Using SelectColumns() To Alias Columns In DAX

A few years ago I wrote this post on how to alias columns in a table in DAX, using a combination of AddColumns() and Summarize(). The good news is that in Excel 2016/the Power BI Designer/SSAS Tabular 2016 there’s a new DAX function specifically for this purpose: SelectColumns(). Here’s an example of how it can be used:

Imagine you have the following source table, called Products:


You can write a DAX query to get all the rows and columns from this table like so:


Here’s the output of that query in DAX Studio (and remember, DAX Studio can connect to data loaded into the Power BI Designer, which is what I’m doing here):


You can alias the columns in this table using SelectColumns() very easily, like so:

    "Column One", Products[Product],
    "Column Two", Products[Colour]

Here’s the output:


The syntax for SelectColumns() is straightforward: the first parameter is a table expression, and after that there are pairs of parameters consisting of:

  • A new column name
  • An expression returning a column from the table given in the first parameter

As you can see in the output of the query above, I’ve renamed the Product column “Column One” and the Colour column “Column Two”.

This means I can now crossjoin a table with itself without needing to worry about conflicting column names, like so:

        "Column One", Products[Product],
        "Column Two", Products[Colour]


One other interesting thing to note about SelectColumns() is that it allows you to do projection in a DAX query easily – as Marco notes here, it was possible before but it wasn’t pleasant. For example, the query:

    "Just Colour", Products[Colour]



Notice how there are three rows in the output here and that the value Green occurs twice. If you’re a true DAX afficionado, you might get excited about that.

Thoughts On All The Recent Power BI/SQL Server 2016 BI/Excel 2016 News

The last few weeks have seen more Microsoft BI-related announcements in a short time than I can ever remember before. Some of them I’ve blogged about; most I’ve at least tweeted. For good summaries of what’s coming for Power BI, on-premises SQL Server BI and Excel 2016 I can recommend the following posts by other people, all of which are worth reading:

Even then I’m not sure everything has been covered, and because new stuff is coming thick and fast (custom regions in Power Map! DirectQuery/ROLAP in the cloud with Power BI connecting to Azure SQL Database!) it’s hardly worth trying. However, I do think this is as good a point as any to work out what I think about all this activity and where Microsoft is heading.

SSAS Multidimensional Improvements

I’m well past the stage of feeling angry about the neglect of SSAS Multidimensional over the past few years, and I’m genuinely grateful that it’s getting some investment rather than nothing at all. That said, I’m not sure which customers asked for Netezza support or DBCC – they aren’t things I’ve ever needed. The promised performance improvements are where I expect the real value to be, and on their own they will probably give existing customers reason enough to upgrade to 2016. It would have been nice to get even one new feature from this list though.

SSAS Tabular Improvements

As expected, the Tabular engine in SSAS 2016 gets a lot of new stuff for free because of its shared heritage with other Power BI tools. My feeling is that uptake of Tabular has been slower than it should have been because 2012 was, frankly, a bit v1.0 with all the immaturity that implies, and there haven’t been any substantial improvements since then. With 2016, though, it looks like Tabular will take a great leap forward and as a result be seen as a much more capable platform. There will certainly be fewer reasons to choose Multidimensional over Tabular, although for applications that require complex calculations (such as financial applications) Multidimensional will still have the upper hand. The more reasons I have to love Tabular, the less I’ll worry about the lack of new features in Multidimensional.

Power Query And The Corporate/Self-Service BI Crossover

As regular readers of this blog may have noticed, I like Power Query a lot and I’m pleased to see that it has extended its reach into corporate BI. Power Query as a data source for SSAS will be important for scenarios where Power Pivot models are upgraded to server-side solutions; I don’t think it will be a good idea to use Power Query if you’re building an SSAS solution from scratch though. Power Query in SSIS was another predictable development and one which should make it easier to work with certain data sources (such as Excel files); the existing ability to publish the output of an SSIS package as an OData feed using the Data Streaming Destination, which can then be consumed by Power Query, could open up some interesting scenarios where a user builds a data set in Power Query and publishes it via SSIS for consumption by other Power Query users.

It’s the promised integration of Power Query and SSRS that excites me most though. I asked for it here and it looks like my wish has been granted! As well as providing access to a wider range of data sources and a common ‘get data’ experience with other tools, I think it will be the key to making SSRS and in particular Report Builder the self-service BI tool that so many customers want it to be. Report Builder has struggled with two problems since it first appeared: first, make it easier for users to lay out a nice-looking report on a canvas, something that the current version does a reasonable job of I think; and second, make it easy for non-technical users (who, for example, might have little or no SQL knowledge) to get data from data sources for their reports – this is where it has not succeeded in the past, and where Power Query could make all the difference. Power Query, among other things, is a solid, user friendly, SQL generation tool. This, plus the fact that SSRS will be updated for all modern browsers and get new visualisations and report themes etc, means that the vast number of existing SSRS customers will have a lot of good reasons to upgrade to 2016, and when they do they’ll also find it easy to integrate with the rest of Power BI.

Power BI: Will Anyone Buy It?

It’s very easy for Microsoft BI fanboys like me to get all worked up by the constant drip feed of tweets about new Power BI features. An impartial observer will point out that some of these features, like the ability to change the colours of your charts in Power View, are actually things we should be embarrassed at not having already. Nonetheless I think it’s fair to say that Microsoft are doing a good job of getting its core customers excited about Power BI and there’s also a lot of evidence that people outside this core at, at least, curious, so from a marketing perspective everything’s going well.

Even if the marketing is good, that will only get Power BI evaluated. Those evaluations will only turn into purchases if the product itself is up to the task. Microsoft set itself an extremely difficult task when it decided to change the direction of Power BI and deliver a respectable version 1.0 this year; the impressive speed that new features are arriving at suggests that they will manage it. When this product is put side-by-side with competing tools it will have some advantages – Power Query is excellent, the Power Pivot engine is fast and can handle all kinds of complex calculations – but will inevitably appear immature in other respects such as visualisation. I think the limit on the amount of data that can be held in a single data model, either on the desktop or in the cloud, is also something that will be a problem for those of us who are used to building server-side SSAS solutions that can hold all the data the user ever needs to see. Maybe DirectQuery/ROLAP on SQL Azure and perhaps Azure SQL Data Warehouse will make this irrelevant? Overall though in my opinion the version of ‘new’ Power BI that will RTM later this year will be seen as more than good enough from a technical standpoint, and if this rate of change is maintained for version 2.0 then it will be something special.

I also think that the focus on building APIs and connectors to other web services is a really clever move. There are a lot of other vendors out there who don’t want to build their own BI functionality, and if Microsoft can convince them to use Power BI that will bring a lot of customers on board. Even at this early stage it looks like Microsoft is doing a good job of recruiting these vendors (SQL Sentry for example, but there are many others) as well as getting other teams inside Microsoft (like Visual Studio Online) to do the same. Close integration with new Microsoft services like Azure Stream Analytics and Azure SQL Data Warehouse should have a similar effect, although less pronounced given that these new services will have few users initially.

While I admit the divorce from Excel was the right thing to do in the circumstances, I still find that I prefer working in Excel over the Power BI Dashboard Designer. Maybe that’s partly due to habit, but Power View still has a long way to go before it has the flexibility of Excel PivotTables and especially cube formulas. That’s why I think Marco Russo’s campaign to create an API for the Dashboard Designer and to support external connections from Excel and other tools is so important. If you haven’t voted already, please do so now! This would be a killer feature in that it would allow you to continue to build reports in Excel (maybe 32-bit) while still making use of new features in the engine. It would give use all the good things we have today with the Excel Power add-ins and more. It would also, as Marco points out, be another reason for third party vendors to use the Power BI platform.

The final factor to consider is price. Making the Dashboard Designer free is important, because it’s not just a Dashboard Designer but a complete, standalone desktop self-service BI solution in itself. Many customers will use it as such without buying a Power BI subscription – that is, if they know that is an option. The free/$9.99 cloud subscription model is also very attractive, and all in all the new pricing model is a refreshing change from the nightmare that ‘old’ Power BI licensing was. I wonder if there will be any particular incentives (financial or otherwise) for partners to sell or recommend Power BI to their customers? If not,there probably should be.


Overall, I’m happier with the direction that Microsoft BI is going in than I have been for a long time. Power BI now seems like it has some momentum behind it, and that it is a coherent product rather than a collection of (individually impressive) tools bound into Excel that, for one reason or another, customers couldn’t use to their full potential. We’ll have to see whether it does become a commercial success or not but I think it has a good chance of doing so now. Excel 2016 also has some welcome improvements, even if it is now the ‘slow track’ for self-service BI; the more users discover Power Pivot and Power Query via Excel 2013 and soon 2016, the more likely it is that they’ll start using the rest of the Power BI stack.

Meanwhile it seems like at last there is at last a serious commitment to improve the on-premises SQL Server BI stack on the part of Microsoft. Some time ago I wrote a post on why corporate BI and self-service BI are both necessary and I still stand by what I said there; it’s also clear that a lot of customers, especially enterprise customers and especially in Europe, are not yet ready to put their most valuable data in the cloud. Microsoft has the chance to be one of the few vendors with great self-service and corporate BI stories, and great on-premises and cloud BI stories. Also, given that today’s SQL Server BI customers are the most likely to become tomorrow’s Power BI customers, keeping them happy in the medium term while Power BI matures should be a priority.

Let’s see where we are this time next year…?

Power Query Announcements At The PASS BA Conference

There were a couple of big (well, big if you’re a Power Query fan like me) announcements made today by Miguel Llopis at the PASS BA Conference:

  • Today Power Query is available only to people who have Excel Professional Plus or Excel standalone, but as of May a version of Power Query will be available on every Excel SKU. There will be some limitations around data sources that are supported if you don’t have Excel Professional Plus, but that’s ok – this change will make it much easier for people to learn about and use Power Query, and I’m really happy about that.
  • Other new features coming in the May update of Power Query include the ability to turn off prompts about native database queries (useful in this scenario, for example), OData v4.0 support, the ability to use alternative Windows credentials to run queries, and a couple of new transformations such as removing empty rows.
  • Excel 2016 – where Power Query is now native to Excel – will have support for creating Power Query queries using VBA and macro recording. I understand you won’t be able to edit individual steps in a query, but you’ll be able to create and delete queries programmatically and change where they load their data too.
  • Excel 2016 will also support undo/redo for Power Query and give you the ability to copy/paste queries (even from workbook to workbook).
  • There was a commitment that Power Query in Excel 2016 will keep getting updates on a regular basis, rather than get tied to the much slower Office release cycle, so it retains parity with the Power Query functionality in the Power BI Dashboard Designer.

All very cool stuff!

Documentation For New Excel 2016 DAX Functions

Microsoft has published documentation for the new DAX functions in the Excel 2016 preview here:

There’s a lot of detail, including examples (although the ConcatenateX() page isn’t live at the time of writing – but I’ve blogged about that already), so it’s well worth reading through.

NaturalInnerJoin And NaturalLeftOuterJoin DAX Functions In Excel 2016

Continuing my series on new DAX functions in Excel 2016, here are two more: NaturalInnerJoin() and NaturalLeftOuterJoin(). Both do pretty much what you’d expect.

Consider the following two tables in an Excel worksheet, called ColourFruit and FruitPrice:


With these tables loaded into the Excel Data Model as linked tables, the next step is to create a relationship between the tables on the Fruit column:


Both functions only work with two tables that have an active relationship between them, and both take two tables from the Excel Data Model as parameters. Once you’ve done that you can use these functions in a DAX query.

The queries

evaluate naturalinnerjoin(ColourFruit,FruitPrice)


evaluate naturalinnerjoin(FruitPrice,ColourFruit)

…both perform an inner join between the two tables on the Fruit column and both return the same table:


The query

evaluate naturalleftouterjoin(ColourFruit,FruitPrice)



The query

evaluate naturalleftouterjoin(FruitPrice,ColourFruit)



For NaturalLeftOuterJoin() the table given in the first parameter is on the left-hand side of the left outer join, so all rows from it are returned, whereas the table in the second parameter is on the right-hand side of the join so only the matching rows are returned.

ConcatenateX() DAX Function In Excel 2016

This is the first of many posts on the new DAX functions that have appeared in Excel 2016 (for a full list see this post). Today: the ConcatenateX() function.

The mdschema_functions schema rowset gives the following description of this function:

Evaluates expression for each row on the table, then return the concatenation of those values in a single string result, separated by the specified delimiter

Its signature is:

CONCATENATEX(Table, Expression, [Delimiter])

It’s easier to understand what it does using a simple example though. Consider the following table on a worksheet in Excel 2016:


When you add this table to the Excel Data Model (I called the table Sales) you can add the following measure:

Purchasing Customers:=

If you then use this measure in a PivotTable, you see the following:


As you can see, the measure returns a comma-delimited list of all of the customers who have bought each product. Very useful…

What’s New In The Excel 2016 Preview For BI?

Following on from my recent post on Power BI and Excel 2016 news, here are some more details about the new BI-related features in the Excel 2016 Preview. Remember that more BI-related features may appear before the release of Excel 2016, and that with Office 365 click-to-run significant new features can appear in between releases, so this is not a definitive list of what Excel 2016 will be able to do at RTM but a snapshot of functionality available as of March 2015 as outlined in this document and which I’ve found from my own investigations. When I find out more, or when new functionality appears, I’ll either update this post or write a new one.

Power Query

Yesterday, in the original version of my post, I mistakenly said that Power Query was a native add-in in Excel 2016: that’s not true, it’s not an add-in at all, it’s native Excel functionality. Indeed you can see that there is no separate Power Query tab any more, and instead there is a Power Query section on the Data tab instead:


Obviously I’m a massive fan of Power Query so I’m biased, but I think this is a great move because it makes all the great Power Query functionality a lot easier to discover. There’s nothing to enable – it’s there by default – although I am a bit worried that users will be confused by having the older Data tab features next to their Power Query equivalents.

There are no new features for Power Query here compared to the latest version for Excel 2013, but that’s what I expected.

Excel Forecasting Functions

I don’t pretend to know anything about forecasting, but I had a brief play with the new Forecast.ETS function and got some reasonable results out of it as seen in the screenshot below:


Slicer Multiselect

There’s a new hammer icon on a slicer, which, when you click it, changes the way selection works. The default behaviour is the same as Excel 2013: every time you click on an item, that item is selected and any previous selection is lost (unless you were holding control or shift to multiselect). However with the hammer icon selected each new click adds the item to the previously selected items. This is meant to make slicers easier to use with a touch-screen.


Time Grouping in PivotTables

Quite a neat feature this, I think. If you have a table in the Excel Data Model that has a column of type date in it, you can add extra calculated columns to that table from within a PivotTable to group by things like Year and Month. For example, here’s a PivotTable I built on a table that contains just dates:


Right-clicking on the field containing the dates and clicking Group brings up the following dialog:


Choosing Years, Quarters and Months creates three extra fields in the PivotTable:


And these fields are implemented as calculated columns in the original table in the Excel Data Model, with DAX definitions as seen here:


Power View on SSAS Multidimensional

At-bloody-last. I haven’t installed SSAS on the VM I’m using for testing Excel 2016, but I assume it just works. Nothing new in Power View yet, by the way.

Power Map data cards

Not sure why this is listed as new in Excel 2016 when it seems to be the same feature that appeared in Excel 2013 Power Map recently:

Power Pivot

There isn’t any obvious new functionality in the Power Pivot window, but it’s clear that the UI in general and the DAX formula editor experience in particular has been improved.


Suggested Relationships

When you use fields from two Excel Data Model tables that have no relationship between them in a PivotTable, you get a prompt to either create new relationships yourself or let Excel detect the relationships:


Renaming Tables and Fields in the Power Pivot window

In Excel 2013 when you renamed tables or fields in the Excel Data Model, any PivotTables that used those objects had them deleted. Now, in Excel 2016, the PivotTable retains the reference to table or field and just displays the new name. What’s even better is that when you create a measure or a calculated column that refers to a table or column, the DAX definition of the measure or calculated column gets updated after a rename too.


There are lots of new DAX functions in this build. With the help of the mdschema_functions schema rowset and Power Query I was able to compare the list of DAX functions available in 2016 with those in 2013 and create the following list of new DAX functions and descriptions:

DATEDIFF			Returns the number of units (unit specified in Interval) 
			between the input two dates
CONCATENATEX		Evaluates expression for each row on the table, then 
			return the concatenation of those values in a single string 
			result, separated by the specified delimiter
KEYWORDMATCH		Returns TRUE if there is a match between the 
			MatchExpression and Text. 
ADDMISSINGITEMS		Add the rows with empty measure values back.
CALENDAR			Returns a table with one column of all dates between 
			StartDate and EndDate 
CALENDARAUTO		Returns a table with one column of dates 
			calculated from the model automatically
CROSSFILTER		Specifies cross filtering direction to be used in 
			the evaluation of a DAX expression. The relationship is 
			defined by naming, as arguments, the two columns that 
			serve as endpoints
CURRENTGROUP		Access to the (sub)table representing current 
			group in GroupBy function. Can be used only inside GroupBy 
GROUPBY			Creates a summary the input table grouped by the 
			specified columns
IGNORE			Tags a measure expression specified in the call to 
			SUMMARIZECOLUMNS function to be ignored when 
			determining the non-blank rows.
ISONORAFTER		The IsOnOrAfter function is a boolean function that 
			emulates the behavior of Start At clause and returns 
			true for a row that meets all the conditions mentioned as 
			parameters in this function.
NATURALINNERJOIN		Joins the Left table with right table using the 
			Inner Join semantics
NATURALLEFTOUTERJOIN	Joins the Left table with right table 
			using the Left Outer Join semantics
ROLLUPADDISSUBTOTAL		Identifies a subset of columns specified 
			in the call to SUMMARIZECOLUMNS function that should be 
			used to calculate groups of subtotals
ROLLUPISSUBTOTAL		Pairs up the rollup groups with the column 
SELECTCOLUMNS		Returns a table with selected columns from the table 
			and new columns specified by the DAX expressions
SUBSTITUTEWITHINDEX		Returns a table which represents the semijoin of two 
			tables supplied and for which the common set of 
			columns are replaced by a 0-based index column. 
			The index is based on the rows of the second table 
			sorted by specified order expressions.
SUMMARIZECOLUMNS		Create a summary table for the requested 
			totals over set of groups.
GEOMEAN			Returns geometric mean of given column 
GEOMEANX			Returns geometric mean of an expression 
			values in a table.
MEDIANX			Returns the 50th percentile of an expression 
			values in a table.
PERCENTILE.EXC		Returns the k-th (exclusive) percentile of 
			values in a column.
PERCENTILE.INC		Returns the k-th (inclusive) percentile of 
			values in a column.
PERCENTILEX.EXC		Returns the k-th (exclusive) percentile of an 
			expression values in a table.
PERCENTILEX.INC		Returns the k-th (inclusive) percentile of an 
			expression values in a table.
PRODUCT			Returns the product of given column reference.
PRODUCTX			Returns the product of an expression 
			values in a table.
XIRR			Returns the internal rate of return for a schedule of 
			cash flows that is not necessarily periodic
XNPV			Returns the net present value for a schedule of cash flows

Plenty of material for future blog posts there, I think – there are lots of functions here that will be very useful. I bet Marco and Alberto are excited…


We now have support for working with Power Query in VBA.