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Aron Mesterbasic
This course covers methods and practices for performing advanced data analytics at scale. You will build on existing analytics experience and will learn to implement and manage a data analytics environment, query and transform data, implement and manage data models, and explore and visualize data. In this course, you will use Microsoft Purview, Azure Synapse Analytics, and Power BI to build analytics solutions.
Your course package is designed to provide maximum learning and convenience. This is included in the price of your course:
Your expert instructor will get you ready for the following exam, which is included in your course package.
You´ll have the perfect starting point for your training with these prerequisites:
- 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 Data Analyst.
Using our engaging learning methodology using a variety of tools, we’ll cover the entire curriculum.
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
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
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
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
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
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
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.
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
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 Virtual Classroom is an online room, where you will join your instructor and fellow classmates in real time. Everything happens live and you can interact freely, discuss, ask questions, and watch your instructor present on a whiteboard, discuss the courseware and slides, work with labs, and review.
Yes, you can sit exams from all the major Vendors like Microsoft, Cisco etc from the comfort of your home or office.
With Readynez you do any course form the comfort of your home or office. Readynez provides support and best practices for your at-home classroom and you can enjoy learning with minimal impact on your day-to-day life. Plus you'll save the cost and the environmental burden of travelling.
Well, learning is limitless, when you are motivated, but you need the right path to achieve what you want. Readynez consultants have many years of experience customizing learner paths and we can design one for you too. We are always available with help and guidance, and you can reach us on the chat or write us at info@readynez.com.