Microsoft Power BI: Data Analysis Practitioner

As technology progresses and becomes more interwoven with our businesses and lives, more data is collected about business and personal activities. This era of “big data” has exploded due to the rise of cloud computing, which provides an abundance of computational power and storage, allowing organizations of all sorts to capture and store data. Leveraging that data effectively can provide timely insights and competitive advantage.

The creation of data-backed visualizations is a key way data scientists, or any professional can explore, analyze, and report insights and trends from data. Microsoft® Power BI® software is designed for this purpose. Power BI was built to connect to a wide range of data sources, and allows users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Power BI’s data connection capabilities and visualization features go far beyond those that can be found in spreadsheets, allowing users to create compelling and interactive worksheets, dashboards, and stories that bring data to life and turn data into thoughtful action.

Microsoft Power BI: Data Analysis Practitioner

Course Objectives:

In this course, you will explore and visualize data with Power BI.

You will:

• Analyze data with self-service BI.
• Connect to data sources.
• Perform advanced data modeling and shaping.
• Visualize data with Power BI.
• Enhance data analysis.
• Model data with calculations.
• Create interactive visualizations.

Business intelligence (BI) is a term that has become increasingly common over recent years. Along with big data, data mining, predictive analytics, data science, and data stewards, BI is now very much part of business vocabulary. Much of the impetus behind this is the need for organizations to cope with ever-increasing datasets. It is now normal to have databases that contain millions of rows, requiring gigabytes, terabytes, or even petabytes, of storage space. Data is no longer confined to an on-premises server room—it is hosted in the cloud, feeds are taken from third-party providers, public datasets are freely available, and social media interactions generate ever-expanding datasets. Reporting and analysis is certainly not a new concept to business, but the difference between how data analysis is done today, compared with five or 10 years ago, is immense. Nowadays, organizations need BI to see not only what was done in the past, but also more of what is to come. There is now an overwhelming amount of data to gather and compose into reports. There is also an increasing need for data to offer up-to-the-minute numbers, so a business can react faster to changing trends in markets and industries. Those businesses that can react fast and predict near-term trends to provide products and services where there is consumer demand have the best chance of survival in our modern and highly competitive world. With the rise of big data, there is an increasing need for data analysts who can take this data, and find the critical points within a plethora of information.

Self-service business intelligence (BI) is becoming increasingly popular in organizations. This approach enables business users to access corporate data, and create and share reports and key performance indicators (KPIs) without dependency on a dedicated report developer. Business users can use the Microsoft Power BI suite of tools to connect to a wide variety of data sources. These include the main industry-standard databases, Microsoft cloud-based services—Microsoft Azure SQL Database, Azure Data Lake, and Azure Machine Learning—alongside Microsoft Excel and other files, and software as a service (SaaS) providers such as Microsoft Bing, Facebook, and MailChimp. The combination of flexibility and the ability to create visually stunning, interactive dashboards quickly makes Power BI an obvious choice for any organization that needs to provide its users with a self-service BI solution.

Lesson 1: Analyzing Data with Self-Service BI

 Topic A: Data Analysis and Visualization for Business Intelligence

 Topic B: Self-Service BI with Microsoft Power BI

 Lesson 2: Connecting to Data

 Topic A: Create Data Connections

 Topic B: Model Data with Relationships

 Topic C: Save Power BI Files

Lesson 3: Performing Advanced Data Modeling and Shaping

 Topic A: Clean and Transform Data with the Query Editor

 Topic B: Shape Data with the Query Editor

 Topic C: Combine and Manage Data Rows

 Lesson 4: Visualizing Data with Power BI

 Topic A: Create Visualizations in Power BI

 Topic B: Chart Data in Power BI

 Lesson 5: Enhancing Data Analysis

 Topic A: Enhance Analysis with Customized Visuals and Pages

 Topic B: Enhance Analysis with Tooltips

 Lesson 6: Modeling Data with Calculations

 Topic A: Create Calculations with Data Analysis Expressions (DAX)

 Topic B: Create Calculated Measures and Conditional Columns

Lesson 7: Creating Interactive Visualizations

 Topic A: Create and Manage Data Hierarchies

 Topic B: Filter and Slice Reports

 Topic C: Create Dashboards in Power BI

To ensure your success, you should have experience managing data with a spreadsheet program such as Microsoft Excel or Google Sheets.

Optionally, having experience with other data analytics tools, such as Google Analytics™ or Customer Relationship Management (CRM) tools, as well as an understanding of database design concepts and basic programming constructs such as looping and branching, will help you get even more out of this course.

This course is designed for professionals in a variety of job roles who are currently using desktop or web-based data-management tools such as Microsoft Excel or SQL Server reporting server to perform numerical or general data analysis. They are responsible for conducting data analysis and providing reports about their analysis, and are looking for alternative ways to analyze business data, visualize insights, and share those insights with peers across the enterprise. This includes capturing and reporting on data to peers, executives, and clients.