AZURE - Vinay Tech House

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Azure BI

This course covers Azure Clous, Blob Storage, Data Lake, Data Factory, Data Bricks, SSIS Integration, and SSAS Tabular Cubes with Detailed Materials, Software Installation and Videos. One REAL-TIME PROJECT and CASE STUDIES will give more understanding about BI Projects in Azure.

Classroom | Online | Fast Track | Self Paced

Course Highlights

Live Projects

Placement Assistance

Expert Trainers

Premium Training

Live Video Share

Real-Time Case Studies

Frequently Asked Questions

What is Azure BI and What are it's uses?

Azure is a vast cloud platform with multiple services (SaaS, PaaS, SaaS), if we perform Business Intelligence and Analytical operations in Azure, then it is Azure BI.

It is not a separate tool or application or service available in the market.

Is Azure BI easy to learn?

It is easy to learn because of simple cloud service, processes and many low code interfaces.

Does Azure BI have a market?

Yes, Microsoft is the leader in Analytics and Business Intelligence since 16 years. It is providing its wonderful support to the current cutting edge processes and technologies by its monthly updates. And also On-Premise MSBI and Cloud Power BI providing other BI supportive services beside Azure BI. Kindly visit the following links to know more about the Azure BI Market & Leadership - https://powerbi.microsoft.com/en-us/blog/microsoft-named-a-leader-in-the-2022-gartner-magic-quadrant-for-analytics-and-bi-platforms/ - https://powerbi.microsoft.com/en-my/blog/microsoft-named-a-leader-in-the-forrester-wave-augmented-bi-platforms-q3-2021/

What if I miss a training session?

No need to worry, daily videos are in the class room folder and materials in the materials folder. You can watch and practice and also reach out to the trainer for queries.

What type of study materials and videos we will get and how long they are available?

You will get all materials after a week of your joining which you can download and use. Daily live class recordings will be placed in a folder and you will have access for maximum 12 months. Lab practice documents and required Power BI credentials provided for practice till one year.

Quick Enquiry

Why Join Vinay Tech

In-Depth Curriculum

Our educational program aims to comprehensively cover all & important points & aspects of the subject

Course Specialized Trainers

Our Trainers are high experienced industry experts with their teaching methods designed for their particular course

10+ Years of Experience

We’ve come a long way teaching from hundreds to thousands, so we use our experience in guiding students in the right path

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Vinay Tech House is prefered by many students as their favourite, rating as the best in teaching

Curriculum

Mandatory Topic 1: Azure, Azure BI, Cloud, Types and Understanding

Azure BI Demo content

Data, Data Availability storage areas [File stream, Database]
Data warehouse, BI definitions and layers]
Cloud storages and cloud components
Azure & BI existence in IT, Product services
Microsoft Azure vs AWS vs GCP
Azure BI Features, Cloud BI
Azure BI Tools and Components
Azure Architecture & Services
On-Premises vs. Cloud computing [Azure]
Azure BI Opportunities and Support
Legacy vs. Modern BI tools
Azure BI components History & releases
Installation process and challenges
Azure accounts creation & practice

Cloud Fundamentals and Understanding

Data warehouse, Data Mart and differences
Types of data marts and real-time usage
ODS, Stage, EDW, and DW definitions
Data Lake and Blob Storages
DWH Life Cycles
DWH Approaches (INMON and KIMBALL)
Data Granularity, Data movement stages

Mandatory Topic 2: Data Warehouse and Data Model Understanding

Data warehouse [Modern] Fundamentals

Data warehouse, Data Mart and differences
Modern Data Warehouse and Storages
Types of data marts and real-time usage
ODS, Stage, EDW, and DW definitions
Data Lake and Blob Storages
DWH Life Cycles
DWH Approaches (INMON and KIMBALL)
Data Granularity, Data movement stages

[Theory and Complete Practical]

Dimension, Dimension Table & types
Fact, Fact Table & measures types
Fact less fact table
Schemas (Star, Snow Flake, Galaxy & Hybrid)
Surrogate key and usages in real time
Business, Conceptual, Logical, Physical Data Models
1:1, 1: M, M: M relationships
Single and Bidirectional relationships
Cross filtering relationship
Role Playing real-time usage
Surrogate key live usages with practical

Topic 3: Azure Resources, Resource Groups, Manager, and Virtual Machine

Resources, Groups & VM

How to Create Resources and Resource Groups in Microsoft Azure
Azure Resource Manager vs. Classic deployment
How to create Virtual Machine

Topic 4: Azure SQL Database, On-Premise Databases, Azure Data Studio

Azure SQL Database, On-Premise Databases, Azure Data Studio

What is Azure SQL Database
SQL Server Vs SQL Database
Azure Data Studio and SSMS
Different deployments of SQL in Azure
How to Create Azure SQL Server
How to Create Database in Azure SQL Server
How to Query Azure SQL Server from On-premises SSMS and Cloud
What is Polybase in Azure SQL
External Tables understanding
How to Load Data from On-premises to Cloud SQL using data factory
Migration of Existing Data from on premises to SQL Azure
SQL Data Mover Practice
Generating reporting using SQL Database

Topic 5: Azure Data Warehouse

Microsoft Azure Data Warehouse

What is Warehouse and Warehouses available
What is Azure Data Warehouse
Creating Azure Data Warehouse
Querying Data from Azure DWH
Generating report and dashboard using PowerBI Visualization tool

Topic 6: Azure Data Factory

ADF

Azure Data Factory [ADF] vs SQL Server Integration Services [SSIS]
What is Azure Data Factory
When to use ADF
Creating Linked Services
Creating Datasets
Creating Pipeline with Copy Activity
Creating Pipeline from Template
Querying Data from Azure Data Warehouse
Monitoring Pipeline
Auditing and Manage
Deployments
Integration Services Runtime

Integration Runtime (IR)

SSIS Integration Services Runtime
Azure Integration Services Runtime
WConfiguring Integration Services Runtime
Querying Data from Azure Data

Components of Azure Data Factory [ADF]

Linked Services
Data Sets
Transformations
Pipelines

Various Types of Activities

Stored procedure
Maintaining Metadata(Logging)
Error handling and Logging error records
Lookup
Get Metadata
Set Variable
Append variable
Execute Pipeline
Execute SSIS Packagee
Delete
Wait

Data Flow Activity Transformation

Source
Sink
Filter
Select
Conditional Split
Derived Column
Join
Lookup
Union
Aggregat
Exists
Surrogate key
Pivot
UnPivot
Sort

Iterations and Conditions

For Eache
If Condition
Until
Switch
Filter

Incremental ETL Process using ADF

Azure Automation Account
Run Book in Azure and execute Power shell scripts using runbook
Logic Apps in Azure and usage
Web Activity
How to Deploy Data Factory Pipelines DEV, Test, Prod environment
Version Control and Code Repository in Git Hub
Debugging and Monitoring Pipelines
Error handling and Logging error records
Lift and Shift SSIS packages in to Azure Data Factory

Security

Security the Data Credentials
Data Encryption in Transit
Storing Credentials in Azure Key Vault

Case Study Practice on Azure

Moving data from Blob to Blob
Moving data from Blob to Azure SQL Server
Moving data from SQL Server to Blob
Moving data from ADLS to Azure SQL Server
Moving data from ADLS to ADL
Configure different Types of Integration Runtimes
Azure Integration runtime
Azure Self Hosted Integration Runtimee/li>
SSIS Integration runtime
Moving Data from Blob to On Premise SQL Server
Moving Data from On Premise SQL Server To Azure SQL
Moving Data from On Premise files to Azure SQL Servere
Moving Data from On Premise files to ADLS and to Azure SQL Server
Load data from Multiple tables into SQL Server using dynamic expressions and schema creation scripts
Load data from Multiple Files using SQL Server dynamic expressions and schema creation scripts
Use dynamic parameters within the pipeline
Trigger a pipeline using another pipeline
Different ways to deploy Azure resources from one resource group to another resource group
Deploy SSIS packages to ADF and Schedule
Query Azure Data lake using U-SQL
Deploy Analysis services cube to Azure
Create and Query Azure Databricks notebooks using Python
Version Control and Code Repository in Git Hub (check in and check out)
Data Lake Analytics
Azure HD-insight
U-SQL
Basics of Data bricks using python
Basics of Power BI with Azure
Creating Virtual Machines (VM's) with Windows and Unix Operating System
Azure Synapse Analytics

Topic 7: Polybase

POLYBASE

Creating Master Key
Creating Scoped Credential
Creating External Data Source
Creating External File Format
Creating External Table

Topic 8: Datalake

Data Lake

What is Data Lake
How to store Data into data lake
How to store Data into data lake
Introduction to Azure Data Lake U-SQL Batch Job
Data Lake Analytics
What is HD-insight
U SQL Detailed Description

Topic 9: Databricks

DataBricks

What is Databricks
Configure data bricks
Read data from data bricks by creating clusters

Topic 10: Azure Event Hub & Real-Time Analytics

Azure Event Hub & Real Time Analytics

What is Azure Event Hub
How to configure Event Hub
Perform Realtime analytics on Event Hub Data

Topic 11: Azure Analysis Services

ALYSIS SERVICES –TABULAR MODEL

Workspace Database, Workspace Server, Direct Query, Backup to disk
Installation steps, error mechanisms Creating a tabular model and setting model
Data to the model, renaming tables, filtering columns
Rename Columns
Monitoring relationships, Providing relationships
Create Hierarchies
Create partitions
Create perspectives
Create Roles
Create KPIs
Deployment

Projects Covered

Banking project

We Do Cover Microsoft Azure Project In Our Training That Helps You Give Real Time Experience.

TeleCommunication Project

This project helps you get real-time experience into the workflow

Interested in a Free demo? Want to learn more?

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