PowerPivot Workbook Size Optimizer

Browsing through my RSS feeds this morning, I saw a new download on the Microsoft site: an Excel addin (Excel 2013 only, I think) called the PowerPivot Workbook Size Optimizer. You can get it here:

Here’s the blurb from the site:

The Workbook Size optimizer for Excel can better compress data inside workbooks that use PowerPivot or PowerView if this data comes from external data sources. The best size compression can be achieved for workbooks based on SQL Server databases and there are a few tricks we can do for other SQL datasources as well. The optimizer will install as an add in to excel and will provide you with a nice wizard to better compress the size of your workbook. Using the optimizer you can often get more than 1,000,000 rows datasets in a workbook under 10 MB, share it in SharePointOnline and interact withit using the Excel Web App in any browser.

Here’s a screenshot:


Despite a testing a few models with data from Adventure Works I couldn’t get it to suggest any changes (it didn’t spot that I had imported a column containing binary data, hmmm) but I guess it needs more testing on larger/more diverse data sources. Maybe there’s a blog post coming from the PowerPivot team coming soon explaining how to use this?

UPDATE: after playing around with it a bit more, I was able to get it to suggest some changes to tables. Marco has some more details:

And there’s a white paper on the rules that it uses:

A Partly Successful Attempt To Create Life With Data Explorer (Power Query)

NOTE: This post was written before Data Explorer was renamed as Power Query. All of the content is still relevant to Power Query.

I’ll apologise for the title right away: this post isn’t about a Frankenstein-like attempt at creating a living being in Excel, I’m afraid. Instead, it’s about my attempt to implement Jon Conway’s famous game ‘Life’ using Data Explorer, how it didn’t fully succeed and some of the interesting things I learned along the way…

When I’m learning a new technology I like to set myself mini-projects that are more fun than practically useful, and for some reason a few weeks ago I remembered ‘Life’ (which I’m sure almost anyone who has learned programming has had to write a version of at some stage), so I began to wonder if I could write a version of it in Data Explorer. This wasn’t because I thought Data Explorer was an appropriate tool to do this – there are certainly better ways to implement Life in Excel – but I thought doing this would help me in my attempts to learn Data Explorer’s formula language and might also result in an interesting blog post.

Here’s the code I came up with eventually:


    Source = Excel.CurrentWorkbook(){[Name="Input"]}[Content],

    GetAction = Excel.CurrentWorkbook(){[Name="Source"]}[Content]{0}[Source],

    GetLastOutput = try Excel.CurrentWorkbook(){[Name="Output"]}[Content],

    ChooseInput = if GetAction="Input" or GetLastOutput[HasError]

        then Source else GetLastOutput[Value],

    Unpivot = Table.Unpivot(ChooseInput,{"1", "2", "3", "4", "5", "6"

        , "7", "8", "9", "10"},"Column","Value"),

    InsertedIndex = Table.AddIndexColumn(Unpivot,"Index"),

    PivotedRows = Table.RowCount(InsertedIndex),

    OriginalColumnCount = Table.ColumnCount(ChooseInput),

    GetValue = (i) =>; if i<0 or i>=PivotedRows then 0 

        else InsertedIndex[Value]{i},

    GetNeighbours = (i) =>; GetValue(i-1) + GetValue(i+1) 

        + GetValue(i-OriginalColumnCount) + GetValue(i+OriginalColumnCount)

        + GetValue(i-OriginalColumnCount-1) + GetValue(i-OriginalColumnCount+1)

        + GetValue(i+OriginalColumnCount-1) + GetValue(i+OriginalColumnCount+1),

    NeighbourCount = Table.AddColumn(InsertedIndex, "Neighbours",

        each GetNeighbours([Index])),

    Custom1 = Table.AddColumn(NeighbourCount , "NewValue",

        each if [Value]=1 and ([Neighbours]=2 or [Neighbours]=3)

        then 1 else if [Value]=0 and [Neighbours]=3 then 1 else 0),

    HiddenColumns = Table.RemoveColumns(Custom1,{"Value", "Index", "Neighbours"}),

    Custom2 = Table.Group(HiddenColumns, {"Column"},

        {{"Count", each Table.Transpose(Table.RemoveColumns(_,"Column")), type table}}),

    #"Expand Count" = Table.ExpandTableColumn(Custom2, "Count", {"Column1", "Column2"

        , "Column3", "Column4", "Column5", "Column6", "Column7", "Column8", "Column9"

        , "Column10"}, {"1", "2", "3", "4", "5", "6", "7", "8", "9","10"}),

    HiddenColumns1 = Table.RemoveColumns(#"Expand Count",{"Column"})



You can download the associated Excel 2013 workbook here.

Some explanation of the code:

  • The first problem that I faced was that in Life you need to start with a grid of cells, apply the rules of the game, and then output the results to the same grid. This is a problem for Data Explorer because, unless you have already run a query, the output table doesn’t exist, and even if you have you can’t update the values in that table without them being overwritten. So I decided to create a table where you can enter the initial state of your grid as a series of 1s and 0s. It’s on the Input sheet and its called Input:


  • Whether the Input table is used as the starting point for the query depends on the contents of yet another table, called Source, on the sheet called Output in the workbook. It can hold one of two text values: “Input” or “Output” (I used Excel’s Data Validation functionality to lock this down), and the ChooseInput step then determines whether the Input table or the table called Output is used as the input for the Data Explorer query. Here’s what the Output worksheet looks like:image

    The workflow is therefore as follows: enter the starting point on the Input table, make sure the Source table shows “Input”, refresh the query, change the Source table to “Output” and then refresh the query to show each subsequent iteration.

  • The Output table simply displays the same values as the table that shows the results of the Data Explorer query. I created a separate table for two reasons: one, I wanted to use custom formatting to show the results; and two, to try to work around the big problem that I eventually found I couldn’t work around completely, which is that Data Explorer doesn’t actually support this type of recursive query (ie scenarios where the output of a query is also used as the input). This thread on the Data Explorer MSDN Forum has some details on the problem. I found I got errors after just about every other step when using the Data Explorer-created table as the input, whereas the errors were much less frequent if I duplicated the values in a separate table. It now works most of the time, but it still errors far too much for my liking. Hohum.
  • I did also use Data Explorer’s error-handling functionality, using the try statement in the GetLastOutput step, to solve this problem but it made no difference. It was good to find out how a try statement works: basically when you use it, the return value is a record containing two values, one which indicates whether an error occurred in the try, and the other the value that was returned if there was no error. You can see me checking these values in the ChooseInput step, with the calls to GetLastOutput[HasError] (which returns true if there was an error in the try) and GetLastValue[Value] (which returns the value tested in the try if there was no error).
  • Once the query worked out which input to use, the next step is to calculate the values in the grid for the next iteration. I decided that the easiest way to do this was to unpivot the resultset using the the new UnPivot() function; with all the data in a single column it was then relatively easy to declare the functions GetValue() and GetNeighbours() to apply the rules of Life, output the results in a new column in the Custom1 step.
  • The final problem to solve was that I needed to re-pivot the data to get it back into original table format. Although Data Explorer has an UnPivot() function it doesn’t have a Pivot() function; luckily, Peter Qian showed me how to do this on the forum in this thread using Table.Group() and my code is in the Custom2 step.

So despite the errors (and Data Explorer is still in beta, so some errors are only to be expected), many lessons learned. I hope you find this useful too.

SSAS on Windows Azure Virtual Machines

You may have already seen the announcement about Windows Azure Virtual Machines today; what isn’t immediately clear (thanks to Teo Lachev for the link) is that Analysis Services 2012 Multidimensional and Reporting Services are installed on the new SQL Server images. For more details, see:

SSAS 2012 Tabular is also supported but not initially installed.

Applying a Function to Every Cell in a Table in Data Explorer (Power Query)

NOTE: This post was written before Data Explorer was renamed as Power Query. All of the content is still relevant to Power Query.

Now that the PASS Business Analytics Conference is over, I can get back to playing around with Data Explorer and blogging about it. I’ve been working on a fun demo that I’ll try to blog about later this week, but in the course of creating this demo I came across a technique that I didn’t end up using but which I thought deserved a post on its own: how to apply a function to every cell in a table, rather than just every cell in a column.

For example, let’s imagine that you have a table that looks like this:


…and you want to add one to every single cell in the table, so you get:


It’s possible in the UI by creating lots of custom columns and then deleting the original columns, for sure, but I found a more elegant solution. Here’s the full DE code:


    Source = Excel.CurrentWorkbook(){[Name="Input"]}[Content],

    FunctionToApply = (x) =>; x + 1,

    GetColumnNames = Table.ColumnNames(Source),

    TransformList = List.Transform(GetColumnNames, each {_ , FunctionToApply}),

    Output = Table.TransformColumns(Source, TransformList)



Here’s what each step does:

  • Source: gets the data from the Excel table named Inputimage
  • FunctionToApply: defines a new function that takes a single parameter, x, and returns the value x+1. See this post for more details on using function in Data Explorer.image
  • GetColumnNames: returns a list object which contains the names of all of the columns in the table returned in the Source step.image
  • TransformList: this is the interesting step! It creates a new list based on GetColumnNames, but whereas GetColumnNames contains just one record per item in the list (the column name), this returns a list of lists, each with two items: the column name and a reference to the function FunctionToApply. It looks like this in the UI:imageIf you click on the first of the list links shown (and this isn’t part of the process, I’m only doing this to show what’s there) you see the following:


  • Output: the list of lists created in the previous step can now be passed to the Table.TransformColumns() function to apply the function FunctionToApply() to every cell in every column in the table.image

I’m sure this is going to be useful to me at some point in the future… You can download the sample workbook here.

PASS Business Analytics Conference Summary

The PASS Business Analytics Conference in Chicago finished yesterday, and because I was there and because I did a fair amount of cheerleading for it (see here and here for example) I wanted to post a few thoughts on how it went.

I’ll be honest and say that I had a few worries before the event. Would anyone want to go? Would the sessions be a repeat of what get on the BI tracks at the PASS Summit and hundreds of other SQL Server conferences? In fact, everything went really, really well. Some of the sessions were quite sparsely attended (though this had nothing to do with the quality of the content – some of the best sessions didn’t get much of an audience) but overall there was a very respectable number of people (1200ish?). I had as many people in my session on OData as I’d get at any other large conference, and it was standing room only in at least one of Marco’s sessions. I also rather liked the fact that it was smaller than the Summit – it made it much easier to meet all the people I wanted to meet. If it carries on for a few years it could easily attract a much larger number of people.

Regarding the content I was particularly pleased because a lot of the topics I’d asked for turned up on the schedule. In fact one thing that struck me (and a few other people said the same thing to me as well) was that this was the first conference I’d been to in a long time where there were sessions that I really wanted to see in every time slot. My favourite session of the whole conference was Marc Smith on NodeXL; anyone that reads my blog knows I’ve been a big fan of NodeXL for a long time, but I learned a lot from this session because it concentrated on the basics of social network analysis rather than the tool itself. This was a prime example of the kind of topic that you simply wouldn’t get at a regular SQL Server conference – it was a business analytics session. Even the more technical presentations, such as the one on HPC Services for Excel, was outside the usual boundaries of SQL Server BI. Incidentally, I must get round to playing with HPC Services for Excel – you could use it to parallelise some DAX calculations, or even to batch process large numbers of PowerPivot models on desktop machines overnight…

So, in summary, the conference was a big success and I had a great time. I’ll definitely be going back next year. And did I mention that I got to meet Steven Levitt of Freakonomics fame?

GeoFlow Public Preview Available

First big news from the PASS BA Conference: the public preview for GeoFlow is now available. You can download it here:

Here are the official announcements with all the details:

GeoFlow is an addin for Excel 2013 that allows you to visualise your data on a 3D map, to zoom in and explore that data, and record ‘tours’ of this data. It’s a lot of fun! As a taster, here’s a screenshot of a visualisation showing English secondary schools exam results data (average A-Level point score per pupil) broken down by school gender of entry:


UPDATE: one other thing I have to mention is that when this was announced in the keynote at the PASS BA Conference this morning, Amir Netz did an absolutely astounding demo showing GeoFlow’s touch-based capabilities running on a massive Perceptive Pixel screen (I think it was this one: http://www.perceptivepixel.com/products/82-lcd-multi-touch-display). It was possibly the most impressive demo I’ve seen of any Microsoft BI product. Anyway, I got to play on it myself later and it was as cool as it looked. If you’ve got $80000 burning a hole in your pocket then you could do worse than invest in one of these babies.