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From Data to Insights with Power BI - Summary

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Overview
Difficulty
Intermediate
Duration
59m
Students
134
Ratings
4.5/5
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Description

Power BI allows business users to analyze data and share insights across all levels of an organization. It gives an end-to-end view of important metrics and key performance indicators through intuitive and interactive dashboards all in one place.

In this course, you will learn about several Power BI tools that would help you enhance reports to expose insights and present them in a way that appeals to a wide range of end-users.

Learning Objectives

  • Understand how to apply conditional formatting, slicers, and filters
  • Perform top N analysis
  • Explore statistical summary
  • Use the Q&A visual
  • Add a Quick Insights result to a report
  • Understand when and where to create reference lines by using the Analytics pane
  • Learn when and where to use the Play Axis feature of a visualization
  • Understand how to personalize visuals

Intended Audience

  • Beginners to data analytics
  • Business analysts
  • Business intelligence developers
  • Business intelligence managers
  • Anyone who wants to learn about Power BI

Prerequisites

  • Microsoft Power BI Desktop for PC/Windows users (free download)
  • Familiarity with preparing data using Power BI
  • Familiarity with modeling data using Power BI
  • A basic understanding of Power Query, Power Pivot, and DAX is a plus but not required
Transcript

I hope you enjoyed learning about data insights with Power BI. Let's do a quick recap of what you learned. Conditional formatting where our visualizations benefit from dynamically setting colors based on the numeric value of a field in our data tables, to highlight data points that are above or below a given value such as areas of low or high sales. We specified customized colors on table cells as well as bar charts based on font color gradient rules and field values.

Slicers and filters. As a way of filtering our datasets to reduce the portion of data displayed in the report visualizations, we applied slicers and sync them to speak to other pages within our report, we applied a selection filter on a slicer once and have it applied to other pages, and we applied advanced slicers to report. Top N Analysis; using the Top N filter which works like the top clause in SQL, filtering and returning the data according to a specified number we want to filter. We applied the Top N filter to minimize the number of fields and to show only top value entries instead of basic filtering or advanced filtering.

Statistical summary. As a way to provide a quick and simple description of our data, statistical summary shows us the key distribution of our data and helps us identify key takeaways and anomalies that might exist in our datasets. We summarized a column within a table and explored key statistical functions using DAX.

The Q&A Visual, which allows our end users to ask natural language questions about the dataset, and Power BI uses machine learning and data science in order to come up with an answer on the fly in the form of a visual. We use the Q&A Visual for a report to allow end users to ask questions about the dataset. We set up the Q&A to teach our report more terms and questions to make it work better for the end users, and exported a report to Power BI service and use the Q&A functions online.

The Quick Insights feature which uses machine learning algorithms to go through a large dataset to quickly produce insights. A great way to build dashboards when we don't know where to start and helps us find insights that we might have missed in the reports to present them in an interesting and interactive visualizations and provide a deep understanding of our dataset. We added a quick insights result card to a dashboard, interacted with the quick insights results and connected to Power BI Web Service, and worked on the content tab of the report.

Reference Lines and Analytics Pane, which captures all the analytical options available for any selected chart to highlight a line indicating the minimum, mean or maximum value in a line chart. We identified the visuals that allows the use of reference lines such as the line chart. Use the analytics pane to add tread lines, add constant lines, show multiple series and change my color and line type. The Play Axis Feature, which acts as a dynamic slicer when we want to see trends and look for patterns in our data over time by clicking on 'play' and just focus on how our data is evolving.

We identified the visuals that allow using the play access features such as the scatter chart, imported play access as a custom visual, use the play access feature to step through the data using a date dimension and edited the interactions to view how each time period is creating a different view of the data. Personalized Visuals, which enable us to empower readers, to explore and personalize the visuals they want to see, like to change the type of visual, swap a graph access or add a tool tip to a table.

Through ad hoc exploration of visuals on a Power BI report, we personalized visuals in the report according to a preferred design using the personalized pane. We published report to Power BI service and then save the personalized view using the bookmarked feature. To learn more about Power BI, please look through our Microsoft library. We have courses on nearly every topic and we have more content coming out all the time. If you have any feedback positive or negative about this course or any other cloud academy courses, direct these inquiries to support@cloudacademy.com. Thanks, and have fun with Power BI.

About the Author

Moatasim has been a data and insight consultant since 2014, driving data culture strategies in enterprises, non-profit organizations and tech startups to improve their decision making. He has teamed up with Fortune 1000 companies, MBB and Big Four consultants on complex engagements in government and private sectors. He has been a data analyst, business analyst, BI manager, and instructor. To date, Moatasim has created learning content relating to business intelligence, data analysis and machine learning, mostly within Power BI, Azure, SQL and Python. His hobbies included heavy metal drumming and meditation.