PL-300: Extracting Insights from Data Using Power BI

Microsoft Power BI    |    Intermediate
  • 14 videos | 1h 54m 41s
  • Includes Assessment
  • Earns a Badge
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Getting insights from data isn't always straightforward. However, using a tool like Power BI helps with heavy lifting. Through this hands-on course, learn to obtain insights from data using a combination of Power BI's visualization and analysis features. Explore how and why numeric data is summarized. Discover how the sum, mean, and median statistics, among others, give different views of the same data. Practice modeling data into customized groups to better represent it to end users. Use scatter charts to identify clusters and enable analysis of snapshots of data with a play axis. Finally, use the key influencers visual to identify how certain metrics are influenced by values in other fields. Upon completion, you'll know how to take advantage of the analytics features of Power BI visuals. You'll also be more prepared for the PL-300 certification exam.


  • Discover the key concepts covered in this course
    Apply different summary statistics to obtain different metrics from your data
    Recognize how duplicated numeric values can be aggregated in visuals
    Create groups out of the existing categorical values in a table field
    Edit, manage, and use customized groups in visuals
    Create groups out of a numeric field by binning the data points
    Identify clusters in your data by using the clusters feature in power bi
  • Recognize how to interpret clusters in your data and tweak power bi's clustering algorithm for your data
    Use the play axis feature of a power bi scatter chart to enable chart animation and explore data at different points in time
    Analyze data over a time series using a line chart and a slicer
    Find the values in a categorical field that have the greatest influence on a numeric field in your data
    Identify key influencers across multiple fields in your dataset
    Find the range of values in a numeric field that serves as key influencers for a metric
    Summarize the key concepts covered in this course


  • 2m 56s
  • 8m 52s
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    3.  Aggregating Duplicated Values
    6m 14s
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    4.  Grouping Categorical Values
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    5.  Editing and Applying Customized Groups
    5m 51s
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    6.  Binning Data Based on a Numeric Column
    9m 48s
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    7.  Finding Clusters in a Dataset
    11m 59s
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    8.  Interpreting and Configuring Clusters
    11m 44s
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    9.  Animating Scatter Charts with a Play Axis
    10m 38s
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    10.  Time Series Analysis with Line Charts
    7m 8s
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    11.  Identifying Key Influencers of Metrics
    12m 4s
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    12.  Identifying Combinations of Key Influencers
    10m 59s
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    13.  Finding Numeric Field Values as Key Influencers
    4m 28s
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    14.  Course Summary
    2m 1s


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