Official Learning Partner

Course Highlights

Complete Real-time and Practical Azure Admin Training with Real-time Scenarios. Azure Administrator include implementing, managing, and monitoring identity, governance, storage, compute, and virtual networks in a cloud environment, plus provision, size, monitor, and adjust resources

This Azure Admin Training includes core Azure services, Azure workloads, security, and governance. In addition, this role should have experience using PowerShell, Azure CLI, Azure portal, and Azure Resource Manager templates in addition to Mock Interviews, Resume Guidance, Concept wise Interview FAQs and ONE Real-time Case Study.

Azure DevOps and azure fundamentals video banner

Training Highlights:

Azure Fundamentals
Azure DevOps
DevOps Tools
Azure Boards

Azure Pipelines
Azure Artifacts
Git, Github
Azure AD

DevOps Benefits
DevOps Services
Azure Repos
Azure Testing

DevOps Server
Docker

Course Content

Azure DevOps
Training Course Contents:

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Azure Admin

Develop an Instrumentation Strategy (5-10%)

Design and implement logging

assess and Configure a log framework
design a log aggregation and storage strategy (e.g. Azure storage)
design a log aggregation using Azure Monitor
manage access control to logs (workspace-centric/resource-centric)
integrate crash analytics (App Center Crashes, Crashlytics)

Design and implement telemetry

design and implement distributed tracing
inspect application performance indicators
inspect infrastructure performance indicators
define and measure key metrics (CPU, memory, disk, network)
implement alerts on key metrics (email, SMS, webhooks, Teams/Slack)
integrate user analytics (e.g. Application Insights funnels, Visual Studio App Center, TestFlight, Google Analytics)

Integrate logging and monitoring solutions
configure and integrate container monitoring (Azure Monitor, Prometheus, etc.)

configure and integrate with monitoring tools (Azure Monitor Application Insights, Dynatrace, New Relic, Naggios, Zabbix)
create feedback loop from platform monitoring tools (e.g. Azure Diagnostics VM extensions, Log Analytics agent, Azure Platform Logs, Event Grid)
manage Access control to the monitoring platform

Develop a Site Reliability Engineering (SRE) strategy (5-10%)

Develop an actionable alerting strategy

identify and recommend metrics on which to base alerts
implement alerts using appropriate metrics
implement alerts based on appropriate log messages
implement alerts based on application health checks analyze combinations of metrics
develop communication mechanism to notify users of degraded systems
implement alerts for self-healing activities (e.g. scaling, failovers)

Design a failure prediction strategy

analyze behavior of system with regards to load and failure conditions
calculate when a system will fail under various conditions
measure baseline metrics for system
Leverage Application Insights Smart Detection and Dynamic thresholds in Azure Monitor

Design and implement a health check

analyze system dependencies to determine which dependency should be included in health check
calculate healthy response timeouts based on SLO for the service
design approach for partial health situations
design approach for piecemeal recovery (e.g. to improve recovery time objective strategies)
integrate health check with compute environment
implement different types of health checks (liveness, startup, shutdown)

Develop a security and compliance plan (10-15%)

Design an authentication and authorization strategy

design an access solution (Azure AD Privileged Identity Management (PIM), Azure AD Conditional Access, MFA)
organize the team using Azure AD groups
implement Service Principals and Managed Identity
configure service connections

Design a sensitive information management strategy

evaluate and configure vault solution (Azure Key Vault, Hashicorp Vault)
generate security certificates
design a secrets storage and retrieval strategy (KeyVault secrets, GitHub secrets, Azure Pipelines secrets)
formulate a plan for deploying secret files as part of a release

Develop security and compliance

automate dependencies scanning for security (container scanning, OWASP)
automate dependencies scanning for compliance (licenses: MIT, GPL)
assess and report risks
design a source code compliance solution (e.g. GitHub Code scanning, GitHub Secret scanning, GitHub security, pipeline-based scans, Git hooks, SonarQube, Dependabot, etc.))

Design governance enforcement mechanisms

implement Azure policies to enforce organizational requirements
implement container scanning (e.g. static scanning, malware, crypto mining)
design and implement Azure Container Registry Tasks (eg. Azure Policy)
design break-the-glass strategy for responding to security incidents

Manage source control (10-15%)

Develop a modern source control strategy

integrate/migrate disparate source control systems (e.g. GitHub, Azure Repos)
design authentication strategies
design approach for managing large binary files (e.g. Git LFS)
design approach for cross repository sharing (e.g. Git sub-modules, packages)
implement workflow hooks
design approach for efficient code reviews (e.g. Pull PandaGitHub code review assignments, schedule reminders, Pull Analytics)

Plan and implement branching strategies for the source code

define Pull Requests (PR) guidelines to enforce work item correlation
implement branch merging restrictions (e.g. branch policies, branch protections, manual, etc.)
define branch strategy (e.g. trunk based, feature branch, release branch, GitHub flow)
design and implement a PR workflow (code reviews, approvals)
enforce static code analysis for code-quality consistency on PR

Configure repositories

configure permissions in the source control repository
organize the repository with git-tags
plan for handling oversized repositories
plan for content recovery in all repository states
purge data from source control

Integrate source control with tools

integrate GitHub with DevOps pipelines
integrate GitHub with identity management solutions (Azure AD)
design for GitOps
design for ChatOps
integrate source control artifacts for human consumption (e.g. Git changelog)
integrate GitHub Codespaces

Facilitate communication and collaboration (10-15%)

Communicate deployment and release information with business stakeholders

create dashboards combining boards, pipelines (custom dashboards on Azure DevOps)
design a cost management communication strategy
integrate release pipeline with work item tracking (e.g. AZ DevOps, Jira)
integrate GitHub as repository with Azure Boards
communicate user analytics

Generate DevOps process documentation

design onboarding process for new employees
assess and document external dependencies (e.g. integrations, packages)
assess and document artifacts (version, release notes)

Automate communication with team members

integrate monitoring tools with communication platforms (e.g. Teams, Slack, dashboards)
notify stakeholders about key metrics, alerts, severity using communication platforms (e.g. Email, SMS, Slack, Teams)
integrate build and release with communication platforms (e.g. build fails, release fails)
integrate GitHub pull request approvals via mobile apps

Define and implement continuous integration (20-25%)

Design build automation

integrate the build pipeline with external tools (e.g., Dependency and security scanning,Code coverage)
implement quality gates (e.g. code coverage, internationalization, peer review)
design a testing strategy (e.g. integration, load, fuzz, API, chaos)
integrate multiple tools (e.g. GitHub Actions, Azure Pipeline, Jenkins)

Design a package management strategy

recommend package management tools (e.g. GitHub Packages, Azure Artifacts, Azure Automation Runbooks Gallery, Nuget, Jfrog, Artifactory)
design an Azure Artifacts implementation including linked feeds
design versioning strategy for code assets (e.g. SemVer, date based)
plan for assessing and updating and reporting package dependencies (GitHub

Automated Security Updates, NuKeeper, GreenKeeper)

design a versioning strategy for packages (e.g. SemVer, date based)
design a versioning strategy for deployment artifacts Design an application infrastructure management strategy
assess a configuration management mechanism for application infrastructure
define and enforce desired state configuration for environments

Implement a build strategy

design and implement build agent infrastructure (include cost, tool selection, licenses, maintainability)
develop and implement build trigger rules
develop build pipelines
design build orchestration (products that are composed of multiple builds)
integrate configuration into build process
develop complex build scenarios (e.g. containerized agents, hybrid, GPU)

Maintain build strategy

monitor pipeline health (failure rate, duration, flaky tests)
optimize build (cost, time, performance, reliability)
analyze CI load to determine build agent configuration and capacity

Design a process for standardizing builds across organization

manage self-hosted build agents (VM templates, containerization, etc.)
create reuseable build subsystems (YAML templates, Task Groups, Variable Groups, etc.)

Define and implement a continuous delivery and release management strategy (10-15%)

Develop deployment scripts and templates

recommend a deployment solution (e.g. GitHub Actions, Azure Pipelines, Jenkins, CircleCI, etc.)
design and implement Infrastructure as code (ARM, Terraform, PowerShell, CLI)
develop application deployment process (container, binary, scripts)
develop database deployment process (migrations, data movement, ETL)
integrate configuration management as part of the release process
develop complex deployments (IoT, Azure IoT Edge, mobile, App Center, DR, multiregion, CDN, sovereign cloud, Azure Stack, etc.)

Implement an orchestration automation solution

combine release targets depending on release deliverable (e.g., Infrastructure, code, assets, etc.)
design the release pipeline to ensure reliable order of dependency deployments
organize shared release configurations and process (YAML templates, variable groups, Azure App Configuration)
design and implement release gates and approval processes

Plan the deployment environment strategy

design a release strategy (blue/green, canary, ring)
implement the release strategy (using deployment slots, load balancer configurations, Azure Traffic Manager, feature toggle, etc.)
select the appropriate desired state solution for a deployment environment (PowerShell DSC, Chef, Puppet, etc.)
plan for minimizing downtime during deployments (VIP Swap, Load balancer, rolling deployments, etc.)
design a hotfix path plan for responding to high priority code fixes

Module 1: Azure DevOps Training Content [For Plans A, B, C]

Module I: Azure Funda & DevOps Basics

Ch 1. Azure Fundamentals

Basics of Cloud Computing
Cloud Services: Advantages
Cloud Services: Product Models
Virtualization Concepts in Cloud
Comparing On-Premise with Cloud
DevOps : Introduction, Use
Azure Cloud : Features, Advantages
Azure Cloud : Services & Usage
Azure Cloud : Platform Components
Azure Resoures, Service Types
Azure PaaS, IaaS & SaaS
Azure Account Creation, Resources

Ch 2. Azure Services, Configurations

Azure Registration and Azure Portal
Azure Resources and Azure Services
Azure Resource Types, Resource Groups
Creating Resource Groups in Azure Portal
Resource Groups: Access, Advantages
Cost and Billing Management
Azure Storage Account Creation
Storage Account Types, Replication
Azure BLOB Data Storage Containers
Azure Storage Explorer Tool
Uploads, Imports, SAS and Access Key
Azure File Storage and On-Premise Access

Ch 3. Azure Active Directory, Monitoring

Azure Active Directory Service
Azure AD : Users, Tokens & Passwords
Azure AD : Groups, Members, Owners
Azure AD : App Registrations, Tokens
Service Principals and Real-time Use
Identity & Access Management (IAM)
Azure Monitoring and Metrics
Azure Dashboards and Counters
Customizations and Usage Reports
Azure Alerts and Conditions
Notifications: Push/Email/SMS
Log Analytics and Health Checks

Ch 4. SDLC, Dev & Operations, DevOps

Software Development Life Cycle
SRS Documents and Principles
Design, Planning and Coding
Coding Techniques and Tools
Testing Operations, Issues
UAT, Production Deployment Issues
Need for DevOps Services
Life Cycle Management
Automations and Code Control
DevOps Tools and Techniques
DevOps : Advantages, Benefits
DevOps Engineers: Job Roles

Ch 5. DevOps Tools, Git & GitHub

DevOps Tools & Life Cycle Stages
Continuous Development (CD)
Continuous Integration (CI)
Planning Phase: UML Tools
Code: Visuaal Studio, Git
Build: Maveen and Gradle
Test: Selleinum and Junit
Release: Jenking, Bamboo
Deploy: Puppet, Chef, Ansible
Operate: Visual Studio Options
Monitor: NewRelic, Splunk
Git & GitHub For Code Store

Ch 6. Docker, Kubernetes, AzureDevOps

Introduction to Docker in Azure
Understanding Docker Lifecycle
ACI Containers and Options
Introduction to Kubernetes in Azure
Kubernetes Lifecycle Implementation
Azure Kubernetes Containers, Options
Azure DevOps : Advantages
Azure DevOps: Services
Azure Boards, Azure Repos
Azure Pipelies and Realtime Use
Azure Test Plans and Artifacts
VSTS Versus Azure DevOps

Module II: Azure DevOps Service – 1

Ch 7: Organizations & Projects

Azure DevOps: Implementation Plan
Creating and Using Organizations
Planning and Security Advantages
Region Specifications and Owners
Users and Resource Limits
Azure DevOps – Org Notifications
Azure Projects – Creation, Use
Public and Private Projects
Version Control: Git and TFS
Work Item Process: Agile
Basic, CMM and Scrum Options
Security, Teams, Dashboards

Ch 8: Azure Boards

Azure Boards – Creation, Use
Work Item – Fields & Sprints
Kanban Boards, Item Tracking
Backlogs and Code Testing
Bugs and Feature Requests
Team Dashboards, Monitoring
Azure Boards with Agile Process
Azure Boards For CMMI Procces
Azure Boards For Scrum Procces
Change Column & Queries
Style Rules and Highlight Cards
Color Tag & Work Item Cards

Ch 9: Azure Repos

Azure Repository (Repo), Storage
Distributed Versus Centralized
Azure DevOps Repos: Cloning
Commit, Push and Pull Options
Branch & Branch Policies
Fork, Git and WorkFlow
Git Versus TFVC, Customizations
Public Projects and Pull Requests
Notification Options in Repos
Team Foundation Version Control
Git and TFS Projects in DevOps
Azure Repos with Slack

Ch 10: Azure Pipelines For CI/CD – 1

Azure Pipelines – Architecture, Creation
Azure Pipeline Creation Ecosystem
Continious Integration (CI)
Continious Development (CD)
Build Pipeline in Azure DevOps
Key Concepts, Real-time Use
Creating Pull and Push Requests
Release Pipelines – Creation, Use
Multi Stage Release Pipelines
New Branch Options with Pipelines
Classic Release Pipelines
Classic Editor – Pipeline Creation

Ch 11: Azure Pipelines For CI/CD – 2

Continous Integration Pipelines
PreDeployments in Azure devOps
WorkTeam Correlation Options
Azure Pipelines – Customizations
GitHub with Azure Active Directory
GitBub with DevOps Integration
Pipeline Creation Comparisions
AzurePipelines for YAML
Agent, Approvals and Artifacts
Caching, Conditions and Jobs
Classic Builds and Class Release
Dependancies, Job Deployments

Ch 12: Azure Testing & Artefacts

Azure Testing Options in DevOps
Manual Testing in Kanban
Manual Testing in Test Manager
UAT and Test Tracking
Test Case Explorer in DevOps
Stakeholder Feedback
Azure Artifacts and Feeds
Single Feeds & Multi Feeds
Nuget, npm, Maven with DevOps
Versions and Compatability
Retention Polocies with Artifacts
Maven Central Upstream Sources

Azure DevOps Service – 2
Az DevOps Server

Ch 13: Azure Functions, App Service, Alerts

Azure Functions and Automations
Azure Event Notifications, Audits
Azure App Services & Webapps
Build, Deployment and Scaling
Azure App Service Migrations
Azure Apps Versus DevOps
Azure Monitoring and Alerts
Notification Options in Azure
Alert Management, Operators
Creating, Managing Alert Rules
RBAC , Continuous Monitoring
Smart Groups and Performance

Ch 14: Azure DevOps Resources in Portal

Azure DevOps Services From Portal
Application Insights and Logs
Log Analytics and Storage Account
API Management Services
API Connections in Azure
Azure DevOps Organizations
DevTest Labs From Azure Portal
Build Apps with Azure DevOps
Azure Pipelines and Samples
Plan and Buld Tasks in DevOps
Setup Azure DevOps Org Account
Create & Publish Azure Pipelines

Ch 15: Azure DevOps Strarter, App Insights

Azure DevOps Starter Deployments
Migrations from Git Repository
Continuous Integration (CI)
Continuous Delivery (CD)
Item Pipeline and Workflow
Azure DevOps Pipelines
DevOps Starter, Github Integration
DevOps Starter, DevOps Integration
DevOps Starter Vs Azure DevOps
Github Actions & Azure DevOps
Azure DevOps to Azure VM
Examine CI and CD Pipelines

Ch 16: Power Shell & Azure DevOps

Azure Power Shell and DevOps
Power Shell Installations
Power Shell in Azure Portal
Creating Resources in Portal
Creating Pipelines in PowerShell
YAML Snippet and Arguments
Writing Sample Apps, Builds
Writing Warnings and Errors
Powershell with Multiple Args
Service Fabric Manifests
Publish Test Results in DevOps
Run Functional Test Results

Ch 17: DevOps Server – Configurations

Azure DevOps Server – Advantages
On-Premise Configurations for Server
Code Share, Track Work and Shipping
Visual Studio Team Fundation Server
Azure DevOps Server – Installation
Criterion for Azure DevOps Server
SQL Server Installation for DevOps
Database Engine, FullText Search
Services and Service Account, Agent
SSMS Tools Installation for Access
Server Connections, Authentication
Database Creation using SSMS

Ch 18: DevOps Server & Visual Tools

Privacy Advantages with DevOps Server
XML Definition Files and Options
Build Server Configurations
Content Version and Projects
General Administration Tasks
Server Level Administration Tasks
Adding Users to Projects
Grant and Restrict Permissions
Set Code & Test Properties
Area and Iteration Paths
Adding Teams and Scaling
Billing Items & Monitoring

Module 2: Azure Data Engineer Training Content [For Plans B, C]

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;

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

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 Usage
Big Data Storage and Data Analytics
Column Store Data in Azure Synapse
Automated Tuning and Security
Access, Pause/Resume with Synapse
SSMS & ADS Tools Connections

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 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 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 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 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 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 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 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 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

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

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 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 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 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 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 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 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 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 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 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

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

Ch 21: Azure Databricks Configurations

Azure Databricks: Spark Based Analytics
ADB Workspace, Data Science Analytics
Workspace Options, Databricks Runtime
Serverless Storage, ETL and Analytics
Databricks File System (DBFS) Store
Notebooks: SQL, Spark, Python, Scala
Apache Spark Eco System & Integrations
Azure Databricks Deployment Options
Databricks Units (DBU) & Workspace
Network Security Group and Storage
Databricks Clusters: Architecture
Standard & High Concurrency Clusters
Databricks Pools, Capacity: CPU, Memory
Autopilot Options; Worker & Driver Nodes

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 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 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 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 Monitoring with ADB
Databricks with Power BI Desktop
Spark Connectors in Power BI
Access Token from Azure Databricks
Spark Cluster Connection: Nodes, Pools
Server Host Name, Ports and HTTP
Power BI Reports with Databricks

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
Azure Cosmos DB Accounts in Portal
Azure Cosmos DB with Data Explorer
Creating Containers & JSON Documents
Data Store and Data Access (Querying)
Scaling Options for Cosmos DB & Cautions

Ch 27: Azure Cosmos DB Queries Level 1

Hierarchial JSON Documents in 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 28: Azure Cosmos DB Queries Level 2

Data Import Tool: Installation, 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 Execution using Cosmos DB Scripts
Dynamic Calculation & Reporting Options

Ch 29: Azure Notebooks, Azure Functions

Azure Notebooks, Serverles Deployment
Azure Cosmos Notebooks, 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 30: Azure Cosmos Admin, Power BI

Azure Cosmos DB: Conistency Levels
Bounded Staleness and Consistent Prefix
Eventual & Synchronizations with Cosmos
Azure Cosmos: Backup Retention, Restores
IAM: Identity Access Management, Azure AD
Owner Role, Contributor & Reader Roles
Cosmos Backup Operator, Account Reader
Global Distribution Strategies, BCDR
Data Replication and High Availability
Multi Region Writes and Data Access
Azure Cosmos Database Cost Calculations
Availability Zones, Automated Failvoer
Azure Cosmos Database Management
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 with Azure Synapse and Azure Cosmos Database; Big Data Analytics using Azure Databricks and Azure Stream Analytics. This Real-time Project also includes End User Reporting with Power BI. Additionally includes Resume Support and DP 200, DP 201 Certification Guidance.

Module 3: Power BI Training Content [For Plan C]

Part 1: Power BI Report Design

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 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 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 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 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 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

Part 2: ETL, Data Modeling, DAX

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 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 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 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 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 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

Part 3: Power BI Cloud, Admin

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 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 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 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 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 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 Requirements, Analysis
Cloud and Report Server
Project FAQs and Solutions

Azure DevOps Training Plans

	Plan A 1. Azure DevOps	Plan B Azure DevOps Azure Data Engineer	Plan C Azure DevOps Power BI, Azure Data Engineer
Course Duration	4 Weeks	10 Weeks	14 Weeks
Azure DevOps Benefits	✔	✔	✔
SDLC, Dev & Operations, DevOps	✔	✔	✔
DevOps Tools, Git & GitHub	✔	✔	✔
Docker, Kubernetes, AzureDevOps	✔	✔	✔
Azure Boards, Azure Repos	✔	✔	✔
Azure Testing, Azure Artifacts	✔	✔	✔
Azure Pipelines (CI, CD)	✔	✔	✔
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	✖	✔	✔
Power B: Report Design, Visuals	✖	✖	✔
Power BI: M Lang, DX for ETL	✖	✖	✔
Power BI: Report Server, Admin	✖	✖	✔
Total Course Fee*	INR 12000USD 163	INR 35000USD 473	INR 43000USD 582

Azure DevOps Training Schedules

S No	Time (IST, Mon - Fri)	Start Date	Register
1	6 AM - 7:30 AM (W)	Coming Soon	Register

CURRICULUM

SQL SCHOOL

24x7 LIVE Online Server (Lab) with Real-time Databases.
Course includes ONE Real-time Project.

Technical FAQs

Who is SQL School? How far you have been in the training services ?

SQL School is a registered training institute, established in February 2008 at Hyderabad, India. We offer Real-time trainings and projects including Job Support exclusively on Microsoft SQL Server, T-SQL, SQL Server DBA and MSBI (SSIS, SSAS, SSRS) Courses. All our training services are completely practical and real-time.CREDITS of SQL School Training Center

We are Microsoft Partner. ID# 4338151
ISO Certified Training Center
Completely dedicated to Microsoft SQL Server
All trainings delivered by our Certified Trainers only
One of the few institutes consistently delivering the trainings for more than 8+ Years online as inhouse
Real-time projects in
- Healthcare
- Banking
- Insurance
- Retail Sales
- Telecom
- ECommerce

I registered for the Demo but did not get any response?

Make sure you provide all the required information. Upon Approval, you should be receiving an email containing the information on how to join for the demo session. Approval process usually takes minutes to few hours. Please do monitor your spam emails also.

Why you need our Contact Number and Full Name for Demo/Training Registration?

This is to make sure we are connected to the authenticated / trusted attendees as we need to share our Bank Details / Other Payment Information once you are happy with our Training Procedure and demo session. Your contact information is maintained completely confidential as per our Privacy Policy. Payment Receipt(s) and Course Completion Certificate(s) would be furnished with the same details.

What is the Training Registration & Confirmation Process?

Upon submitting demo registration form and attending LIVE demo session, we need to receive your email confirmation on joining for the training. Only then, payment details would be sent and slot would be allocated subject to availability of seats. We have the required tools for ensuring interactivity and quality of our services.

Please Note: Slot Confirmation Subject to Availability Of Seats.

Will you provide the Software required for the Training and Practice?

Yes, during the free demo session itself.

How am I assured quality of the services?

We have been providing the Trainings – Online, Video and Classroom for the last EIGHT years – effectively and efficiently for more than 100000 (1 lakh) students and professionals across USA, India, UK, Australia and other countries. We are dedicated to offer realtime and practical project oriented trainings exclusively on SQL Server and related technologies. We do provide 24×7 Lab and Assistance with Job Support – even aftrer the course! To make sure you are gaining confidence on our trainings, participans are requested to attend for a free LIVE demo based on the schedules posted @ Register. Alternatively, participants may request for video demo by mailing us to contact@sqlschool.com Registration process to take place once you are happy with the demo session. Further, payments accepted in installments (via Paypal / Online Banking) to ensure trusted services from SQL School™

YES, We use Enterprise Edition Evaluation Editions (Full Version with complete feature support valid for SIX months) for our trainings. Software and Installation Guidance would be provided for T-SQL, SQL DBA and MSBI / DW courses.

Why Choose SQL School

100% Real-Time and Practical
ISO 9001:2008 Certified
Concept wise FAQs
TWO Real-time Case Studies, One Project
Weekly Mock Interviews
24/7 LIVE Server Access
Realtime Project FAQs
Course Completion Certificate
Placement Assistance
Job Support
Realtime Project Solution
MS Certification Guidance

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