Udemy – Exam DP-700 Fabric Data Engineer Associate Ultimate Guide – Sarnendu De (Mar 2025)
English | Tutorial | Size: 3.23 GB
Multiple Concept & hands-on Lab on Fabric Spark Pool, PySpark, Version Control, Security, Governance, Eventstream, KQL
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
RAPIDGATOR:
rapidgator.net/file/6f273962b8f95601bff6b499b565bfcd/Udemy_-_Exam_DP-700_Fabric_Data_Engineer_Associate_Ultimate_Guide_-_Sarnendu_De_(Mar_2025).part1.rar.html
rapidgator.net/file/9725f4a2dee0d0c539af6b3cda3275ac/Udemy_-_Exam_DP-700_Fabric_Data_Engineer_Associate_Ultimate_Guide_-_Sarnendu_De_(Mar_2025).part2.rar.html
rapidgator.net/file/e743b05c495add18d5812a81544b9d90/Udemy_-_Exam_DP-700_Fabric_Data_Engineer_Associate_Ultimate_Guide_-_Sarnendu_De_(Mar_2025).part3.rar.html
TURBOBIT:
trbt.cc/3degbon50ddt/Udemy_-_Exam_DP-700_Fabric_Data_Engineer_Associate_Ultimate_Guide_-_Sarnendu_De_(Mar_2025).part1.rar.html
trbt.cc/f50sq61wun0a/Udemy_-_Exam_DP-700_Fabric_Data_Engineer_Associate_Ultimate_Guide_-_Sarnendu_De_(Mar_2025).part2.rar.html
trbt.cc/48ilmw88ojcy/Udemy_-_Exam_DP-700_Fabric_Data_Engineer_Associate_Ultimate_Guide_-_Sarnendu_De_(Mar_2025).part3.rar.html