What will I learn in this Microsoft Azure Data Engineer Certification?
This course will prepare you for exams DP-200 for implementing and designing Azure data solutions, enabling you to design and perform data management, monitoring, security and privacy using the complete Azure data services stack. Further, you will learn the below list of topics:
1. Implement Azure Data Solution (DP 200)
- Implementing a data storage solution
- Managing and developing data processing
- Monitoring and optimizing data solutions
Further, candidates who design analytics solutions and build operationalized solutions on Azure and who are familiar with the features and capabilities of batch data processing, real-time processing, and operationalization technologies, etc., can also opt for this Azure Data Engineering training course.
Why should I learn Azure Stream Analytics in this DP-200 certification?
Using Azure Stream Analytics, you can manage real-time event processing applications by scaling it. It promotes greater performance through partitioning, so complicated queries can be parallelized and run on many stream nodes.
Will I learn Azure Data bricks in this Azure Data Engineering training?
With Azure Databricks, you can get the most advanced version of Apache Spark, which will enable you to seamlessly integrate it with the open-sourced libraries. Also, with Azure’s inherent scalability that surpasses every other cloud services, you can easily update the clusters in the Apache Spark.
What is Azure Cosmos DB? Why is it important for getting certification?
Azure Cosmos DB leverages the Jupiter notebooks and Apache Spark to reduce the time to insights by collecting and serving data and performing analysis on local database copies in Azure regions. In this certification, you will cover this topic in detail.
Does Azure Data Engineering training in Edutech Skills cover Azure SQL Database?
Yes, Azure SQL Database is included in this DP-200 certification course.
Who should take up this best Azure Data Factory training course?
This Microsoft Azure Data Factory certification is ideal for candidates who are looking to start their career or already working in the following roles:
- Data Engineers
- Data Architects
- Data Scientists
- Data Analysts
What are the prerequisites for taking up this best Azure Data Factory training online?
Relevant work experience in Data Engineering issues with Azure SQL Data Warehouse, Azure Data Lake, Azure Data Factory, and Azure Stream Analytics should be needed to sign up for this Azure Data Engineer certification training.
Why should I learn Azure Data Engineer topics?
Azure data engineer enables companies to convert all their big data from storage systems, relational & non-relational databases into data-driven workflows. This helps them put up concrete strategies, accomplish goals, and improve the market value of the data they own! For this, they require certified professionals.
In the United States, the average salary for a newbie in this position is about US$85,000, and in India, it is around â‚¹700,000 (rough estimate). In addition, experienced candidates with recognized DP-200 certification can earn up to US$120,000 in the United States and up to â‚¹1,500,000 in India!
Why should I go for Edutech Skills Azure Data Factory online training?
Today, every company is moving towards cloud computing to meet growing customer expectations and gain a competitive advantage. Microsoft Azure is growing at an unprecedented rate. Therefore, there is an urgent need for Azure certified management professionals.
Edutech Skills Azure certification training (DP-200 certification) gives you hands-on experience using Azure services, storage, servers, and more. You will work on managing virtual machines, protecting and managing identities. After you get certified, you can apply for the best jobs at top salaries.
Module 01 – Non-Relational Data Stores and Azure Data Lake Storage
1.1 Document data stores
1.2 Columnar data stores
1.3 Key/value data stores
1.4 Graph data stores
1.5 Time series data stores
1.6 Object data stores
1.7 External index
1.8 Why NoSQL or Non-Relational DB?
1.9 When to Choose NoSQL or Non-Relational DB?
- Best Uses
1.10 Azure Data Lake Storage
- Azure Data Lake-Key Components
- How it stores data?
- Azure Data Lake Storage Gen2
- Why Data Lake?
- Data Lake Architecture
Module 02 – Data Lake and Azure Cosmos DB
2.1 Data Lake Key Concepts
2.2 Azure Cosmos DB
2.3 Why Azure Cosmos DB?
2.4 Azure Blob Storage
2.5 Why Azure Blob Storage?
2.6 Data Partitioning
- Horizontal partitioning
- Vertical partitioning
- Functional partitioning
2.7 Why Partitioning Data?
2.8 Consistency Levels in AzureCosmos DB
- Semantics of the five-consistency level
1. Load Data fromAmazonS3 to ADLS Gen2 with Data Factory
2. Working with Azure Cosmos DB
Module 03 – Relational Data Stores
3.1 Introduction to Relational Data Stores
3.2 Azure SQL Database
- Deployment Models
- Service Tiers
1. Create a Single Database Using Azure Portal
2. Create a managed instance
3. Create an elastic pool
3.3 Why SQL Database Elastic Pool?
1. Create a SQL virtual machine
2. Configure active geo-replication for Azure SQL Database in the Azure portal and initiate failover.
Module 04 – Why Azure SQL?
4.1 Azure SQL Security Capabilities
4.2 High-Availability and Azure SQL Database
- Standard Availability Model
- Premium Availability Model
4.3 Azure Database for MySQL
1. Design an Azure Database for MySQL database using the Azure portal
2. Connect using MySQL Workbench
4.4 Azure Database for PostgreSQL
1. Design an Azure Database for PostgreSQL – Single Server
4.5 Azure Database For MariaDB
1. Create an Azure Database for MariaDB server by using the Azure portal
4.6 What is PolyBase?
- Why PolyBase?
4.7 What is Azure Synapse Analytics (formerly SQL DW)?
- SQL Analytics and SQL pool in Azure Synapse
- Key component of a big data solution
- SQL Analytics MPP architecture components
1. Import Data From Blob Storage to Azure Synapse Analytics by Using PolyBase
Module 05 – Azure Batch
5.1 What is Azure Batch?
5.2 Intrinsically Parallel Workloads
5.3 Tightly Coupled Workloads
5.4 Additional Batch Capabilities
5.5 Working of Azure Batch
1. Run a batch job using Azure Portal
2. Parallel File Processing with Azure Bath using the .NET API
3. Render a Blender Scene using Batch Explorer
4. Parallel R Simulation with Azure Batch
Module 06 – Azure Data Factory
6.1 Flow Process of Data Factory
6.2 Why Azure Data Factory
6.3 Integration Runtime in Azure Data Factory
6.4 Mapping Data Flows
1. Transform data using Mapping data flows
Module 07 – Azure Data Bricks
7.1 What is Azure Data bricks?
7.2 Azure Spark-based Analytics Platform
7.3 Apache Spark in Azure Data bricks
1. Run a Spark Job on Azure Data bricks using the Azure portal
2. ETL Operation by using Azure Data bricks
3. Stream data into Azure Data bricks using Event Hubs
Module 08 – Azure Stream Analytics
8.1 Working of Stream Analytics
8.2 Key capabilities and benefits
1. Analyse phone call data with stream analytics and visualize results in Power BI dashboard
8.3 Stream Analytics Windowing Functions
- Tumbling window
- Hopping Window
- Sliding Window
- Session Window
Module 09 – Monitoring & Security
9.1 What is Azure Monitor?
- Metrics Vs Logs
9.2 What data does Azure Monitor collect?
9.3 What can you Monitor?
- Insights and Core Solutions
9.4 Alerts in Azure
- Flow of Alerts
- Key Attributes of an Alert Rule
- What can you set alert on?
- Manage alerts
- Alert States
- How to create an alert?
1. Create, View, and Manage Metric alerts using Azure Monitor
2. Monitor your Azure Data Factory Pipelines proactively with Alerts
9.5 Azure Security Logging & Auditing
- Types of Logs in Azure
- Azure SQL Database Auditing
- Server-level vs. Database-level Auditing Policy
1. Azure SQL Database Auditing