Learn how to use Microsoft Cloud Services for Big Data Engineering effectively.
Types of Data
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29 Mins
: 0
Understanding File Formates
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23 Mins
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Understanding Database
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14 Mins
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OLTP/OLAP
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15 Mins
: 0
Modern Data Warehouse in Azure
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6 Mins
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Understanding Big Data Processing
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29 Mins
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Real-Time Use Case
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7 Mins
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Azure SQL Database Introduction
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26 Mins
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Compare Deployment Options
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13 Mins
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Elastic Pool
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27 Mins
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Azure SQL Security
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28 Mins
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Introduction To Business Continuty
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9 Mins
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Backup and Restore
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18 Mins
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High Availability in Different Tiers
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8 Mins
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Active Geo Replication and Auto Failover Groups
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34 Mins
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Spark Introduction
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53 Mins
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Azure Databricks Introduction
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17 Mins
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Databricks Key Concepts
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22 Mins
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Data Bricks Cluster
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25 Mins
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Notebook Introduction
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8 Mins
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Analyse Data in DBFS
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19 Mins
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Read File from Data Lake
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13 Mins
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Apply Schema
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10 Mins
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Data Cleansing and Transformation -Part1
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23 Mins
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Data Cleansing and Transformation-Part2
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9 Mins
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Explore Data with SQL
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4 Mins
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Enable Unity Catlog for Workspace
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12 Mins
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Introduction to Data Factory
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26 Mins
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Use Copy Data Wizard
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13 Mins
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Copy all Files from Blob to Data Lake
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11 Mins
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Copy and Decompress File from Blob to Data Lake
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8 Mins
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Copy Data from Blob to Azure SQL
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15 Mins
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Connect Data Lake Using Service Principal or Managed Identity
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36 Mins
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Using Self-Hosted Integration Runtime
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19 Mins
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Get Metadata Activity
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7 Mins
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Set Variable Activity
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5 Mins
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Stored Procedure Activity
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17 Mins
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Configure Dynamic Connection
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12 Mins
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For Each and Filter Activity
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23 Mins
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Data Flow
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37 Mins
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Power Query
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24 Mins
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Scheduled Trigger
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10 Mins
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Tumbling Window Trigger
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21 Mins
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Event-Based Trigger
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13 Mins
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Git Integration
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12 Mins
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Introduction to Azure Synapse Analytics
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35 Mins
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Introduction to Dedicated SQL Pool
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23 Mins
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Understanding Distributions
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27 Mins
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Understanding Columnstore Index
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14 Mins
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Polybase and CTAS
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30 Mins
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CETAS
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7 Mins
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Copy Statement
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20 Mins
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Introduction to Serverless Pool
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7 Mins
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Query CSV and Parquet Data
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23 Mins
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Query JSON Data
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9 Mins
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Query Partitioned Data
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9 Mins
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Working With Metadata Objects
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21 Mins
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Introduction to Stream Analytics
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34 Mins
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Introduction To Event Hub
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11 Mins
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Ingesting Data From Event Hub
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40 Mins
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Sending Data To Event Hub
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10 Mins
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Using Reference Input and Windowing Functions
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18 Mins
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CosmosDB Introduction
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21 Mins
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Creating CosmosDB Account
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22 Mins
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Understand CosmosDB Request Units
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15 Mins
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CosmosDB Global Replication and Consistency Levels
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16 Mins
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CosmosDB Partition Key
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14 Mins
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OVERVIEW
The DP-203 : Microsoft Azure Data Engineers assesses your ability to plan and carry out data solutions using Azure services. Data processing, data storage, and data security on the Azure platform are among the subjects covered in this exam. Candidates must show that they can integrate data services, create data solutions that satisfy business needs, and guarantee data security and compliance. By passing DP-203, you can demonstrate that you are an expert in using Azure technologies for data engineering tasks, which makes you a valuable asset in the cloud-based data management field.
COURSE OBJECTIVES
PRE-REQUISITES
WHO CAN DO THIS COURSE
The DP-203 course is suitable for:
TRAINING AT BITC(BestITCourses)
Meet Your Certified Trainer
Mrs. Vandana Soni, a Microsoft Certified Trainer and Azure Data Engineer Associate, has 25 years of IT experience. She excels in Corporate Training, Live Training, and Online Webinars.
She has trained 50,000+ individuals & delivered 50+ corporate trainings. She specializes in SQL Server, Azure Data Engineering, & Data Analytics, providing certification guidance from basics to advanced.
Know more about Vandana Soni - https://www.bestitcourses.com/trainers/Vandanasoni
Follow her on LinkedIn - https://www.linkedin.com/in/vandana-soni-85a29475/
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