DP-500T00: Azure Enterprise Data Analyst Associate

• Implement and manage a data analytics environment
• Query and transform data
• Implement and manage data models
• Explore and visualize data

Candidates for this course should have subject matter expertise in designing, creating, and deploying enterprise-scale data analytics solutions. Specifically, candidates should have advanced Power BI skills, including managing data repositories and data processing in the cloud and on-premises, along with using Power Query and Data Analysis Expressions (DAX). They should also be proficient in consuming data from Azure Synapse Analytics and should have experience querying relational databases, analyzing data by using Transact-SQL (T-SQL), and visualizing data.

Before attending this course, it is recommended that students have:

• A foundational knowledge of core data concepts and how they’re implemented using Azure data services. For more information see Azure Data Fundamentals.
• Experience designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value using Microsoft Power BI. For more information see Power BI training.

Module 1: Introduction to data analytics on Azure
This module explores key concepts of data analytics, including types of analytics, data, and storage. Students will explore the analytics process and tools used to discover insights and learn about the responsibilities of an enterprise data analyst and what tools are available to build scalable solutions.

Lessons

• Explore Azure data services for modern analytics
• Understand concepts of data analytics
• Explore data analytics at scale

After completing this module, students will be able to:

• Describe types of data analytics
• Understand the data analytics process
• Define data job roles in analytics
• Understand tools for scaling analytics solutions

Module 2: Govern data across an enterprise
This module explores the role of an enterprise data analyst in organizational data governance. Students will explore the use of Microsoft Purview to register and catalog data assets, to discover trusted assets for reporting, and to scan a Power BI environment.

Lessons

• Introduction to Microsoft Purview
• Discover trusted data using Microsoft Purview
• Catalog data artifacts by using Microsoft Purview
• Manage Power BI artifacts by using Microsoft Purview

After completing this module, students will be able to:

• Browse, search, and manage data catalog assets.
• Use data catalog assets with Power BI.
• Use Microsoft Purview in Azure Synapse Studio.
• Register and scan a Power BI environment using Microsoft Purview.

Module 3: Model, query, and explore data in Azure Synapse
This module explores the use of Azure Synapse Analytics for exploratory data analysis. Students will explore the capabilities of Azure Synapse Analytics including the basics of data warehouse design, querying data using T-SQL, and exploring data using Spark notebooks.

Lessons

• Introduction to Azure Synapse Analytics
• Implement star schema design and query relational data in Azure
• Analyze data with a serverless SQL pool in Azure Synapse Analytics
• Optimize data warehouse query design
• Analyze data with a Spark Pool in Azure Synapse Analytics

Lab : Query data in Azure

Lab : Explore data in Spark notebooks

Lab : Create a star schema model

After completing this module, students will be able to:

• Understand when to use Azure Synapse Analytics in reporting solutions.
• Query data with SQL.
• Query data with Spark.

Module 4: Prepare data for tabular models in Power BI
This module explores the fundamental elements of preparing data for scalable analytics solutions using Power BI. Students will explore model frameworks, considerations for building data models that will scale, Power Query optimization techniques, and the implementation of Power BI dataflows.

Lessons

• Choose a Power BI model framework
• Understand scalability in Power BI
• Optimize Power Query for scalable solutions
• Create and manage scalable Power BI dataflows

Lab : Create a dataflow

After completing this module, students will be able to:

• Choose an appropriate Power BI model framework.

Module 5: Design and build scalable tabular models
This module explores the critical underlying aspects of tabular modeling for building Power BI models that can scale. Students will learn about model relationships and model security, working with direct query, and using calculation groups.

Lessons

• Create Power BI model relationships
• Enforce model security
• Implement DirectQuery
• Create calculation groups

Lab : Create model relationships

Lab : Enforce model security

Lab : Design and build tabular models

Lab : Create calculation groups

Module 6: Optimize enterprise-scale tabular models
This module covers key aspects of performance optimization using large-format data. Students will explore optimization using Synapse, Power BI, and external tools.

Lessons

• Optimize performance using Synapse and Power BI
• Improve query performance with hybrid tables, dual storage mode, and aggregations
• Use tools to optimize Power BI performance

Lab : Use tools to optimize Power BI performance

Lab : Improve query performance using aggregations

Lab : Improve query performance with dual storage mode

Lab : Improve performance with hybrid tables

Module 7: Implement advanced data visualization techniques by using Power BI
This module explores data visualization concepts including accessibility, customization of core data models, real-time data visualization, and paginated reporting.

Lessons

• Understand advanced data visualization concepts
• Customize core data models
• Monitor data in real-time with Power BI
• Create and distribute paginated reports in Power BI report builder

Lab : Monitor data in real-time with Power BI

Lab : Create and distribute paginated reports in Power BI Report Builder

Module 8: Implement and manage an analytics environment
This module explores key considerations for implementing and managing Power BI. Students will understand key recommendations for administration and monitoring of Power BI, including configuration and management of Power BI capacity.

Lessons

• Recommend Power BI administration settings
• Recommend a monitoring and auditing solution for a data analytics environment
• Configure and manage Power BI capacity
• Establish a data access infrastructure in Power BI

Module 9: Manage the analytics development lifecycle
This module explores considerations for deployment, source control, and application lifecycle management of analytics solutions. Students will understand what to recommend and will be able to deploy and manage automated and reusable Power BI assets.

Lessons

• Recommend a deployment strategy for Power BI assets
• Recommend a source control strategy for Power BI assets
• Perform impact analysis of downstream dependencies from dataflows and datasets
• Recommend automation solutions for the analytics development lifecycle, including Power BI REST API
• Deploy and manage datasets by using the XMLA endpoint
• Deploy reusable assets

Lab : Create reusable Power BI assets

Module 10: Integrate an analytics platform into an existing IT infrastructure
This module explores the integration of a Power BI analytics solution into existing Azure infrastructure. Students will understand Power BI tenant and workspace configurations, along with considerations for Power BI deployment in an organization.

Lessons

• Recommend and configure a Power BI tenant or workspace
• Identify requirements for a solution, including features, performance, and licensing strategy
• Integrate an existing Power BI workspace into Azure Synapse Analytics

The DP-500T00: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI training course prepares learners for the Microsoft Certified: Azure Enterprise Data Analyst Associate certification.

 

Learners are required to complete and pass the DP-500 certification exam in order to attain this credential.

 

The DP-500 exam measures your ability to accomplish the following technical tasks: implement and manage a data analytics environment; query and transform data; implement and manage data models; and explore and visualize data.

 

Skills measured

 

• Implement and manage a data analytics environment (25–30%)
• Query and transform data (20–25%)
• Implement and manage data models (25–30%)
• Explore and visualize data (20–25%)

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Top Data Analyst Certifications for 2023

 

If you fit the profile of someone who loves to analyze data and discover insights and have fundamental understanding of data repositories and data processes, both on-premises and in the cloud, read on!

What is the role on an Azure Enterprise Data Analyst?

 

An Azure Enterprise Data Analyst is a professional who specializes in working with data in the Microsoft Azure cloud platform. Their role involves using a range of Azure services, tools, and technologies to gather, store, process, analyze, and visualize data, ultimately helping businesses make informed decisions. 

 

In addition to that, Azure Enterprise Data Analysts should also possess strong analytical and problem-solving skills, as well as in-depth knowledge of Azure data services, SQL, data modeling, data warehousing, and data visualization tools.

 

What is the Azure Enterprise Data Analyst Associate certification?

 

The Azure Enterprise Data Analyst Associate certification is a Microsoft certification that validates the skills required to design and implement modern data solutions that integrate with Azure services.

 

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In today's fast-paced and highly competitive world of technology, it's more important than ever to stay ahead of the curve and differentiate yourself as a skilled professional.

 

Microsoft certifications are globally recognized, industry-standard credentials that showcase your expertise in various Microsoft technologies, making them a worthwhile investment in your career growth. By obtaining a Microsoft certification, you're not only validating your skills and knowledge, but also demonstrating your commitment to continuous learning and staying current with the latest industry trends.

 

Microsoft certifications cater to a wide range of roles, including developers, administrators, data professionals, and IT managers, providing a versatile pathway to career advancement. As organizations increasingly rely on Microsoft technologies such as Azure, Office 365, and Dynamics 365, the demand for certified professionals continues to grow. A Microsoft certification not only improves your employability, but also enhances your earning potential and credibility within your field.

 

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Why learn Azure?

 

In today's digital landscape, cloud computing has become an essential part of every organization's IT strategy, and Microsoft Azure stands at the forefront of this transformation. As one of the leading cloud platforms, Azure offers a wide range of services and tools, making it a highly sought-after skill for IT professionals across various industries.

 

By learning Azure, you're not only staying current with the latest developments in cloud technology but also empowering yourself to work on cutting-edge projects, improve your problem-solving capabilities, and drive innovation within your organization.

 

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As an Azure professional, you'll be equipped to deploy, manage, and maintain cloud infrastructure, ensuring seamless integration and optimal performance of critical business applications. Learning Azure not only enhances your career prospects but also significantly increases your earning potential, as certified Azure professionals are highly valued in the job market.

 

Embrace the power of cloud computing and take your career to new heights by mastering Microsoft Azure, and unlock a world of new possibilities and opportunities in this exciting, ever-evolving field.