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  • Basket Analysis with #dax in #powerpivot and #ssas #tabular

    A few days ago I published a new article on DAX Patterns web site describing how to implement Basket Analysis in DAX. This topic is a very classical one and is also covered in the many-to-many revolution white paper. It has been also discussed in several blog posts, listed here in historical order: Simple Basket Analysis in DAX by Chris Webb ...
    Posted to SQLBI - Marco Russo (Weblog) by sqlbi on June 12, 2014
  • SQLBits XI in May 2013 – many reasons to attend! #sqlbits #dax #tabular

    I and Alberto Ferrari will speak at SQLBits XI (Nottingham, UK – May 2-4, 2013) and there are many good reasons to join us there, especially if you are interested to DAX! Here are our sessions: Thursday, 02 May 2013 – Training Day - From 0 to DAX The entire day is dedicated to learning DAX, starting from the syntax and going forward ...
    Posted to SQLBI - Marco Russo (Weblog) by sqlbi on February 20, 2013
  • Order of Evaluation in CALCULATE and Clever Hierarchy Handling in #dax

    After the first two editions of the SSAS Tabular Workshop, I and Alberto had some time to flush some of the pending activities. We published two articles: Clever Hierarchy Handling in DAX: DAX is not a hierarchy-friendly language, especially if you have a MDX background. If you have to implement hierarchy-based calculation, MDX is still ...
    Posted to SQLBI - Marco Russo (Weblog) by sqlbi on May 2, 2012
  • Distinct Count of Customers in a SCD Type 2 in #DAX

    If you have a Slowly Changing Dimension (SCD) Type 2 for your customer and you want to calculate the number of distinct customers that bought a product, you cannot use the simple formula: Customers := DISTINCTCOUNT( FactTable[Customer Id] ) ) because it would return the number of distinct versions of customers. What you really want to do is to ...
    Posted to SQLBI - Marco Russo (Weblog) by sqlbi on April 9, 2012
  • Using SQL to query Multidimensional and Tabular models #dax #sql #mdx #ssas

    Analysis Services answers to query in MDX, in DAX (by now just for Tabular models) and has a limited capability to answer SQL queries. It is not useful for any development or client tool, but I wanted to write a blog post on it in order to be able to retrieve these information I gathered during study of DAX and MDX queries sent to Tabular ...
    Posted to SQLBI - Marco Russo (Weblog) by sqlbi on January 12, 2012
  • Fact Tables with Different Granularities in #PowerPivot and #BISM #Tabular

    A few weeks ago I received a question that inspired me in writing this article about how to handle data at different granularities in PowerPivot and BISM Tabular. I think this is a common pattern when you have a budget table that contains data at an aggregated level (like month and product category) and you want to compare it with sales that are ...
    Posted to SQLBI - Marco Russo (Weblog) by sqlbi on January 11, 2012
  • Query Projection in #DAX

    I wrote a short article about query projection in DAX. To make the story short, you should always use SUMMARIZE in order to remove columns from a table in a query. Thus, if you just want three columns from a table, instead of writing this in SQL: SELECT Col1, Col2, Col3 FROM Table you should write this in DAX: EVALUATE SUMMARIZE( Table, ...
    Posted to SQLBI - Marco Russo (Weblog) by sqlbi on December 29, 2011
  • #DAX Query Plan in SQL Server 2012 #Tabular

    The SQL Server Profiler provides you many information regarding the internal behavior of DAX queries sent to a BISM Tabular model. Similar to MDX, also in DAX there is a Formula Engine (FE) and a Storage Engine (SE). The SE is usually handled by Vertipaq (unless you are using DirectQuery mode) and Vertipaq SE Query classes of events gives you a ...
    Posted to SQLBI - Marco Russo (Weblog) by sqlbi on November 21, 2011
  • PowerPivot, basket analysis and the hidden many to many

    Surfing on the web, here, I came into this intriguing question: How do we ask something like ''Show me how many customers have an iPad but don't have a book?'' We are speaking about a sales analysis where the canonical entities are Customers, Products and Sales. Moreover, because we have been used to speak about cycles since many years ago, ...
    Posted to Alberto Ferrari (Weblog) by AlbertoFerrari on May 19, 2011
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