCH OFFSET, NEXT ROWS, Order By
  • Data Refresh (Manual and Automated)
Real-time Case Study - 1 (Sales & Retail)
Objective : Database Design, Table Design and Relations.
Involves Purchases, Products, Customers and Time Data with Various Data Types.
Real-time Case Study - 2 (Sales & Retail)
Objective : Queries, Excel Integration
Pivot Tables, Pivot Charts, ODC Connections
1. Azure Fundamentals: What is Cloud? Advantages of Azure Cloud? IaaS, SaaS & PaaS. Azure Data Engineer Technologies, Job Roles. DP 200, 201 Exams Azure Account Registration and Free Trail Activation; Understanding Azure Resources and Resource Types; Creating Resource Groups in Azure Portal;
2. Azure SQL Server: Azure Resources; Resource Groups; Azure SQL Server [Logical Server] Creation; Server Name Format and Firewall Rules; Azure Services Access with Firewall; Test Connections with SSMS Tool and Azure Data Studio Tool; Creating Azure SQL Databases in Portal, T-SQL; Tables, Data Inserts;
3. Azure SQL DB Migrations: Azure SQL DB Migrations from OnPremise; Using Data Migration Assistant Tool; Migration Assessments; Deploy Schema & Migrate Data Options; Onpremise Versus Azure SQL DB Differences; Generating bacpac Files From SSMS Tool; Azure SQL DB Exports & Imports;

Mod 1: Azure Data Factory, Azure Synapse, Azure Data Share, Azure Key Vaults

Mod 2: Azure Storage, Azure Data Lake Storage, Azure Data Lake Analytics, U-SQL

Mod 3: Azure Databricks, Azure Cosmos DB, Azure Stream Analytics, NoSQL

Ch 1: Azure Data Factory, Synapse Intro

  • Azure Data Factory (ADF) Operations
  • Hybrid Data Ingestion, Orchestration
  • Data Processing & Movement in ADF
  • Data Pipelines, Flows & Wrangling
  • Data Mashup and ETL in Azure
  • Azure Synapse (Data Warehouse)
  • Enterprise Warehouse with Synapse
  • Azure Synapse (SQL Pools) Creation
  • DWUs : Data Warehouse Units &
  • Big Data Storage and Analytics
  • Column Store in Azure Synapse
  • Automated Tuning and Security
  • Access, Pause/Resume with Synapse
  • SSMS & ADS Tools Connections

Ch 11: Azure Storage Concepts

  • Azure Storage Managed Service & Use
  • Azure Storage Services and Types
  • High Availability, Durability, Scalability
  • Blob: Binary Large Object Storage
  • General Purpose : Gen 1 and Gen 2
  • Blobs, File Share, Queues and Tables
  • Data Lake Gen 2 with Azure Storage
  • Blob - File System and Object Storage
  • Queues: Message Store, Secured Access
  • File Share - SMB [Server Message Block]
  • Azure Tables - Unstructured Data Store
  • Block Blob, Append Blob and Page Blobs
  • HTTP & HTTPS Access to Azure Services
  • Azure Storage Containers, End Points

Ch 21: Azure Databricks Configurations

  • Azure Databricks - Spark Based Analytics
  • ADB Workspace &Data Science Analytics
  • Workspace Options, Databricks Runtime
  • Serverless Storage, ETL, Analytics
  • Databricks File System DBFS in Real-time
  • Notebooks: SQL, Spark, Python, Scala
  • Apache Spark Eco System & Integrations
  • Azure Databricks Deployments, Workspace
  • Databricks Pricing; Databricks Units (DBUs)
  • Databricks Storage, Network Security Group
  • Databricks Clusters : Architecture
  • Standard & High Concurrency Clusters
  • Databricks Pools, Capacity : CPU, Memory
  • Autopilot Options; Worker & Driver Nodes

Ch 2: Azure Synapse Architecture

  • MPP - Massively Parallel Processsing
  • Control Node and Compute Nodes
  • Azure Storage, DMS and DWUs
  • Round Robin, Replicate, Hash Tables
  • Service Level Objective, Sharding
  • Resource Classes; Gen 1 and Gen 2;
  • Table Creation, Storage, Distribution
  • CTAS: Create Table As Select. Indexes
  • Distribution Types, Time Partitions
  • Logins and Users in SQL Server
  • Users and Roles in Synapse SQL DW
  • Resource Classes; Blob Data Import
  • COPY INTO Statement in T-SQL
  • Data Monitoring Scripts with T-SQL

Ch 12: Azure Tables & Azure BLOB

  • Azure Tables - Real-time Use, NoSQL
  • Schema-less Design and Access Options
  • Structured and Realtional Data Storage
  • Tables, Entities and Properties Concepts
  • Azure Storage Account for Table Store
  • Azure Tables in Portal - GUI, Data Types
  • Azure Tables using Storage Explorer Tool
  • Query Azure Tables @ Query Builder
  • Data Imports From Excel, CSV Files
  • BLOB Data Imports @ T-SQL Queries
  • SAS: Shared Access Signature
  • CSV Uploads, Downloads, Edits, Keys
  • Master Key Credentials, External Sources
  • BULK INSERT Statement, Data Imports

Ch 22: Databricks Notebooks, Spark Jobs

  • Databricks Workspace and Spark Clusters
  • FileStore and Tables. Notebook Options
  • Data File Uploads an Tables to DBFS
  • Notebook Creation, Cells, Cmd Executions
  • Python Notebooks, ETL, Data Access
  • Data Frames Creation, Access, Analytics
  • Reports, Graphs, Plot and Custom UI
  • Spark Jobs with Azure Open Datasets
  • Notebooks For Azure BLOB Data Access
  • Remote Data @ Spark Jobs in Notebooks
  • Parquet Files and Data Frames with Spark
  • Select Queries on Temporary Data Views
  • Bar Chart and Custom Reports, Analytics
  • ADB Plots: Aggregation and Display Type

Ch 3: Azure Data Factory Architecture

  • ADF Pipeline Design, Publish, Trigger
  • ADF Architecture, Pipelines & ETL
  • DIU : Data Integration Units; Concurrency
  • Linked Service, Dataset & Activities
  • Staging Data - Advantages and Pricing
  • Polybase Indexes, Compression Options
  • Mapping Data Flow, Wrangling Data Flow
  • Pipeline Creation using Copy Data Tool
  • Azure BLOB Storage to Synapse DB
  • Linked Service and Datasets. Mapping
  • Polybase; Staging, Bulk Import Options
  • Validate, Publish Pipelines to ADF Store
  • Pipeline Execution (Triggers), Monitoring
  • Auto Resolving Integration Runtime (IR)

Ch 13: Azure Files, Queues & Security

  • Azure Files - SMB Protocol, Creation
  • Shared Access, Fully Managed, Resilency
  • Performance, Size Requirements for Shares
  • Azure Storage Explorer Tool for File Access
  • Azure Queues and Message Queues
  • Adding Messages, Queing and De-Queing
  • Clear Queue and Messages from Explorer
  • Azure Storage Security - Storage Keys
  • Shared Access - Primary, Secondary Keys
  • SAS: Shared Access Signature Generation
  • Encryption and Data Security at REST
  • CORS (Cross Origin Resource Sharing)
  • Auditing Access, Network Access Rules
  • Firewall, Advanced Threat Protection

Ch 23: Python Notebooks & Operations

  • Databricks Notebooks, Cells and Usage
  • Execution & Idle Contexts and Evictions
  • Azure Databricks Notebooks Tasks
  • Cluster Configuration Metadata Reads
  • Notebook Schedules, Cloning, URL Path
  • Notebook Exports and Imports; Re-use
  • Cluster Configurations with Notebooks
  • Python Notebooks and Magic Commands
  • CSV Files to DBFS. Access using Python
  • JDBC Hosts, Connection String, Access
  • SQL Contexts & SQL DB Connections
  • Data Imports with pyspark Assemblies
  • Pandas Data frames in Python Notebooks
  • Tables and Data Imports using Notebooks

Ch 4: Azure Data Lake with ADF

  • Creating Azure Data Lake Storage
  • Data Lake Gen 2 Hierarchial Namespace
  • Excel Upload to Container, Data Preview
  • Pipeline Parameters, Variables, OUT
  • Copy Data Tool: Timeout and Schedule
  • Secured Pipelines and Linked Services
  • Sink Options; Colum Mapping, Triggers
  • Azure SQL Database Loads to Synapse
  • Azure SQL Database Tables Data Loads
  • For Each Loops with ADF Pipelines
  • Copy Data Tool, Pipeline Edits in ADF
  • Task Schedules and Tumbling Window
  • Pipeline Execution & Runs; Monitor

Ch 14: Azure Monitor, KQL, Power Shell

  • Azure Monitor Components for Storage
  • Metrics and Logs with Azure Storage
  • Monitoring the Azure Storage Namespaces
  • Adding KQL Metrics; Account, Blob and File
  • Ingress & Egress Chart; Average Latency
  • Request Breakdowns, Signal Logic Options
  • Alerts, Conditions, Notifications and Emails
  • Power Shell Commands for Azure Storage
  • PowerShell Remoting: Scripts and cmdlets
  • Background Jobs, Transactions & Eventing
  • Network Transfer & Power Shell Types
  • $ # Prefix, Resource Groups in Power Shell
  • Creating Storage Account, Context & Files

Ch 24: Scala Notebooks, SQL Notebooks

  • Scala Notebooks and Big Data Loads
  • CSV Files from Databricks File System
  • Data Source Connections with Spark
  • Driver Classes and SQL Server Drivers
  • Data Frames in Spark, Reading Data
  • Display, Transformations with Spark
  • Data Loads to Azure SQL Synapse
  • SQL Notebooks & Data Frame, Access
  • Python Magic Comands for Data Access
  • Data Frame View, Testing data.take(n)
  • SQL Context for Data Representations
  • SQL in Notebooks: SELECT, WHERE
  • ORDER BY, GROUP BY, TOP, LIMIT

Ch 5: On-Premise Data to Azure

  • On-Premise Data Sources with Azure
  • Install Self Hosted Integration Runtime
  • Access Keys & Use. Configuration Tools
  • Remote Linked Services in ADF & SH IR
  • Authentication with Integration Runtime
  • Sourc, Sink Linked Service Connections
  • Incompatable Rows Skip, Fault Tolerance
  • Table Mapping, Column Mapping, Errors
  • Synapse Pool Connection with Onpremise
  • Staged Data Copy & ETL Performance
  • Azure Blob for Staging. Polybase
  • Connections Management - Preview
  • Pipeline Exectution, Run IDs, Errors

Ch 15: Azure Stream Analytics, Event Hubs

  • Azure Stream Analytics Pattern, Realations
  • Ingest & Analyse; Stream Analytics Jobs
  • IoT Hub, IoT Devices; Transformations
  • IoT, Stream Analytics Jobs Monitoring
  • Stream Analytics Jobs: Edits, Security
  • Streaming Units, Error Handling
  • Test Result, Output Schema in Hubs
  • IoT Hubs, IoT Events: Azure SQL DB
  • Azure Stream Analytics Integration
  • Event Hub Policies, Consumer Groups
  • Power BI Reports from Azure Storage
  • Shared Access Signature with Power BI
  • Data Visualizations with Azure Storage

Ch 25: Databricks Jobs & Power BI

  • Databricks Jobs : Creation and Usage
  • Job, Workspace & Concurrency Limits
  • Notebooks with and without Parameters
  • Jobs with Default Parameter Execution
  • Interactive and Automated Clusters
  • Job Schedules & Manual Executions
  • Active Jobs and Job Monitoring with ADB
  • Databricks with Power BI Desktop
  • Spark Connectors in Power BI
  • Access Token from Azure Databricks
  • Spark Cluster Connections, Nodes, Pools
  • Server Host Name, Ports and HTTP
  • Power BI Reports with Databricks

Ch 6: Incremental Loads with ADF - 1

  • ADF Pipelines with Stored Procedures
  • Watermark Tables and Timestamp Columns
  • Incremental Data Loads to Azure DW
  • New Rows and Old Rows Indentifications
  • Storing High Water Mark Data
  • Stored Procedures for Timestamp Updates
  • Azure Storage Container Incremental Loads
  • Lookup in ADF Portal & ModifiedDate
  • Expressions in ADF Portal for Lookup
  • Expressions in ADF Portal for Source
  • @activity with output Data Pipelines
  • SQL Queries for Dataset Creation
  • Concat Function, Run IDs For File Names
  • ADF Pipeline Validation and Triggers

Ch 16: Azure Data Lake Storage (ADLS)

  • Azure Data Lake Storage - Data Store
  • LIVE Edits, Permissions & Sharing
  • Hadoop based on Apache YARN
  • HDFS File System , Map Reduce
  • Authentication & Access Control
  • Azure Data Lake Gen 1 - Deployment
  • Encryption with Service Master Key
  • ADLS - Pricing and Instance Details
  • Data Explorer Tool in Azure Portal
  • Azure Strorage Explorer Tool
  • File Preview and Header Row Promotion
  • Download / Rename / Access Properties
  • Folder Upload & Download; Quick Access
  • Cached File Access & Folder Statistics

Ch 26: Azure Cosmos DB - Architecture

  • Azure Cosmos DB: Gloabally Distributed
  • Multi Model Support for Big Data
  • Turnkey Global Distribution in Cosmos
  • Always-On, Elastic Scalability, Low Pricing
  • SQL API, Mongo DB, Cassandra, Gremlin
  • Table API: Real-time Applicative Uses
  • Azure Cosmos DB and Database Concept
  • Containers - Collection, Table & Graph
  • Items - Document, Rows, Node and Edge
  • Create Azure Cosmos DB Account in Portal
  • Create Azure Cosmos DB with Data Explorer
  • Creating Containers, Add JSON Documents
  • Data Store and Data Access (Querying)
  • Scaling Options for Cosmos DB & Cautions

Ch 7: Incremental Loads with ADF - 2

  • Incremental Load Pipeline Design in ADF
  • Working with Azure Storage Containers
  • Pipeline Executions, Incremental Schedules
  • Regular Schedules & Tumbiling Windows
  • Binay Copy, Last Modified Date in Blob
  • Pipeline Trigger Schedules, Modifications
  • Incompatable Rows Skips, Fault Tolerance
  • Incremental Loads with Mutliple Tables
  • Stored Procedures, Loops in ADF Pipelines
  • Configure ETL Sources, Pre-Copy Scripts
  • Using @{item() with Dyanamic Connections
  • Table_Schema for Column Mapping
  • Writing Expressions For Dynamic Loads
  • Staging and Performance for ADF Loads

Ch 17: ADLS Monitoring, Alerts

  • Azure Data Lake Monitoring and Alerts
  • ADL Metrics, Storage Utilization Reports
  • Reads & Writes Metrics; Charts, Metrics
  • Data Reads, Writes, Requests - Storage
  • Report Shares, Download to Excel, Alerts
  • Scope, Conditions and Action Groups
  • Email Notifications and Scope Options
  • ADLS - Security Management and Levels
  • ADLS Resource Levels, Folder / File Leve
  • IP Address; Role Based Access (RBAC)
  • Access Control Lists (ACL), IAM AD Roles
  • POSIX - Access ACLs and Default ACLs
  • ACL Permissions; Read, Write,; Execute
  • Super User, RWX, Owning Users, Groups

Ch 27: Azure Cosmos DB Queries Level 1

  • Hierarchial JSON Documents with Cosmos
  • Embrace SQL, Extend SQL with NoSQL
  • Writing, Adding and Importing JSON
  • NoSQL Query Concepts and Executions
  • SELECT Format and Query Items
  • Request Charge, Results and IO Reads
  • Writes, Index, Lokup and Roundtrip
  • JSON Document & Key Value Pairs
  • Data Storage, Query: WHERE, SET
  • FROM, Aliases, Geo Spatial Queries
  • JSON Scripts to Access Sub Documents
  • Hierarchial Data, Parent-Child Relations
  • NoSQL: Unary and Binary Operators
  • SELECT with IN, BETWEEN, TOP, JOIN

Ch 8: Mapping Data Flow in ADF

  • Data Flow Task Creation in ADF Pipelines
  • Transformation Editor and Parameters
  • Comparing ADF Pipelines and Data Flow
  • Debugging: ADF Managed Executions
  • Apache Spark Clusters @ ADF Debugging
  • Authoring Data Flow, Graph, Configuration
  • Transformation Setting, Optimize, Inspect
  • Conditional Split Transformation in ADF
  • Pivot Transformation in Mapping Data Flow
  • Pivot Column & Aggregation Functions
  • Pivot Transformation, Pivot Settings
  • Pivot Key Value, Enabling Null Values
  • Pivoted Columns, Pattern, Optimize
  • Column Prefix, Help Graphic, Metadata

Ch 18: Azure Key Vaults & ADL Analytics

  • Azure Passwords, Keys and Certificates
  • Azure Key Vaults - Name and Vault URI
  • Inbuilt Managed Key, Azure Key Vault
  • Standard & Premium Azure Key Vaults
  • Identify Vault Name, URI: Access Points
  • Secret Page, Key Backups & Restores
  • Adding Keys to Azure Vaults, Types
  • Azure Data Lake Analytics Creation
  • Dynamic Scaling, U-SQL Implementation
  • Azure Data Lake Storage for Data Lake
  • Jobs Creation, Execution Environment
  • Distibuted Runtime Environment in ADLA
  • ADLA - On-demand Job Service in Azure
  • Exabyte Scale and Data Lake in USQL

Ch 28: Azure Cosmos DB Queries Level 2

  • Data Import Tool : Installation and Usage
  • JSON Data Imports to Azure Cosmos DB
  • Azure Cosmos Endpoints, Access Keys
  • NoSQL Queries on JSON Documents
  • Writing Stored Procedures & Functions
  • ACID Properties : Atomocity, Consistency
  • Isolation, Durability with Procedures
  • SP Coding, Execution with Parameter
  • Stored Procedures for Document Uploads
  • Procedures with Variables, getResponse()
  • Procedure Advantages, Execution Option
  • User Defined Functions (UDF) in Cosmos
  • UDF Executions using Cosmos DB Scripts
  • Dynamic Calculations & Reporting Options

Ch 9: Wrangling Data Flow in ADF

  • Wrangling Data Flow in ADF : Advantages
  • Power Query Online Editor for Mashup
  • Spark Code for Cloud Scale Executions
  • Wrangling Data For Less Formal Analytics
  • Sources and Sinks with Wrangling DF
  • Github Integration with ADF Repository
  • User Defined Data Stores in GitHub
  • Transformations in Data Wrangling
  • Group By, Aggregate, Reordering
  • Pivot, Aggregations in Power Query
  • ADF Data Types & ADF Pipeline Store
  • Heterogenous Sources in Power Query
  • ADF Publish, GitHub Store Differences

Ch 19: Data Lake Analytics, U-SQL 1

  • Azure Data Lake Analytics : Advantages
  • USQL - Big Data Processing Language
  • Azure Portal and Visual Studio Access
  • Aggregate, Analytical, Ranking Functions
  • U-SQL Catalog : Databases and Objects
  • Rowsets, Types and USQL Expressions
  • Azure U-SQL Jobs For Data Insertions
  • U-SQL Jobs for Storage, Retreival
  • SELECT, EXTRACT & OUTPUT Clauses
  • USING, Outputters, Extractors Classes
  • Script Execution, Job Graph, Diagnosis
  • AU Allocation, Analysis for Job Execution
  • Script Reuse. CSC, User & System Errors

Ch 29: Azure Notebooks, Azure Functions

  • Azure Notebooks, Serverles Deployments
  • Azure Cosmos Notebooks and Advantages
  • Jupyter Notebook : Implementation, Usage
  • Pandas DataFrame with Python Scripts
  • Understanding Notebook and Cells
  • Python Script for Azure Cosmos DB
  • Python Script for Data Import & Report
  • Azure Functions: Creation and Apps
  • Azure Functions @ Cosmos DB Triggers
  • Azure Function App Service Plans
  • Serverless Components, Azure Insight
  • Azure Cosmos DB Monitoring, Logs
  • Azure Monitor Workbooks, Timelines

Ch 10: ADF : End to End Implementation

  • Azure Data Share: Configuration & Use
  • Azure Data Share: PaaS for ADF Shares
  • Importing BACPAC Files into Azure
  • Azure SQL DB: Data Lake Storage Gen 2
  • Data Filters, Aggregations, Joins in ADF
  • Spark Clusters for DataFlow Debugging
  • Multi Leve Data Flows in ADF Pipeline
  • Data Loads to Azure Synapse from ADLS
  • Data Load Settings and Optimization
  • ADF Pipeline Debugging, Publish in ADF
  • Data Shares with Azure Synapse Tables
  • Data Ingestion, Consumption with Synapse
  • Recipients and Azure AD Users, Accounts
  • Run IDs, Monitoring, Cost Analysis, Metrics

Ch 20: Data Lake Analytics, U-SQL 2

  • U - SQL Operations with Visual Studio
  • Script.usql, Executions & Job Graphs
  • ADLA Account & Local Job Executions
  • Metadata, State History & AU Analysis
  • Working with TSV Data Sources in ADLS
  • Extract, Format, Data Loads with U-SQL
  • Adding New Columns to Files with U-SQL
  • ADLA Jobs For Create Databases, Tables
  • ADLA Managed Tables & External Tables
  • Create Tables from Query Rowset Option
  • Clone & Copy Tables using U-SQL Jobs
  • Hash Distributed Tables, Clustered Index
  • TVF - Table Valued Functions, Retreival
  • SELECT, TOP, FETCH & ROW_NUMBER

Ch 30: Azure Cosmos DB Admin, Power BI

  • Conistency Levels in Azure Cosmos DB
  • Bounded Staleness, Session, Consistent Prefix
  • Eventual, Synchronization Options with Cosmos
  • Azure Cosmos DB : Backups & Restores. Retentions
  • IAM - Identity Access Management with Azure AD
  • Owner Role, Contributor Role and Reader Role
  • Cosmos DB Backup Operator, Account Reader Roles
  • Global Distribution Strategies and BCDR
  • Data Replication Options and High Availability
  • Multi Region Writes and Data Access Options
  • Azure Cosmos Database Cost Calculation Options
  • Availability Zones, Manual / Automated Failvoer
  • Azure Cosmos Database Cost Calculation Options
  • Costing Factors: Workloads and Multi Region Writes

Real-time Project @ Ecommerce Domain:

 

Includes On-Premise Migrations with bac Files, Azure Storage Compoments, Azure Data Ingestions using Azure Data Factory; Big Data Storage wit Synapse, Cosmos Database; Big Data Analytics using Azure Databricks and End User Reporting. Resume Support and DP 200 & DP 201 Certification

Part 1: Power BI Report Design

Part 2: ETL, Data Modeling, DAX

Part 3: Power BI Cloud, Admin

Ch 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
  • MCSA 70-778, MCSA 70-779 Exam
  • Types of Reports in Real-World
  • Interactive & Paginated Reports
  • Analytical & Mobile Reports
  • Data Sources Types in Power BI
  • Power BI Licensing Plans - Types
  • Power BI Training : Lab Plan
  • Power BI Dev & Prod Environments

Ch 7 : POWER QUERY LEVEL 1

  • Power Query M Language Purpose
  • Power Query Architecture and ETL
  • Data Types, Literals and Values
  • Power Query Transformation Types
  • Table & Column Transformations
  • Text & Number Transformations
  • Date, Time and Structured Data
  • List, Record and Table Structures
  • let, source, in statements @ M Lang
  • Power Query Functions, Parameters
  • Invoke Functions, Execution Results
  • Get Data, Table Creations and Edit
  • Merge and Append Transformations
  • Join Kinds, Advanced Editor, Apply
  • ETL Operations with Power Query

Ch 13 : POWER BI CLOUD - 1

  • Power BI Service Architecture
  • Power BI Cloud Components, Use
  • App Workspaces, Report Publish
  • Reports & 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 Page Interaction in Dashboard
  • Adding Media: Images, Custom Links
  • Adding Chs and Embed Links
  • API Data Sources, Streaming Data
  • Streaming Dataset Tiles (REST API)

Ch 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

Ch 8 : POWER QUERY LEVEL 2

  • 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 Transformations
  • Move Column and Split Column
  • Extract, Format and Numbers
  • Date & Time Transformations
  • Deriving Year, Quarter, Month, Day
  • Add Column : Query Expressions
  • Query Step Inserts and Step Edits

Ch 14 : POWER BI CLOUD - 2

  • Dashboards Actions,Report Actions
  • DataSet Actions: Create Report
  • Share, Metrics and Exports
  • Mobile View & Dashboard Themes
  • Q & A [Cortana] and Pin Visuals
  • Export, Subscribe, Subscribe
  • Favorite, Insights, Embed Code
  • Featured Dashboards and Refresh
  • Gateways Configuration, PBI Service
  • Gateway Types, Cloud Connections
  • Gateway Clusters, Add Data Sources
  • Data Refresh : Manual, Automatic
  • PBIEngw Service, ODG Logs, Audits
  • DataFlows, Power Query Expressions
  • Adding Entities and JSON Files

Ch 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 with Slicer
  • Disabling Slicers,Clear Selections
  • 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

Ch 9 : POWER QUERY LEVEL 3

  • 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
  • Testing 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

Ch 15 : EXCEL & RLS

  • 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 Modeling in Power BI Desktop
  • DAX Roles Creation and Testing
  • Adding Power BI Users to Roles
  • Custom Visualizations in Cloud
  • Histogram,Gantt Chart,Infographics

Ch 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

Ch 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, Using Columns with DAX
  • Quick Measures and Summaries
  • Validation Errors, Runtime Errors
  • SUM, AVERAGEX, KEEPFILTERS
  • Dynamic Expressions, IF in DAX

Ch 16 : Report Server, RDL

  • 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 For Report Server
  • 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 Generation and Use
  • Mobile Report Publisher, Usage

Ch 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
  • SQL Queries and Enter Data
  • Data Modeling : Currency, Relations
  • Summary, Format, Synonyms
  • Web View & Mobile View in PBI

Ch 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
  • Entity Sets and Slicing in DAX
  • Dynamic Expressions, RETURN
  • Date, Time and Text Functions
  • Logical, Mathematical Functions
  • Running Total & EARLIER Function

Ch 17: MSBI Integrations

  • Power BI with SQL Server Source
  • Power BI with SQL Data Warehouse
  • Power BI with SSAS OLAP Server
  • Power BI with Azure SQL DB Source
  • Power BI with Azure SQL Warehouse
  • Power BI with Azure Analysis Server
  • Power BI with SSRS (RDL) Reports
  • Power BI Report Builder Tool
  • Installation & Configuration
  • Paginated Reports Design, Use
  • Data Sources, Datasets, RDL
  • Report Publish (RDL) to Cloud
  • Report Verifications, Data Sync
  • Interactive Vs Paginated Reports
  • Creating, Managing Alerts in Cloud

Ch 6 : Visualization Properties

  • Stacked Charts and Clustered Charts
  • Line Charts, Area Charts, Bar Charts
  • 100% Stacked Bar & Column Charts
  • Map Visuals: Tree, Filled, Bubble
  • Cards, Funnel, Table, Matrix
  • Scatter Chart : Play Axis, Labels
  • Series Clusters & Selections
  • Waterfall Chart and ArcGIS Maps
  • Infographics, Icons and Labels
  • Color Saturation, Sentiment Colors
  • Column Series, Column Axis in Lines
  • Join Types : Round, Bevel, Miter
  • Shapes, Markers, Axis, Plot Area
  • Display Units,Data Colors,Shapes
  • Series, Custom Series and Legends

Ch 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 in DAX
  • TODAY, DATE, DAY with DAX
  • Time Intelligence Functions - DAX

Ch 18 : REAL-TIME PROJECT
  • Project Requirement Analysis
  • Implementing SDLC Phases
  • Requirement Gathering, FSA
Phase 1:
  • PBIX Report Design
  • Visualizations, Properties
  • Analytics and Formating
Phase 2:
  • Data Modeling, Power Query
  • Dynamic Connections, Azure DB
  • Parameters and M Lang Scripts
Phase 3:
  • DAX Requriements, Analysis
  • Cloud and Report Server
  • Project FAQs and Solutions
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