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Power BI Intermediate

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Date(s) - 13/12/2018
1:15 pm - 4:30 pm

The Quill Consultancy


This is a half-day course. The Power BI offers a straightforward approach to report creation, and the ability to create and share dashboards without dependency on a report developer, or the need for Microsoft® SharePoint®. Microsoft Excel® has long been the tool of choice for data analysts who work in a self-service style. However, Excel does not offer a quick and easy way to share reports without the use of either SharePoint, or the creation of multiple copies of spreadsheets that quickly become out of date, or exist outside source control.
In recent years, four power tools have been added to Excel: Power View, Power Query (known as Get & Transform in Excel 2016), Power Pivot, and Power Map. Power BI brings much of this power into an integrated environment in the form of Power BI Desktop. Previously, Excel users have been inconvenienced by needing to transition between the four power tools, but Power BI Desktop brings the tools together. This means that Power BI is fast becoming an obvious choice for the analysis and sharing of data. However, analysts are likely to continue working with Excel for the foreseeable future. Power BI easily cooperates with Excel, and many other data sources. It’s this ability to create reports rapidly, by using data from a combination of sources, that really puts the power into Power BI.

Prerequisite skills/knowledge:

Before attending this course, students must have:

  • Knowledge of relational databases and reporting.
  • Some basic knowledge of data warehouse schema topology (including star and snowflake schemas).
  • Some exposure to basic programming constructs (such as looping and branching).
  • An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.
  • Familiarity with Microsoft Office applications – particularly Excel.

Goals and Expectations:

After completing this course, students will be able to:

  • Connect to Excel files and import data.
  • Describe the data model and know how to optimize your data within the model.
  • Use on-premises and cloud Microsoft SQL Server databases as data sources, along with the R script data connector.
  • Take advantage of the features of the Power BI service by using Q&A to ask questions in natural query language, and create content packs and groups.
  • Perform a range of query editing skills in Power BI.
  • Shape data, using formatting and transformations.
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