Snowflake Data Engineer Training From SQL School Training Institute

Complete Practical and Real-time Snowflake Training with Basic to Advanced Cloud Concepts, ETL (Extract, Transform and Load), DWH (DataWarehouse), Big Data Storage, Big Data Analytics, Incremental Loads, External Stages, SnowPipes, Failsafe Concepts, Data Recovery, Security Management, ETL Management, Administration, Azure Integrations, Power BI Integrations, External Data Connections and more..

This Snowflake Training Classes also includes Concept wise FAQs, Real-time Project, Project Solution, Project FAQs for your Job Interviews, Snowflake Core Certification Guidance with Real-Life Scenarios.

Snowflake Data Engineer Training

  PLAN A PLAN B PLAN C
Course includes Snowflake Snowflake,
Azure Data Engineer
Snowflake, Azure Data Engineer
Power BI
Total Duration 4 Weeks 11 Weeks 15 Weeks
Snowflake: DWH and ETL
Snowflake: Cloud Configurations
Snowflake: DWH Architecture
Snowflake: Database, Schemas
Snowflake: Constraints, SP, Tasks
Snowflake: Partitions & Tuning
Snowflake: Security Management
Snowflake: Automated Backups
Snowflake: SnowSQL Concepts
Snowflake: Variables & Tasks
Snowflake: File Formats, Stages
Snowflake: External Stages
Snowflake: Azure Integration
Snowflake: Snow Pipes & Upserts
Snowflake: Power BI Analytics
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
DP 203 Certification Guidance
Power BI Report Design
Power BI Desktop, Custom Visuals
Data Modelling with Power Query
Data Modelling with DAX
Power BI Cloud, Excel Analysis
Power BI Mobile, R, REST API
PL 300 Exam Guidance
Real-Time Project in Power BI

Trainer: Mr.Sai Phanindra (17+ Yrs of Exper)

All Session Are Completely Practical & Real Time


If above schedules does not work for you, please register for Power BI Training Videos

TRAINING HIGHLIGHTS

Custom Visuals Power BI Mobile
Big Data Sources R, Python, JSON
Excel Analysis Excel Online
Google Big Query Report Server
Gateways, Rest API Power BI Admin
✔ Tabular Mode ✔ Data Models
✔ Tabular Mode OLAP ✔ Tabular Mode DAX
✔ Cube Design ✔ Excel Analytics

Snowflake DataEngineer Training Course Contents:

Mod 1: Snowflake Architecture, Basics

Mod 2: Snowflake Concepts, Admin

Mod 3: ETL, Stages & Pipes

Ch 1: Introduction to Cloud & Snowflake

  • Database Introduction & Database Types
  • OLTP, OLAP and Warehouse Databases
  • Need for Datawarehouses; Advantages
  • Popular Database Technologies
  • Popular Datawarehouse Technologies
  • Need for Cloud & Remote DWH Store
  • Cloud Implementation Types & Usage
  • IaaS: Infrastructure As A Service
  • PaaS: Platform As A Service
  • SaaS: Software As A Service
  • Snowflake Cloud: Introduction
  • Snowflake: Popular SaaS Platform
  • Cloud Datawarehouse Concepts
  • Advantages, Dependencies in Snowflake

Ch 7: Constraints and Data Types

  • Snowflake Constraints, Data Validations
  • NULL and NOT NULL Properties
  • Unique, Primary and Foreign Keys
  • Working with Named Constraints
  • Single Column, Multi Column Constraints
  • Inline and Out Of Line Constraints
  • Table Constraints Types, Real-time Use
  • Constraint Properties: ENFORCED
  • DEFERRED, IMMEDIATE Options
  • Numeric, String and Binary Data Types
  • Boolean Data Types and Usage
  • Date and Time Data Types
  • Semi Structured Data Types
  • Geospatial & Variant Data Types

Ch 13: Snowflake Tasks, Partitions

  • Snowflake Tasks and Real-time Use
  • Snowflake Serverless Compute Model
  • User Managed & Snowflake Managed
  • Tasks Tree: Root and Link Concepts
  • Directed Acyclic Graph (DAG)
  • Tasks Schedules and RESUME Options
  • CREATE, ALTER, DESCRIBE, SHOW
  • CREATE TASK … AFTER Statement
  • ALTER TASK … ADD AFTER Statement
  • CRON Syntax with Tasks, Procedures
  • Virtual Warehouse Concepts (DWH)
  • Multi Cluster Warehouse Config
  • Client Utilities, Drivers & Connectors
  • Auto Scale Options, Billing (Pricing)

Ch 2: Snowflake Account & Editions

  • Creating Snowflake Account (Cloud)
  • Snowflake Trail Account: Limitations, Uses
  • Snowflake Account Components
  • Cloud Platform: Azure, AWS, Google Cloud
  • Regions and Availability with Snowflake
  • Snowflake Editions, Credits; UI Usage
  • Default Accounts; Web UI & Snow Sight
  • Snowflake Storage: Ondemand, Capacity
  • Snowflake Editions and Comparisons
  • Standard Edition: Features, Advantages
  • Enterprise Edition: Features, Advantages
  • Business Critical Edition: Features, Usage
  • Virtual Private Edition (VPS) & Pricing
  • Snowflake Pricing: Ondemand Vs Capacity

Ch 8: Snowflake Cloning (Zero Copy)

  • Cloning Operations with Snowflake
  • Zero Copy and Schema Level Cloning
  • Real-time Uses: Cloning in Snowflake
  • Snapshot Concept, Metadata Options
  • Possible Objects for Snowflake Clone
  • Permissions for Snowflake Cloning
  • Accessing, Controlling Cloned Objects
  • Real-time Considerations @ Cloning
  • Storage Layer and Metadata Layer
  • Cloning with Foreign Key Constraints
  • Cloning Snowflake Databases
  • Cloning Snowflake Schemas, Tables
  • Security and MANAGE GRANTS
  • Cloning and COPY GRANTS Options

Ch 14: SnowSQL and Variables

  • SnowSQL: Concepts, Client Installation
  • SnowSQL Tool: Configuration Options
  • SnowSQL: Account Authorization
  • DDL, DML and SELECT Operations
  • Snowflake SQL Query Syntax Format
  • SnowSQL Command Line Options
  • Working with DB, Schema and Tables
  • Snowflake Variables, Batch Processing
  • Snowflake SQL Data Types, Usage
  • DECLARE, LET, BEGIN and END
  • EXECUTE IMMEDIATE, FOR, END FOR
  • Creating Warehouse, Database, Tables
  • Granting Permissions, Query Execution
  • Writing Output to Files (Win, MAC OS)

Ch 3: Architecture, Warehouse (DWH)

  • Snowflake Architecture & Compute
  • Shared Disk, Shared Nothing Architecture
  • Cluster Nodes and Snowflake Clusters
  • CPU & Memory Resources in Clusters
  • Disk Storage and Network Communication
  • Storage Layer and Cloud Service Layer
  • Database Query Layer & Data Cycle
  • Snowflake Datawarehouse Architecture
  • MPP: Massively Parallel Processing
  • Compute and Storage Components
  • Column Store and Virtual Warehouse
  • Datawarehouse Creation in SnowSight
  • Classic UI with Snowflake; Navigations
  • Data Load and Billing; Auto Suspend

Ch 9: Snowflake Procedures & Views

  • Snowflake Procedures and Functions
  • Creating and Using Stored Procedures
  • Using CALL Command in Snowflake
  • SQL and JavaScript Options with SPs
  • Snowflake Deferred Name Resolution
  • Overloading with Snowflake SPs
  • Transactions & Injection
  • Variables & CALL Command
  • Using execute() with Procedures
  • sqlText:command, createStatement
  • Cursoring Operations
  • Dynamic DML Operations with SPs
  • Loops & next.scan()
  • RETURN and RETURNS Statements
  • Views & Query Storage
  • DML and SELECT Operations on Views
  • Regular Views, System Predefined Views
  • Recursive Views, Parameterized Views

Ch 15: Snowflake Partitions, Stages

  • Snowflake Partitions, Real-time use
  • Service and Storage Layer Concepts
  • Micro Partition with DML, CDC
  • Cluster Key: Usage, ReClusters
  • Depth and Overlap Properties
  • Internal Partition Types & Usage
  • List, Range and Hash Partitions
  • SYSTEM$CLUSTERING_INFORMATION
  • Snowflake Stages and Usage
  • Internal and External Stages
  • User Stages : Creation, Usage
  • Table Stages: Creation, Usage
  • Internal Named Stages, Usage
  • COPY Command, Bulk Data Loads

Ch 4: Snowflake Databases & Tables

  • Snowflake Databases and Data Storage
  • Need for Snowflake Warehouse, Compute
  • Database Objects and Hierarchy
  • Snowflake Worksheet Parameters
  • Database Creation with Snowflake UI
  • Retention Time, DB List & Connections
  • Permanent and Transient Databases
  • Snowflake Tables and their Usage
  • Permanent, Transient & Temp Tables
  • Creating Tables with SnowSight
  • Describe Options, Data Inserts
  • CREATE TABLE AS SELECT
  • Cloning Tables, Case Sensitivity Options
  • Collation, ALTER, DROP & UNDROP

Ch 10: Security Management

  • Security Management Concepts
  • Security Entities with Snowflake
  • Securable Objects, Users & Roles
  • Prevligies and Privilege Groups
  • Snowflake Security Hierarchy
  • Organization, Account, Users, Roles
  • Schema, Tables, Other DB Objects
  • Creating and Using Roles, Users
  • System Defined Roles and Usage
  • Role Hierarchy and Dependency
  • Creating and Working with Users
  • Auditing Users and Password Policy
  • RBAC: Role Based Access Control
  • DAC: Discretionary Access Control

Ch 16: Azure & External Storage

  • Working with Azure Storage
  • Azure Subscription, Resources
  • Create, Use Azure Storage Account
  • Storage Containers, BLOB Data
  • Using SnowSQL with Azure BLOB
  • SAS [Shared Access Signature]
  • Using SAS Key and FILE PATH
  • External Stages in Snowflake
  • File Formats: Creation, Usage
  • Creating & Using External Stages
  • Azure Storage with BLOB
  • COPY INTO Command Usage
  • Listing Stages with Snowflake
  • Snowflake Patterns & RegEx

Ch 5: Time Travel & Transient Tables

  • Time Travel Feature in Snowflake
  • DML Operations and Silent Audits
  • Continuous Data Protection Life Cycle
  • Invoking Time Travel Feature in Snowflake
  • Timestamp, Offset & Query ID Options
  • Time Travel using Offset Feature
  • Time Travel using Query ID Feature
  • Data Recovery using TIMESTAMP
  • Using OFFSET options in Real-world
  • Fail Safe and UNDROP Operations
  • Transient Tables and Real-time Usage
  • Permanent Table and Real-time Usage
  • Restrictions with Permanent Tables
  • Identical Names and Naming Conflicts

Ch 11: Snowflake Transactions

  • Working with Transactions (ACID)
  • Atomicity, Consistency, Isolation
  • Durability and Data Storage Options
  • Transaction Types with Snowflake
  • Implicit, Explicit and Auto Commit
  • BEGIN TRANSACTION & COMMIT
  • DDL Statements and Transactions
  • BEGIN WORK Versus START
  • current_transaction() and Usage
  • to_timestamp_ltz and Usage
  • Failed Transactions with SPs
  • Batches Versus Transactions
  • Transactions with Stored Procedures
  • Scoped and INNER Transactions

Ch 17: SnowPipes & Incremental Loads

  • Snowflake SnowPipes: Incremental Loads & SnowPipe
  • Creating Azure Account For BLOB
  • Creating Container, Generate SAS Key
  • Creating Azure Queue and Event Grid
  • Notification Integration in Snowflake
  • Integrations: Show, Describe, Use
  • Azure Active Directory & IAM
  • Linking Azure AD with Snowflake
  • Enterprise Application, Authentication
  • File Formats with Regular Expr
  • External Data Stages
  • Data Unloading Concepts
  • PUT and GET with SnowSQL
  • Bulk Unloads; Data Preparation & Stages
  • Data Unloading to User Stages
  • Data Unloading to Table Stages

Ch 6: Schemas and Session Context

  • Schemas: Creation, Real-time Usage
  • Permanant and Transient Schemas
  • Managed Schemas in Real-time Usage
  • Verifying and Cloning Snowflake Schemas
  • Invoking Schemas & Cloning Operations
  • ALTER SCHEMA.. IF EXISTS Options
  • Creating, Working with Managed Schema
  • Snowflake Sessions (Workspaces)
  • Session Context: Role and Warehouse
  • Session Context: Database & Schema
  • Working with Fully Qualified Names
  • CTAS: Create Table As Select
  • Data Loading with GUI, SQL Scripts
  • Using Query and History Tab in GUI

Ch 12: Snowflake Streams & Audits

  • Working with Snowflake Streams
  • Stream Object and DML Auditing
  • Snapshot Creation, Offset Options
  • METADATA$ACTION Parameter
  • METADATA$ISUPDATE Parameter
  • METADATA$ROW_ID Parameter
  • Stream Types: Standard Stream
  • Append Only Stream & Usage
  • Insert Only Stream & Usage
  • Data Flow with Snowflake Streams
  • Auditing INSERT, UPDATE, DELETE
  • show streams; desc streams
  • Streams on Transient Tables
  • Time Travel; Using Stream Tables

Ch 18 : REAL-TIME PROJECT

  • Phase 1:
  • Legacy Data Systems
  • Heterogenous Data Platforms
  • File Data Sources
  • Phase 2
  • Desining DWH in Snowflake
  • Incremental Loads
  • Capacity Planning
  • External Data, Integrations
  • SnowPipes and Azure BLOB
  • Phase 3
  • Data Visualizations, Analytics
  • End to End Implementations
  • Project Solution & FAQs
  • Resume & Certification Guidance

Mod 1: Azure Data Factory [ADF], Synapse

Mod 2: Azure Storage & Stream Analytics

Mod 3: Azure Databricks & SparkSQL

Chapter 1: Cloud Basics, Azure SQL DB

  • Cloud Introduction and 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
  • Working with Azure Portal
  • Resource Group Navigations, Options
  • DP 203 Certification Guidance

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 1: Azure Intro, Azure Databricks

  • Azure Databricks : Purpose & Config
  • Need for Azure Databricks (ADB)
  • Azure Databricks Service Creation
  • Azure Databricks Workspace & Usage
  • Spark Cluster Configurations & Capacity
  • Driver Nodes and Worker Nodes in Spark
  • Master Node & Cluster Creation Process
  • Cluster Types and Capacity Options
  • Standard, High Concurrency Clusters
  • Databricks Runtime Service & DBUs
  • Databricks File System (DBFS) and Usage
  • Azure Databricks Workspace Operations
  • ETL and Data Storage Components
  • Spark Concepts and Spark SQL
  • Spark Context and Spark Session
  • DataFrame, Dataset and Real-time Use

Chapter 2: Synapse SQL Pools (DWH)

  • 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 with COPY Table
  • Dynamic Views (DMV) with PDW
  • Data Loads Monitoring, Resource Class

Chapter 2: Azure Migration, 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 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: 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 and Concurrency
  • Creating Linked Services, Datasets
  • Pipeline Trigger, Author and Monitor

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 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: 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, Consistency Check
  • Compression Option, DOP and DOCP
  • ETL Staging Advantages & Performance
  • Staging with Storage Account, Container
  • ADF Pipeline Triggers and Monitoring
  • Polybase For Azure Synapse, Advantages

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 Data Lake Storage Security Options
  • ACL : Access Control Lists & Security
  • Azure BLOB Storage Containers & ACLs
  • Folder Level and File Level Security
  • ACL Permissions: Read, Write & Execute
  • Access Policy: Creation and Realtime Use
  • Permissions: rwacdl; Azure Principals, CORS
  • Comparing IAM and ACLs in Data Lake Store

Chapter 4: Open Data Sources, DeltaLakes

  • Creating Python Notebooks with Databricks
  • Spark Dataframes with Azure OpenDatasets
  • Windows Azure Storage Blob [wasb] Sources
  • Creating Dataframes & Temporary Views
  • Using Print and Display Functions with ADB
  • Big Data Analysis with BLOB Data & Charts
  • Keys, Values, Aggregations, Display Type
  • Databricks Notebooks, Jobs and Stages
  • Azure DeltaLake 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

Chapter 5: OnPremise Data 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 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 5: Databricks Security & Jobs

  • Azure Databricks Security Operations
  • Azure Active Directory (Azure AD)
  • AD Users and RBAC with IAM
  • Owner, Contributor & Reader Roles
  • Workspace Admin Permissions
  • Notebook Permissions and Share Options
  • Shared Notebooks, User Access Options
  • Notebook Operations: Clone & Export
  • Databricks Jobs: Creation Options, Usage
  • Job Limits, Workspace, Concurrency Limits
  • Notebooks with and without Parameters
  • Jobs with Default Parameters, Executions
  • Interactive, Automated Clusters for Jobs
  • Job Schedules and Manual Executions
  • Active Jobs, Recently Run Jobs, Monitoring
  • ADB Jobs with Azure OData Sources, BLOB

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 6: Azure Stream Analytics, IoT

  • Azure Stream 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 Strean 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 6: Databricks @ BLOB, Power BI

  • BLOB Data Access with Databricks
  • Accessing Storage Account, Container
  • Gerate, Use SAS: Shared Access Signature
  • dbutils.fs.mount() with DBFS Store
  • fs.azure.sas.container.strorageaccount
  • spark.read() and DBFS Mounts
  • Scala Transformations, Create Temp View
  • Spark SQL Queries with Temp Views
  • dataframe.write.jdbc() & JVM Properties
  • spark.read.jdbc() with Azure SQL DB
  • Power BI Integration with Databricks
  • Server Host Name, Port and Http Path
  • Cluster Configurations and JDBC
  • User Access Token Generation, Usage
  • Spark ClusterAccess, Power BI Analytics

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 7: IoT Hubs & Event Hubs

  • Azure Stream Analytics For API Data
  • IoT Hubs & IoT Devices, Connection Strings
  • Rasberry 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 App Integration with ASA Jobs

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
  • Spark Notebooks For Dynamic Connections
  • Parameterized Options & Blob Access
  • Data Preparation & Big Data Ingestion
  • Data Extraction and ADLS Storage
  • show(), transformations, wasbs Options
  • Azure SQL Server & Synapse Creations
  • Data Loads with Incremental Changes

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
  • Row Terminator and Compressions
  • T-SQL Queries and Aggregations
  • Aggregation Data Loads in Synapse

Chapter 8: Azure Stream Analytics Security

  • 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
  • Using Azure Key Vaults to secure Resources
  • Azure Storage: Replications and DR Options
  • LRS: Locally Redundant Storage
  • GRS: Globally Redundant Storage
  • ZRS: Zone Redundant Storage
  • Replication Options and Advantages
  • Replication Verification and Modifications
  • Azure Storage Endpoints, Failover Partner

    Real-Time Project

  • ADF Integration, Real-time Project
  • 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()
  • 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
  • Concept wise FAQs, Resume Guidance
  • Project Requirement, Solution, FAQs
  • DP 203 Certification Guidance

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 Resoruce 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)
  • ADF V1 to V2 Migrations, Considerations

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
  • PL 300 Certification Guidance
  • 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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Job-Oriented Real-time Training @ SQL School Training Institute - Trainer :  Mr.Sai Phanindra (17+ Yrs of Exper)