Power BI - Microsoft Power BI is an interactive data visualization software product developed by Microsoft with a primary focus on business intelligence. It is part of the Microsoft Power Platform.

Power BI is a Microsoft business intelligence (BI) and data visualization software service that allows users to connect to various data sources, clean and model data, and create interactive reports and dashboards. It helps users uncover insights and share them through customizable visuals, mobile-optimized reports, and various sharing options. Power BI is part of the Microsoft Power Platform and offers AI-powered features to discover patterns and predict future outcomes.

1. Microsoft © Power BI

2. Microsoft © Power BI

3. As the process of analyzing raw data to find trends and answer questions, the definition of data analytics captures its broad scope of the field. However, it includes many techniques with many different goals. The data analytics process has some components that can help a variety of initiatives. By combining these components, a successful data analytics initiative will provide a clear picture of where you are, where you have been and where you should go. Data analytics is a broad field. There are four primary types of data analytics: descriptive, diagnostic, predictive and prescriptive analytics. Each type has a different goal and a different place in the data analysis process. These are also the primary data analytics applications in business. Data Analytics and Microsoft © Power BI Module 1 – Lesson 1

4. Data Analytics and Microsoft © Power BI Module 1 – Lesson 1 Data Analysts provide real-time insights across an organization. Connect, prepare and model Connect to and transform data with advanced data preparation capabilities. Visualize Create interactive data visualizations and uncover important insights. Publish and share Publish dashboards and share insights to drive informed action throughout your organization.

5. Descriptive and Diagnostic Analytics Module 1 – Lesson 1 Descriptive analytics helps answer questions about what happened. These techniques summarize large datasets to describe outcomes to stakeholders. By developing key performance indicators (KPIs,) these strategies can help track successes or failures. Metrics such as return on investment (ROI) are used in many industries. Specialized metrics are developed to track performance in specific industries. This process requires the collection of relevant data, processing of the data, data analysis and data visualization. This process provides essential insight into past performance. Diagnostic analytics helps answer questions about why things happened. These techniques supplement more basic descriptive analytics. They take the findings from descriptive analytics and dig deeper to find the cause. The performance indicators are further investigated to discover why they got better or worse. This generally occurs in three steps: Identify anomalies in the data. These may be unexpected changes in a metric or a particular market. Data that is related to these anomalies is collected. Statistical techniques are used to find relationships and trends that explain these anomalies.

6. Predictive and Prescriptive Analytics Module 1 – Lesson 1 Predictive analytics helps answer questions about what will happen in the future. These techniques use historical data to identify trends and determine if they are likely to recur. Predictive analytical tools provide valuable insight into what may happen in the future and its techniques include a variety of statistical and machine learning techniques, such as: neural networks, decision trees, and regression. Prescriptive analytics helps answer questions about what should be done. By using insights from predictive analytics, data-driven decisions can be made. This allows businesses to make informed decisions in the face of uncertainty. Prescriptive analytics techniques rely on machine learning strategies that can find patterns in large datasets. By analyzing past decisions and events, the likelihood of different outcomes can be estimated.

7. Overview of Data Roles – Module 1 – Lesson 1 Data Scientists Dealing with all aspects of the project. Collecting and analyzing data. Visualizing and presenting data. Researching and developing new algorithms and approaches. Data Engineers Designing, building, and maintaining data pipelines. Batch processing of collected data and matching its format to the stored data. Keeping the ecosystem and the pipeline optimized and efficient. Ensuring data is available for data scientists and analysts to use.

8. Overview of Data Roles Module 1 – Lesson 1 Data Architect Designing and creating new database systems that match the requirements of a specific business model and job requirements. Maintaining these systems, both from the functionality perspective and the administrative one. Keeping track of the data and deciding who can view, use, and manipulate different sections of the data. Data Storyteller This is a fairly new role in the field of Data Science. Finding the narrative that best describes the data and uses it to express it. Simplifies data, focuses on a specific aspect, analyzes its behavior, and uses their insights to create a compelling story that helps people better understand the data.

9. Overview of Data Roles Module 1 – Lesson 1 Other Roles in Data Science Machine Learning Scientist (academia) Researching new data manipulation approaches and designs new algorithms to be used. Machine Learning Engineer Has strong statistics and programming skills and some knowledge of software engineering. Business Intelligence Developer Designing and developing strategies that allow business users to find the information they need to make decisions quickly and efficiently. Database Administrator Monitoring the database for functionality and creating backups and recoveries. Granting permissions to employees based on their job requirements and employment level.

10. Power BI Licensing Module 1 – Lesson 2 Features vary based on licensing License Type Capabilities Additional capabilities when workspace is in a Premium Capacity Power BI (free) Access to content in My Workspace Consume content shared with them Power BI Pro Publish content to other workspaces, share dashboards, subscribe to dashboards and reports, share with users who have a Pro license Distribute content to users who have free licenses. Power BI Premium Per User Same as Pro. Can also share with users who have a Premium Per User license Distribute content to users who have free and Pro licenses. Power BI Premium Per Capacity Same as Premium Per User.

11. The Landscape of Products and Services in Power BI Module 1 – Lesson 2

12. Power BI Desktop Module 1 – Lesson 2

13. Power BI Service Module 1 – Lesson 2

14. Power BI Desktop & Power BI Service Module 1 – Lesson 2 Power BI Desktop (application) and Power BI Service (cloud-based) are bundled together. Even the free version has a robust feature set.

15. Power BI Report Builder – Module 1 – Lesson 2

16. Module 2 Files – see Video Description

17. Module 2 - Recap

18. Authentication

19. Module 3: Clean, Transform & Load Data

20. Module 3: Join Types

21. Module 3: Recap

22. Module 4: Design a Data Model in Power BI

23. Module 4: What is Data Modeling?

24. Module 4: Lessons

25. Module 4: Breaking Down Tables

26. Module 4: Fact vs. Dimension

27. Module 4: Golden Rule

28. Module 4: Relationships/Cardinality

29. Module 4: Row-Level Security (RLS)

30. Module 4: Recap

31. Module 5: Create Model Calculations Using DAX

32. Module 5: What is DAX?

33. Module 5: Lessons

34. Module 5: Recap

35. Module 6: Optimize Model Performance

36. Module 6: Lessons

37. Module 6: Optimize DirectQuery Models

38. Module 6: When to use DirectQuery vs. Import

39. Module 6: File Size – Import vs. DirectQuery

40. Module 6: What are Variables?

41. Module 6: Understand the Importance of Variables

42. Module 6: Other Optimization Techniques

43. Module 6: Recap

44. Module 7: Create Reports

45. Module 7: Lessons

46. Module 7: Create a Drill-through Page

47. Module 7: Accessibility

48. Module 7: Built-in Accessibility (no configuration)

49. Module 7: Built-in Accessibility (configuration required)

50. Module 7: Recap

51. Module 8: Create Dashboards

52. Module 8: Lessons

53. Module 8: What is a Dashboard?

54. Module 8: Streaming Real-time Data

55. Module 8: Three Types of Real-time Datasets

56. Module 8: Comparison of Dataset Types Capability Push Streaming PubNub Dashboard updates in real time as data is pushed in Yes. For visuals built via reports and pinned to dashboard Yes. For custom streaming tiles added directly to dashboard Yes. For custom streaming tiles added directly to dashboard Dashboard tiles update with smooth animation No. Yes. Yes. Data stored permanently in Power BI for historic analysis. Yes. No. Data is temporarily stored for one hour to render visuals. No. Build Power BI Reports atop the data. Yes. No. No.

57. Module 8: Real-Time Push Dataset

58. Module 8: Recap

59. Module 9: Create Paginated Reports in Power BI

60. Module 9: Report Builder

61. Module 9: Lessons

62. Module 9: Recap

63. Module 10: Perform Advanced Analytics

64. Module 10: Lessons

65. Module 10: Recap

66. Module 11: Manage Workspaces

67. Module 11: Lessons

68. Module 11: Workspace Roles

69. Module 11: Workspace Roles Capability Admin Member Contributor Viewer Update/Delete WS Yes Add/Remove Users, including other Admins Yes Allow contributors to update the app for the WS Yes Add members with lower permissions Yes Yes Publish, unpublish, and change app permissions Yes Yes

70. Module 11: Workspace Roles Capability Admin Member Contributor Viewer Update an app Yes Yes If allowed Share an item/app Yes Yes If allowed If allowed Allow others to reshare items Yes Yes Feature apps on colleagues’ Home Yes Yes Manage dataset permissions Yes Yes

71. Module 11: Workspace Roles Capability Admin Member Contributor Viewer Feature dashboards/reports on colleagues’ Home Yes Yes Yes Create/edit/delete content in WS Yes Yes Yes Publish reports to the WS/delete content Yes Yes Yes Create report in another WS based on a dataset in this WS Yes Yes Yes Copy a report Yes Yes Yes

72. Module 11: Workspace Roles Capability Admin Member Contributor Viewer Create goals based on a dataset in the WS Yes Yes Yes Schedule data refreshes via the on-premises gateway Yes Yes Yes Modify gateway connection settings Yes Yes Yes View/interact with an item Yes Yes Yes Yes Read data stored in WS dataflows Yes Yes Yes Yes

73. Module 11: Recap

74. Module 12: Manage Datasets in Power BI

75. Module 12: Lessons

76. Module 12: Parameters

77. Module 12: Recap