DP-500 Microsoft Azure Enterprise Data Analyst Associate Exam Prep

LU1 Introduction to data analytics on Azure

Topic 1 Explore Azure data services for modern analytics

• Understand the Azure data ecosystem
• Explore modern analytics solution architecture

Topic 2 Understand concepts of data analytics

• Understand data analytics types
• Explore the data analytics process
• Understand types of data and data storage

Topic 3 Explore data analytics at scale

• Explore data team roles and responsibilities
• Review tasks and tools for data analysts
• Scale analytics with Azure Synapse Analytics and Power BI
• Strategies to scale analytics

LU2 Govern data across an enterprise

Topic 4 Introduction to Microsoft Purview

• What is Microsoft Purview?
• How Microsoft Purview works
• When to use Microsoft Purview

Topic 5 Discover trusted data using Microsoft Purview

• Search for assets
• Browse assets
• Use assets with Power BI
• Integrate with Azure Synapse Analytics

Topic 6 Catalog data artifacts by using Microsoft Purview

• Register and scan data
• Classify and label data
• Search the data catalog

Topic 7 Manage Power BI assets by using Microsoft Purview

• Register and scan a Power BI tenant
• Search and browse Power BI assets
• View Power BI metadata and lineage

Topic 8 Integrate Microsoft Purview and Azure Synapse Analytics

1. Catalog Azure Synapse Analytics data assets in Microsoft Purview
2. Connect Microsoft Purview to an Azure Synapse Analytics workspace
3. Search a Purview catalog in Synapse Studio
4. Track data lineage in pipelines
5. Exercise - Integrate Azure Synapse Analytics and Microsoft Purview

LU3 Model, query, and explore data in Azure Synapse

Topic 9 Introduction to Azure Synapse Analytics

• What is Azure Synapse Analytics
• How Azure Synapse Analytics works
• When to use Azure Synapse Analytics
• Exercise - Explore Azure Synapse Analytics

Topic 10 Use Azure Synapse serverless SQL pool to query files in a data lake

• Understand Azure Synapse serverless SQL pool capabilities and use cases
• Query files using a serverless SQL pool
• Create external database objects
• Exercise - Query files using a serverless SQL pool

Topic 11 Analyze data with Apache Spark in Azure Synapse Analytics

• Get to know Apache Spark
• Use Spark in Azure Synapse Analytics
• Analyze data with Spark
• Visualize data with Spark
• Exercise - Analyze data with Spark

Topic 12 Analyze data in a relational data warehouse

• Design a data warehouse schema
• Create data warehouse tables
• Load data warehouse tables
• Query a data warehouse
• Exercise - Explore a data warehouse

LU4 Prepare data for tabular models in Power BI

Topi 13 Choose a Power BI model framework

• Describe Power BI model fundamentals
• Determine when to develop an import model
• Determine when to develop a DirectQuery model
• Determine when to develop a composite model
• Choose a model framework

Topic 14 Understand scalability in Power BI

• Describe the significance of scalable models
• Implement Power BI data modeling best practices
• Configure large datasets
• Exercise: Create a star schema model

Topic 15 Create and manage scalable Power BI dataflows

• Define use cases for dataflows
• Create reusable assets
• Implement best practices
• Exercise: Create a dataflow

LU5 Design and build tabular models

Topic 16 Create Power BI model relationships

• Understand model relationships
• Set up relationships
• Use DAX relationship functions
• Understand relationship evaluation
• Exercise: Work with model relationships

Topic 17 Use DAX time intelligence functions in Power BI Desktop models

• Use DAX time intelligence functions
• Additional time intelligence calculations
• Exercise - Create Advanced DAX Calculations in Power BI Desktop

Topic 18 Create calculation groups

• Understand calculation groups
• Explore calculation groups features and usage
• Create calculation groups in a model
• Exercise: Create calculation groups

Topic 19 Enforce Power BI model security

• Restrict access to Power BI model data
• Restrict access to Power BI model objects
• Apply good modeling practices
• Exercise: Enforce model security

Topic 20 Use tools to optimize Power BI performance

• Use Performance analyzer
• Troubleshoot DAX performance by using DAX Studio
• Optimize a data model by using Best Practice Analyzer
• Exercise: Use tools to optimize Power BI performance
• LU6 Implement advanced data visualization techniques by using Power BI

Topic 21 Understand advanced data visualization concepts

• Create and import a custom report theme
• Enable personalized visuals in a report
• Design and configure Power BI reports for accessibility
• Create custom visuals with R or Python
• Review report performance using Performance Analyzer

Topic 22 Monitor data in real-time with Power BI

• Describe Power BI real-time analytics
• Set up automatic page refresh
• Create real-time dashboards
• Set-up auto-refresh paginated reports
• Exercise: Monitor data in real-time with Power BI

Topic 23 Create paginated reports

• Get data
• Create a paginated report
• Work with charts on the report
• Publish the report

LU7 Implement and manage an analytics environment

Topic 24 Provide governance in a Power BI environment

• Elements of data governance
• Configure tenant settings
• Deploy organizational visuals
• Manage embed codes
• Help and support settings

Topic 25 Facilitate collaboration and sharing in Power BI

• Workspaces evolved
• Impact to Power BI users
• Permissions in workspaces v
• Apps in Power BI
• Share
• Publish to web
• Embed and link in portals
• Data sensitivity labels
• Data privacy

Topic 26 Monitor and audit usage

Premium resource management

• Supporting multi geographies
• Bring your own key (BYOK)
• Featured external tools

Topic 27 Establish a data access infrastructure in Power BI

• Personal gateways versus enterprise gateways
• How data is refreshed
• Gateway network requirements
• Where to install gateway?
• Establish high availability gateways
• Establish load balancing of gateways
• Gateway performance monitoring documentation
• Multiple data sources per gateway
• Manage gateway users
• Active Directory user mapping with custom property lookup

Topic 28 Broaden the reach of Power BI

• REST API custom development
• Provision a Power BI embedded capacity
• Dataflow introduction
• Dataflow explained
• Create a Dataflow
• Dataflow capabilities on Power BI Premium
• Template apps - install packages
• Template apps - installed entities
• Template app governance

Topic 29 Automate Power BI administration

• REST API - Power BI service
• Microsoft Power BI cmdlets for Windows PowerShell and PowerShell core
• Install and use the Power BI cmdlet
• Test REST API calls
• Script typical administrator tasks
• Lab

Topic 30 Build reports using Power BI within Azure Synapse Analytics

• Describe the Power BI and Synapse workspace integration
• Exercise - Connect to Power BI from Synapse
• Understand Power BI data sources
• Exercise - Create a new data source to use in Power BI
• Exercise - Create a new Power BI report in Synapse Studio
• Describe Power BI optimization options
• Exercise - Improve performance with materialized views and result-set caching
• Visualize data with serverless SQL pools

LU8 Manage the analytics development lifecycle

Topic 31 Design a Power BI application lifecycle management strategy

• Define application lifecycle management
• Recommend a source control strategy
• Design a deployment strategy

Topic 32 Create and manage a Power BI deployment pipeline

• Understand the deployment process
• Create a deployment pipeline
• Assign a workspace
• Deploy content
• Work with deployment pipelines

Topic 33 Create and manage Power BI assets

• Create reusable Power BI assets
• Explore Power BI assets using lineage view
• Manage a Power BI dataset using XMLA endpoint
• Exercise: Create reusable Power BI assets

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Minimum Entry Requirement

Knowledge and Skills

• Able to operate using computer functions
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

• Positive Learning Attitude
• Enthusiastic Learner

Experience

• Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

TBD

Hardware: Window or Mac Laptops

• Data Analyst
• Business Intelligence Analyst
• Database Administrator
• Data Scientist
• Data Engineer
• Azure Solution Architect
• Cloud Engineer
• Data Architect
• Machine Learning Engineer
• AI Developer
• Business Analyst
• Data Consultant
• Big Data Engineer
• SQL Developer
• Data Manager

Peter Cheong :  I am a ACLP certied trainer. Specialise In IT related knowlege and conduct IT Training which Include Microsoft Window Server Technology (Wintel) and Linux - Centos/Red Hat. Comptia ,ITIL , Motorola Solution Trunking System and Cisco Networking. I was worked in Motorola Solutions Conduct Motorola Astro 25 Trunking System For Police Force Malaysia (RMPnet),Taiwan Navy, Indonesia METRO POLDA (Police Force). After that I Join As IT Group Manager For W-Group which include 17 subsidiaries Companies in Real Estate Developer,Plantation, Building Management Services ,Contruction and also Fiber Opti Service Provider in Sabah,Malaysia.

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Agus Salim : I am a professional with more than 10 years of experience in Project Management, IT Solutions Management, and Systems Integration both in waterfall and agile methodology. He started out his career as a Web Developer before moving on to Business Analyst/Project Manager. He has strong leadership and the capability of leading a team with a proven ability to deliver projects with tight timelines. Besides his experiences in managing projects, he has good knowledge in Cybersecurity and hands-on experience in Next Generation Firewall such as Check Point. During his free time, he likes to explore Cloud Technology, especially on Microsoft Azure.

Sanjiv Venkatram: Sanjiv i is an ACTA certified experienced leader with a proven track record in business / finance consulting and in developing i) business intelligence (BI) solutions ii) data analytics/analysis solutions and iii) IOT lead BI solutions. Sanjiv's goal through Prudentia Consulting, is to promote the simple joy and excitement of actively using the Microsoft Platform. He believes that the agility afforded by the Microsoft platform helps businesses get time back for deeper business thinking and to spend more time with their end customers

Sanjiv has rich experiences in diverse/complex high-tech businesses, turn around environments and strategic transformations. His functional expertise is in sales analytics, financial planning and analysis, engineering and program management. He has worked across discrete manufacturing, professional services and higher education verticals. He also has a working knowledge of equities portfolio management within the financial services domain.Sanjiv is the CEO of Prudentia Consulting, an organization committed to promoting the active usage of the Microsoft Platform. Prior to this, he has worked at Microsoft (US & APAC: 9.2 years), Cognizant Tech Solutions (3.3 years), Yazaki North America (8 years) and until recently at Oracle. Here are a few of his BI/analytics projects driven at scale: Built APAC wide BI dashboard using the Power BI umbrella tool set (Power BI online, Power BI desktop and Power Pivot) and a KPI lake (SQL DB), Helped develop key KPIs – identified key KPIs and helped land this in the DB, Developed a budget audit tool that captured budget inputs from a host of countries across the globe, Developed a business unit P&L reporting tool (functional architecture) in Business Objects for the world-wide financial planning and analysis team.