Microsoft PowerBI – Advanced Solutions with Microsoft Excel and PowerBI Presented by: Phillip Guglielmi, CPA | Senior BI Consultant and Solutions Architect.

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Presentation transcript:

Microsoft PowerBI – Advanced Solutions with Microsoft Excel and PowerBI Presented by: Phillip Guglielmi, CPA | Senior BI Consultant and Solutions Architect SBS Group Global Direct: 646-747-7576 Email: pguglielmi@sbsgroupusa.com

Agenda Microsoft Power BI: What is it? A deeper look at the parts of Excel Power Tools: Why PowerPivot and Excel? Working with PowerPivot What is the Deployment Process? Uploading your PowerPivot Model to Power BI Creating and publishing a dashboard My Workspace Connecting to PowerBI Service vis a vis Excel (time permitting) Q & A As a BI Professional, I most often see people having difficulty with BOTH compiling data AND extracting insight from this data… Today is about solutions to those ever present problems. Excel can no longer be the sole solution for our data queries. However, Microsoft’s Power tools including PowerPivot and PowerBI represents a seminal moment – because for the first time these tools extend the analytical power of Analysis Services from the server and on to the client’s PC – giving business users enormous analytical capabilities, freed from the rigors of a centralized I.T. department. In this session, we are going to walk through building a report with Powerpivot, extracting and transforming data and uploading the model into PowerBI Desktop where we can use PowerBI as the powerful visualization tool to refine our model and uncover these insights. Actionable Insights Ease of use Powerful analysis

Advanced Analytics are Possible through PowerPivot PowerPivot Massive Data Volumes With a few mouse clicks, a user can create and publish intuitive and interactive self-service analysis solutions Can integrate with multiple services Data fully available to the rest of the workbook Does not need to be downloaded Opens over excel window Making full use of the advances in computer hardware, PowerPivot is an in memory engine exploiting the large amounts of memory now available on the client PC. Being completely in memory, and using column based compression techniques PowerPivot enables Excel 2010 to analyze large amounts of data at breath taking speed – whether the workbook is on the desktop or hosted in SharePoint. The advent of PowerPivot extends the reach of SQL Server to both ends of the business intelligence spectrum. PowerPivot can analyze well over a million rows of data while excel is limited to a 1,048,000 million. Data from a Powerpivot model is available to the rest of the workbook. Compare this with excel where you have to write complicated lookups and formulas to compile data For excel 2016, Powerpivot is included. If you have earlier versions, the download is free on Microsofts website The window opens over the excel window separate from the excel window.

PowerPivot – Powered by Data Analysis Expressions (DAX) DAX uses Excel syntax and many Excel functions Fetch data across relationships (one-many, many-one) PowerPivot also provides Excel with Data Analysis Expressions – otherwise known as DAX. We need DAX BOTH in PowerPivot and Power BI to create calculated columns in our tables and calculated measures in the overlaying PivotTables and visualizations. Some of you may be wondering why we don’t use Multi Dimensional Expressions - also known as MDX - already found in Analysis Services? It is because MDX is just too complicated for the average power user – DAX is a much easier, Excel like way, to handle the multi dimensional models created by PowerPivot and PowerBI. DAX functions inherently exploit the relationships automatically detected or manually created between imported tables – so that they can be used to fetch data across one- many relationships between the tables. There’s no notion of addressing individual cells or ranges with DAX - DAX functions only refer to columns in the data – here are some examples showing concatenation, a simple sum aggregation, the new related function that intrinsically uses relationships between tables and DAX comes with 35 time-series functions that are designed to help with the more tricky calculations like year to date, month to date, and parallel period calculations.

DEMO Walking through creating a Powerpivot model Creating a column calculation and measure Creating a slicer for TopN performing projects So that’s the theory, that’s the end of the slides – now lets look at the theory in practice. `

Getting Started with DAX Studio Once you have completed your model, you can document your measures. If you run the following script, you can extract your measures. select MEASUREGROUP_NAME, MEASURE_NAME, EXPRESSION from $SYSTEM.MDSCHEMA_MEASURES where MEASURE_AGGREGATOR = 0 order by MEASUREGROUP_NAME DAX Studio Window – Getting Started Now you know how to connect DAX Studio to your data models, it is time to look at what you can do (I will be using Excel as my source).  There is a lot to DAX Studio, but let me call out a few things in the UI to get you started (Referring to the image below). - This is the list of tables in your data model – it should be familiar to you - This is the query pane – it is where you write your queries - This is the run button to execute your query (you can also press F5). - This is the default output pane – where you will see the results of your query - You can change the default output from the output pane (4) to various other alternatives including Excel or a file (CSV or TXT). - Once you write your query in the query pane (2), you can click this button to use the DAX Formatter service to format the query directly in the query pane so it is easier to read. The server timings button is used for performance testing – more on that later The connect button allows you to repoint DAX studio to a different data model. Down the bottom of the page you can change from the list of tables to some of the other tabs including Functions (to help you write DAX) and DMV (Dynamic Management Views).  DMVs are a set of technical queries that will return you information about your data model.  More on that later too.

PowerPivot – Summary Analyse external data in the context of corporate data Analyse large data sets beyond the limits of Excel Share insights Use reports as databases Enable I.T. to provide required resources Use as a tool to gather business requirements

PowerPivot – Summary Great references: www.powerpivot.com PowerPivot Wiki www.powerpivotpro.com

DEMO Uploading Powerpivot Model to Power BI Creating a Dashboard Uploading to Power BI Service Key message: Power BI Desktop allows you to connect to data sources beyond what powerbi.com supports – constantly working and adding new data sources Talking points: The four major categories of data source are files, databases, Azure services and other (SaaS category was removed) Power BI Desktop supports a number of data sources that other competing services do not Navigate data quickly with in-memory processing that optimizes performance Pare down datasets to only what’s needed by editing queries before data is loaded to Power BI Desktop

Questions