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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.
In this course, you will explore and visualize data with Power BI.
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.
Topic A: Data Analysis and Visualization for Business Intelligence
Topic B: Self-Service BI with Microsoft Power BI
Topic A: Create Data Connections
Topic B: Model Data with Relationships
Topic C: Save Power BI Files
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
Topic A: Create Visualizations in Power BI
Topic B: Chart Data in Power BI
Topic A: Enhance Analysis with Customized Visuals and Pages
Topic B: Enhance Analysis with Tooltips
Topic A: Create Calculations with Data Analysis Expressions (DAX)
Topic B: Create Calculated Measures and Conditional Columns
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.
2 Days Course
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