Exam DP-700: Fabric Data Engineer Associate - Ultimate Guide | Udemy
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Multiple Concept & hands-on Lab on Fabric Spark Pool, PySpark, Version Control, Security, Governance, Eventstream, KQL

What you'll learn
Official exam topics with CONCEPT and Hands-On Lab/DEMO to pass DP-700 Exam; topics includes
How to configure Spark workspace settings in Fabric
How to configure security and governance in Fabric
How to transform data by using PySpark, KQL (Kusto Query Language), SQL in Fabric
How to configure version control in Fabric
How to create and configure deployment pipelines in Fabric
How to design and implement loading patterns
How to optimize a lakehouse table
How to ingest data by using pipelines
and many others concept and demo session mentioned in description.

This course covers official exam syllabus and Study Guide for Exam DP-700: Implementing Data Engineering Solutions Using Microsoft Fabric; For exam topics, it contains concept class followed by related hands-on Lab/demo session immediately to visualize how to use or implement it for effective learning..

For each of the important topic for Exam DP-700, there are Multiple Concept & hands-on Lab/demo session.

Important topic can be : Fabric Spark Pool, PySpark, Version Control, Security, Governance, Eventstream, KQL (Kusto Query Language)

IMPORTANT NOTE: As per Official update from Microsoft, "Microsoft Certified: Azure Data Engineer Associate Certification and its related Exam DP-203: Data Engineering on Microsoft Azure will all be retired on March 31, 2025."

So Exam DP-700 & Certification is VERY IMPORTANT as it is future of  Data Engineering certification from Microsoft: DP-700: Microsoft Fabric Data Engineer Associate

This EXAM DP-700 contains 3 sections having equal priority:

Implement and manage an analytics solution (30-35%)

Ingest and transform data (30-35%)

Monitor and optimize an analytics solution (30-35%)

and each of these section contains multiple subsection and each subsection contains several topics.

What you will learn from this course?

This course will help you to understand concept of each topic and how to use or implement required Fabric item in project. Hence it will help only to pass DP-700 exam & become Microsoft Certified: Fabric Data Engineer Associate but also to become good Data Engineer in Microsoft Fabric to continue in Data Engineering career.

For Configure Spark workspace settings:

Learn concept and fundamentals/Architecture of Spark Pool in fabric along with Hands-on lab/demo session -

What is Starter Pool ?

How to modify Starter Pool in Fabric and how its related Fabric settings impacts Starter Pool?

What is custom Spark Pool?

How to create custom Spark pool in Fabric and how its related settings impacts custom Spark pool

What is Environment and what are their features and related settings that affects these.

How to create Environment and how its related settings impacts compute configuration of Environment.

What is the impact when these pool/environment are made as default pool in workspace.

For Configure security and governance in Fabric, you will learn concept using diagram on the different data security layers-

What is workspace-level access controls? Overview & Concept

How to implement workspace-level access controls in Fabric through Hands on Lab/Demo.

What is item-level  access controls? Overview & Concept

How to implement item-level access controls in Fabric through Hands on Lab/Demo.

What is file-level  access controls? Overview & Concept

How to implement file-level access controls in Fabric through Hands on Lab/Demo.

What is object-level  access controls? Overview & Concept

How to implement object-level access controls in Fabric through Hands on Lab/Demo.

What is row-level  access controls? Overview & Concept - Row Level Security (RLS)

How to implement row-level access controls in Fabric through Hands on Lab/Demo.

What is column-level  access controls? Overview & Concept - Column Level Security (CLS)

How to implement column-level access controls in Fabric through Hands on Lab/Demo.

What is dynamic data masking in Fabric? Overview & Concept

How to implement dynamic data masking in Fabric through Hands on Lab/Demo.

For Transform data by using KQL (Ingest and transform batch data - Part 5) , through hands-on lab/demo you will learn

KQL Fundamentals: Query Operator & | Pipe

KQL Fundamentals & Hands on Lab: Query Operator - Project , count,  getschema

How to translate SQL query to KQL Query

How to find relevant data using  distinct, take operator, Let statement in KQL

How to find relevant data using Filter/Where in KQL

How to find relevant data using  Case (like if/then/elseif ) in KQL

How to use KQL Search

How to implement sorting records using  Sort operator

How to returns  first N rows using  top operator in KQL

How to Create Columns using  Extend operator in KQL

How to Keep/Remove/Reorder Columns using KQL Project operators  - project, project-away , project-keep,project-reorder, project-rename

KQL join & best performance

How to implement left right outer, Left semi join,  Left anti join, Right semi join, Right anti join,full outer join in KQL

How to use summarize operator to perform Aggregation in KQL

How to perform Aggregation using KQL Aggregation  functions Count() ,Countif(),  sum() , sumif(), avg(), avgif() ,max(), maxif() ,min(), minif()

How to perform KQL Aggregation (Group and aggregate data) - summarize by (Group and aggregate data:) - single aggregation, multiple aggregation (GROUP BY)

For Transform data by using PySpark (Ingest and transform batch data - Part 3), through hands-on lab/demo you will learn

How to use or  implement select take using PySpark in Fabric

How to implement  Filter/Where transformation PySpark  to clean data

How to implement  Drop,  distinct, printschema using PySpark

How to implement  Sort()/OrderBy() to sort records using PySpark

How to implement  WithColumn,  ColumnRenamed transformation using PySpark

How to implement  joins using PySpark

How to implement  Aggregations using PySpark

How to implement  Group and aggregate data using PySpark

For Process data by using eventstreams (Ingest and transform streaming data) , through hands-on lab/demo you will learn

How to perform Manage fields transformation in eventstreams

How to perform filter transformation in eventstreams

How to perform aggregation transformation in eventstreams

How to perform group by transformation using tumbling window in eventstreams

How to perform group by transformation using hopping window in eventstreams

How to perform group by transformation using sliding window in eventstreams

How to perform Expand transformation in eventstreams

How to perform union transformation in eventstreams

How to perform join transformation in eventstreams

For Configure version control, you will learn

What is Version control? Concept & Integration Process

What are related Fabric/Git permission and settings (and Tenant settings  ) required to configure version control in Fabric?

Hands-on Lab/Demo:  How to set up Azure Repo that to be used as part of version control configuration.

Hands-on Lab/Demo: How to configure version control/ Git integration with Azure Repo from Fabric workspace

For Implement database projects, you will learn

What is Database projects - concept & overview

Database projects - Setup & Architecture for demo

Why we need SQL database projects?

Hands-on Lab/Demo: How to implement database projects in Fabric

For Create and configure deployment pipelines

What is deployment pipeline in Fabric? overview

Architecture of deployment pipeline  for Demo  & prerequisites

Hands on Lab/Demo :How to Create and configure deployment pipelines

Hands on Lab/Demo :How to assign workspace to respective stages and deploy content from one stage to next stage.

For Configure domain workspace settings

What is  domain in Fabric ?

What are the Delegated Setting for domain

Hands on Lab/Demo: how these delegated settings impacts domain in Fabric

For SQL database projects:

We will understand why we need SQL database projects

How to Setup Demo components & understand through Architecture diagram

Hands on Lab/Demo - How to Implement database projects in Fabric

For Configure security and governance in Fabric, you will learn concept & implementation of governance -

What is sensitivity labels? Overview & Concept

Sensitivity labels: related admin settings in Fabric

How to apply sensitivity labels to items in Fabric?

For Orchestrate processes, you will learn concept & implementation of Orchestrate processes

How to Choose between a pipeline and a notebook in Fabric?

Design and implement schedules triggers - Design components for demo

How to implement schedules triggers in Fabric Data Factory pipeline.

For Implement orchestration patterns with notebooks and pipelines, including parameters and dynamic expression

Data Factory pipeline good practice

What is Pipeline parameter and dynamic expression concept

How to implement parameters and dynamic expression in pipeline

How to configure pipeline to retry if pipeline run fails

How to implement orchestration patterns with notebooks and pipelines

For Design and implement loading patterns (Ingest and transform data), you will learn

How to design full and incremental data loads in Fabric

How to implement full and incremental data loads in Fabric through hands-on lab/demo

For Ingest and transform batch data - part 1, you will learn

how to choose an appropriate data store

how to choose between dataflows, notebooks, and T-SQL for data transformation

Shortcuts overview in fabric

Shortcuts type in Fabric

Shortcuts folder structure

How to create and manage shortcuts to data  in Fabric through hands-on lab/demo

For Ingest data by using pipelines (Ingest and transform batch data - Part 2), you will learn

How to design Ingest data by using pipelines into Lakehouse

How to ingest data by using pipelines into Lakehouse

How to design Ingest data by using pipelines into warehouse

How to ingest data by using pipelines into warehouse

How to design Ingest data by using pipelines into KQL Database

How to ingest data by using pipelines into KQL Database

For Transform data by using SQL (Ingest and transform batch data - Part 4), through hands-on lab/demo you will learn

How to implement SQL top distinct keyword

How to implement SQL Filter on data

How to  implement SQL Sort on data

How to implement Case & create dynamic or computed column

How to implement SQL Inner Join, left Join, right Join, outer Join

How to implement Aggregation in SQL

How to implement  SQL Group and aggregate data: Group by & Having Clause Aggregation

How to create Create Stored Procedure

How to transform the data using Stored Procedure activity in Data pipeline

For Optimize a lakehouse table (Optimize performance - Part 1) , through hands-on lab/demo you will learn

How to optimize a lakehouse table using Optimize command in Fabric

How to optimize a lakehouse table using V-Order in Fabric

How to optimize a lakehouse table using VACUUM command in Fabric

How to optimize a lakehouse table using Optimizetwrite command in Fabric

How to optimize a lakehouse table using Partition in Fabric

How to optimize a lakehouse table using Table maintenance feature in Fabric

Who this course is for:
If you are University Student who wants to start career as data engineer in Microsoft Fabric
Anyone who is working in any Cloud but wants to up-skill to work as  data engineer in Microsoft Fabric
Anyone who is already working as Azure, AWS, GCP Data Engineer but want to work in Microsoft Fabric
any existing Data Architect who wants to to work in Microsoft Fabric
anyone who wants career in Data Engineering on  Microsoft Fabric
If you want to add "Microsoft Certified: Fabric Data Engineer Associate" certification in resume.

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