Category Archives: Self-Service BI

Esri Plus Subscription for ArcGIS Maps for Power BI is now available

Since Esri introduced ArcGIS Maps for Power BI, we’ve seen many leading organizations use it as an essential element of their data visualization strategy to get more value from their spatial data directly within Power BI. ArcGIS Maps for Power BI enables all Power BI users to easily map their data with a rich mapping data visualization powered by Esri’s ArcGIS technology.

Today, I’m happy to announce that Esri is taking ArcGIS Maps for Power BI to the next level by introducing Plus, a subscription service available for purchase from Esri that allows everyday business users in Power BI to do more with their spatial data. This capability was demonstrated for the first time at Microsoft’s Ignite 2017 conference and is now available in Power BI Desktop and the Power BI service.

Watch Esri’s great video that gives an overview of the capabilities of ArcGIS Maps for Power BI, including the new Plus Subscription features.

What is Plus? In a word: More. More basemaps, more data points, more demographics, more reference layers. It’s a step in our journey to make GIS easy to understand and consume for regular business users. Plus is inspired by many of the feature requests you have made since we introduce ArcGIS Maps for Power BI.

Let’s dig into how you get Plus and what you can get with it. To start, you’ll know Plus is available to you because there’s a new Plus icon in the ArcGIS Maps visual.

Esri Plus Subscription Offer Esri Plus Subscription for ArcGIS Maps for Power BI is now available

Plus is a subscription service you can purchase from Esri through Esri’s website. You can use the learn more link to get all the details. Once you’ve signed up, you’re connecting your user credentials to Esri’s service. This makes for a seamless experience for the Enterprise. The subscription is available at $ 5 per user per month. There’s a 60-day trial period for Plus that’s available at no cost, so you can put it through its paces.

Once you’re signed up and signed in, you’ll see new Plus capabilities identified by the Plus icon,plus icon Esri Plus Subscription for ArcGIS Maps for Power BI is now available.

Here’s a quick summary of everything you get. I’ll go into some details below as well. You can learn more at Esri’s website as well.

Included with ArcGIS Maps for Power BI

Plus subscription

Turn on the power of maps…

No cost, included with Power BI

  • Access US demographics
  • Access public maps
  • Map and view locations
  • Perform spatial analyses such as heat maps, drive times and more
  • Create easy map visualizations with four simple basemaps

Access global data…

$ 5.00 per month, per user

  • Access global demographics
  • Access verified ready-to-use data, curated from authoritative sources
  • Map and view more locations, up to 5,000 address geocodes per map instance, and up to one million per month per user
  • Access 12 basemaps such as satellite imagery, oceans, and terrain to create compelling visualizations that give perspective and impact decisions
  • Conduct the same spatial analyses as Included with ArcGIS Maps for Power BI

Let’s start with more street address geocoding data points, up to 5,000 data points per map instance. One of the major requirements we’ve heard is that often business users want to geocode many street addresses. While at some point it makes sense to incorporate pre-geocoded data into your dataset for speed and predictability, Plus allows you to geocode more street address data points on the fly. This allows you to push mapping even further than previously possible with ArcGIS Maps for Power BI.

One important aspect of showing data on a map is the basemap that underlies the data points. These base maps provide important cues to help relate data points to the environment they reside within. With a Plus subscription, Power BI users get access to 8 additional base map types including topographic, imagery, terrain, and oceans. This means more kinds of analysis can be readily performed in Power BI.

Basemaps Esri Plus Subscription for ArcGIS Maps for Power BI is now available

With Plus you get access to Esri’s catalog of worldwide demographics for use as infographic cards. These data points are often critical to understanding the deeper context of your business data. With Plus, customers get a richer set of demographics in categories like Age, Behaviors, Spending, Keyfacts, Population, and many more. There are really too many to mention in this blog so I recommend you explore them in Power BI.

World demographics Esri Plus Subscription for ArcGIS Maps for Power BI is now available

The reference layers included in Plus are richer as well. Under the new Living Atlas tab, you’ll find layers curated by Esri for each country in the world. You’ll be able to add those to your map and then use them to select data points. For some countries you’ll even find topical reference layers like North American Ecoregions. So, you’ll want to explore the options and see the possibilities they present for a richer experience for your business users.

Reference layer living atlas Esri Plus Subscription for ArcGIS Maps for Power BI is now available

At this point you might be wondering how does this work with your existing ArcGIS Maps for Power BI. Importantly, the free (‘included’) ArcGIS Maps for Power BI continues to be available to you at no cost when you’re using Power BI. If you use a Plus features in a map and share it with other Power BI users, they’ll need a Plus subscription to view the map.

We’re really excited that Esri has introduced Plus, so Power BI users get more value from their spatial data. We’re looking forward to seeing how you use ArcGIS Maps for Power BI together with an Esri’s Plus subscription to make better decisions.

Next Steps:

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Jittered Scatter Charts in Power BI via DAX and Power Query

In a recent post, I hinted that I’d be using theFootball Project V2 as my “platform” for some future techniques-oriented posts.  That future starts today!  And while I certainly have enjoyed writing my more change-management-oriented posts this year like this one and this one, it’s good for me to still get my hands dirty a bit from time to time.

Besides, there’s a certain “back to our roots” quality to be found when I write DAX and M posts.  That’s how it all started here.

In that previous post about the football project, I showed you a report without explaining any of it.  In particular, the “football field” scatter chart representation of a passing chart served as the focal point, and it’s a pretty “hot” visual…

image thumb 2 Jittered Scatter Charts in Power BI via DAX and Power Query

This Post is Primarily About How I “Jittered” the Highlighted Cluster of Dots to make Said Dots More Visible

image thumb 3 Jittered Scatter Charts in Power BI via DAX and Power Query

I can’t make this PBIX downloadable since it contains intellectual property of Cian Fahey, but here’s a quick glance at what the primary data table contains:

image thumb 4 Jittered Scatter Charts in Power BI via DAX and Power Query

This Shows Most of the Columns of My PassData Table
(Ex: in the Second Row, Tom Brady threw an accurate pass 50 yards in the air, outside
of the numbers painted along the left side of the field.  Brandin Cooks caught it
and then ran 4 additional yards as indicated by the [YAC] column)

And here’s what that second row of data looks like when it’s ultimately plotted on my scatter chart:

image thumb 5 Jittered Scatter Charts in Power BI via DAX and Power Query

The Dot Corresponding to the 2nd Row of Data Above: 50 Yards in the Air, Outside the Numbers Left
(I don’t try to visualize the 4 yards he ran after catching it – at least not yet)

Right before I started building this visual, I’d fortunately been reading an article by my good friend Chandoo, in which he “jittered” some dots in an Excel scatter chart.

So when I encountered the problem indicated in the left side of the image above, I knew exactly what I had to do, but this time with a Power BI twist!

I know.  Many of you are probably most-interested in the underlying image part of this technique, or at least more so than you are interested in the jittering.

Not that you’re interested in football, of course, but there are MANY other cases where a custom underlying image from your business would/will be appropriate.

So let’s give it a quick treatment.  Here’s what I did:

  1. I purchased a piece of football field clipart, and trimmed it down to the size I needed (few QB’s can throw a ball more than about 57 yards in the air, so I didn’t need the entire field).
  2. I inserted a scatter chart into my report, set the background image of the plot area to be my modified clipart file, and changed the Image Fit to “Fit” rather than Normal:

image thumb 6 Jittered Scatter Charts in Power BI via DAX and Power Query

  1. I then translated the [Pass Distance] column from my data into a [PreciseY] column using a DAX calculated column (this formula assumes the [Pass Distance] column contains values ranging from –5 to 55, and maps them to a Y-value ranging from 0 to 61:

image thumb 7 Jittered Scatter Charts in Power BI via DAX and Power Query

  1. Then I used [PreciseY] as the Y Axis column in the field list:

image thumb 8 Jittered Scatter Charts in Power BI via DAX and Power Query

  1. Next, I set the Y-Axis of the Scatter Chart so that it ranged from 0 to 62 (experimentation showed me that 62 worked better than 61 – I encourage you to NOT consider this an exact mathematical science, and instead, just trust your eyes):

image thumb 9 Jittered Scatter Charts in Power BI via DAX and Power Query

  1. Lastly, I repeated a similar process to generate a [PreciseX] column, based on a related table lookup (note that I only get five different original values for “X” location, as compared to the hyper-granular and precise Y location I get from the [PassDistance] column):


image thumb 10 Jittered Scatter Charts in Power BI via DAX and Power Query

The Formula

image thumb 11 Jittered Scatter Charts in Power BI via DAX and Power Query

The XCoordLookupTable

  1. Which of course also necessitates I set the range of the X axis of the chart as well.  Note that I used 0-100 even though my [PreciseX] only goes from 10-91, because I do NOT want dots appearing on the far right and left edges, as that would place them “out of bounds” from a football perspective:

image thumb 12 Jittered Scatter Charts in Power BI via DAX and Power Query

OK, that sets up our problem nicely – our dots are going to be pretty well-spaced by default along the Y-axis, but the small number of distinct values of X is going to lead to some serious “clobbering.”

And since we have a “bigger” problem on the X axis, that is the one I chose to jitter, but with a slight “nod” to the Y axis as well (as you will see).

I quickly realized I needed a new column in my model, one that uniquely identified each dot.

Why is that?  Well, I want every single row of my data to get its “own” dot on the graph, and the Power BI scatter chart is quite insistent on there being such a column:

image thumb 13 Jittered Scatter Charts in Power BI via DAX and Power Query

Now, sometimes you may WANT multiple rows to combine into one dot, but in this particular case, I want to see each row of my source data as its own dot.

When adding a new calculated column, there are LOTS of ways to uniquely “stamp” each row with its own distinct value.  I could do this in DAX, but it would require concatenating/combining enough columns together (in this case, probably [Game #], [Qtr], and [Time], since no two rows can “happen” at the same time in the same game.

But for other reasons that you will see shortly, I need the unique identifier to be a number, and I don’t want to go through the contortions of converting text values to numeric, plus as you can see, the data is incomplete in the [Time] column (lots of blanks).

So I went back into the power query that fetches this data in the first place, and added an Index column:

image thumb 14 Jittered Scatter Charts in Power BI via DAX and Power Query

Add an Index Column to the Query…

image thumb 15 Jittered Scatter Charts in Power BI via DAX and Power Query

…and here it is after running said modified query!
(Not sure why I chose to start the column at zero.  Doesn’t matter, 1 would have been fine too)

Now, I drop that [Index] column on the Details dropzone of the scatter chart (as pictured a few images up), and I’m now assured of “one dot per row of data.”

We get it:  you probably arrived here via Google, and now that you’ve got what you needed, you’re leaving. And we’re TOTALLY cool with that – we love what we do more than enough to keep writing free content.  And besides, what’s good for the community (and the soul) is good for the brand.

But before you leave, we DO want you to know that instead of struggling your way through a project on your own, you can hire us to accelerate you into the future. Like, 88 mph in a flux-capacitor-equipped DeLorean – THAT kind of acceleration. C’mon McFly. Where you’re going, you won’t need roads.

Everything we’ve done so far gets me to the place where my dots are all appearing in their [PreciseX] and [PreciseY] locations, but “clobbering” each other:

image4 thumb Jittered Scatter Charts in Power BI via DAX and Power Query

Our “Story So Far” Gets Us to This Place
(Our scatter chart field list at left, dots hiding each other at right)

We need an alternate version of our [PreciseX] column, one that slightly shifts the X-position of a dot left or right to avoid clobbering its close neighbors.  Just a little nudge left or right, one that doesn’t move it TOO much.

But how do we know which dots even NEED jittering/shifting?

If a dot is completely off on its own, its X coordinate doesn’t need to be adjusted.  We only need to pay attention to dots that are clumped together.

So…  how close together is too close? I experimented a bit before coming to the following conclusion.

A “cluster” is defined by:

  • A shared [PreciseX] value, AND
  • A [PreciseY] within a 2-unit “block”

In English, what I decided was that if two dots shared a [PreciseX] and were “really close” in [PreciseY] value, they were “clobbering” each other and required jittering.

I added these two calculated columns using DAX:

image thumb 17 Jittered Scatter Charts in Power BI via DAX and Power Query

The formulas are:

DepthRange =
IF (
    [Pass Distance] < 0,
    IF ( [Pass Distance] <= 201 + INT ( [Pass Distance] / 2 ) )

Cluster =
“X: “ & [PreciseX]
    & “, Depth: “
    & [DepthRange]

DepthRange simply “compresses” pass distances into 2-yard increments.  (I could have used [PreciseY] as the input here instead of [Pass Distance], again with the “divide by two” approach – this value is never going to be displayed to the user, so it doesn’t need to be semantically meaningful, but it DOES need to “lump” similar Y coordinates together, which it does).

Cluster then merely concatenates [PreciseX] and [DepthRange] together, but in a somewhat-friendly format (which helped me to debug).

Now, I add three more columns – two intermediate columns that “build up” to the third, which is the [JitteredX] we desire:

image thumb 18 Jittered Scatter Charts in Power BI via DAX and Power Query

The formulas are:

RankWithinLocationCluster =
    FILTER ( PassData, PassData[Cluster] = EARLIER ( PassData[Cluster] ) ),

JitterXAdjustment =
    AVERAGE ( PassData[RankWithinLocationCluster] ),
    FILTER ( PassData, PassData[Cluster] = EARLIER ( PassData[Cluster] ) )
    – [RankWithinLocationCluster]

JitteredX =
    + ( [JitterXAdjustment] * 2 )

And here they are explained:

  • RankWithinLocationCluster – among all rows/dots that share a Cluster value with this dot, how does this one “rank” in terms of its [Index] value?  In this case, we’re not ranking in the “scoring” sense – the Index value is pretty damn arbitrary here, but since [Index] is numeric and unique, we can use RANKX to essentially make sure that we don’t move dots around and simply “jitter” them right back on top of one another.
  • JitterXAdjustment – ok, THEN we calculated the average of the ranks within this cluster, and subtract THIS dot’s rank within the cluster.  This yields a set of positive/negative/zero integer values, with NO duplicate values within a cluster, which allows us to shift both left and right for a nice even “spread.”  Furthermore, in clusters of size 1, we get a 0 here (no shift).  This also happens to handle odd- and even-sized clusters quite well (if you have three dots in a cluster, their ranks will average to 2, and the middle dot’s rank will be 2, so it stays put).
  • JitteredX – I then take [JitterXAdjustment], multiply it by 2 to make the “spread” a bit wider (again, an eyeball-driven adjustment), then add that to [PreciseX] to yield my NEW x-coordinate, [JitteredX].

Instead of [PreciseX], we now use [JitteredX] as the X-Axis field, as illustrated here…

image thumb 19 Jittered Scatter Charts in Power BI via DAX and Power Query

And…  we’re done!

I suspect/hope that the two techniques demonstrated in this post (underlying image with translated X/Y coordinates, and then the jittering) will get your mental engines revving hard, and there will be questions like “wait, can I use this to do XYZ?” and/or “what if you wanted to jitter both X and Y?”

Bring ‘em on.  Even if you “just” already know how you’re going to apply this, we’re curious/excited to hear it.

The comment thread is now officially open for business wlEmoticon smile 1 Jittered Scatter Charts in Power BI via DAX and Power Query

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Announcing Single Sign-On Support when connecting to data sources from the Power BI Service

We’re glad to announce that it is now possible to use Single Sign-On, leveraging Kerberos, when connecting to certain data sources using DirectQuery mode from Power BI.

When a user interacts with a DirectQuery report in the Power BI Service, each cross-filter, slice, sorting, and report editing operation can result in queries executing live against the underlying on-premises data source.  When single sign-on is configured for the data source, queries execute under the identity of the user interacting with Power BI (that is, through the web experience or Power BI mobile apps). Thereby, each user sees precisely the data for which they have permissions in the underlying data source – with single sign-on configured, there is no shared data caching across different users.

Please note that you will need the latest On-premises data gateway release bits in order to use SSO. After installing those bits, this new option can be configured under “Advanced Options” in the Data Source registration page for On-premises data gateway sources.

You can find more details about how SSO works and what configuration steps are needed in this documentation article:

Support for Single Sign-On is available for the following data sources as of today:

  • SQL Server
  • Teradata
  • SAP HANA (please read note at the end of this blog post)

Additional data sources will be added to this list between now and end of 2017 including Impala, Oracle and SAP BW. Others, such as Spark, will come early in 2018. As usual, please submit your feature requests on this area in the Power BI Ideas forum for future consideration.

Note regarding SAP HANA SSO support: In order to enable SSO on top of SAP HANA, you will need to apply a couple of HANA-specific fixes from SAP:

    1. Upgrading SAP HANA server with SAP’s HANA Patch 122.13, released by SAP at the end of October 2017.
    2. On the gateway machine, installing SAP’s latest HANA ODBC driver.  Minimum version is HANA ODBC version from August 2017.

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Power Query (M)agic Part 3: Divide & Conquer

Blue Pill Red Pill thumb Power Query (M)agic Part 3: Divide & ConquerWelcome back P3 Nation! By now we’re in full swing with this Power Query (M)agic series, three posts and counting! You’re now knowledgeable enough about Power Query (if you read Part One and Part Two, anyway) that I want to throw some cool techniques at you involving M code. The time has come to take off the metaphorical training wheels, dive into the deep end, leave the nest, take a leap of faith (boy does this guy love idioms…), because frankly you are READY FOR IT. “I know it, you know it, everyone knows it.”

“Take the blue pill, the story ends…take the red pill, you stay in Wonderland, and I show you how deep the (PQ) rabbit hole goes.” If you’re still reading, then you took the red pill and chose…wisely. Today I’ll be showing you how to add custom M code using the Advanced Editor. The Advanced Editor is where I LIVE and BREATHE when using Power Query, so welcome to my universe. wlEmoticon smile Power Query (M)agic Part 3: Divide & Conquer

Specifically, I’ll be demonstrating two important ways to visually organize your query by renaming your applied steps and adding visual dividers between them. This technique is especially useful when you have a lot of applied steps, and want to add visual cues between related applied steps.

Since you’ve read the previous post in this series about folders, you’ve seen that visual aids can be VERY HELPFUL when building queries! These techniques are by no means necessary, but they can be a tremendous help in organizing your model. Anything that makes it easier to step back into a model months after development is a win in my book.


So I’ll be the first to tell you that, despite my best efforts, I HATE taking notes. It takes time and energy I chose not to give, especially when I need to store them separately in OneNote or a Word document. A beautiful feature of Power Query is the ability to rename any applied step to whatever you desire, essentially allowing you to write a single line of notes for each step! Corner cutters of the world unite!

This saves so much time, and it’s done easily enough by right-clicking on ANY step, selecting Rename, then changing the original title to whatever friendly name you want. My two cents: rename it to something that will make sense to anyone coming back to this model months (or years!) down the road.

Simply right click on the step you want change, the select rename from the drop down list:

Rename Steps Power Query (M)agic Part 3: Divide & Conquer

But wait, there’s more…you can also add notes to each individual step! You can do this in the SAME dropdown menu as above. What’s even cooler is that those notes…well they show up as a tooltip when you over. So in essence you can create high level summary notes by renaming the step. Then for steps that more complicated (think Rube Goldberg complicated), you can add additional tooltip notes. Badass, that’s what that is. Honestly I didn’t know this existed for the LONGEST TIME! I never would have guessed additional notes would be buried in the properties menu.

Just right click on the step you want to add notes too, select properties, then add your notes:

Applied Step Properties thumb Power Query (M)agic Part 3: Divide & Conquer

Hovering over your step now results in tooltips displaying:

Tooltip thumb Power Query (M)agic Part 3: Divide & Conquer

The Way I Used To Do It (Old & Busted)

A comment on this post enlightened me to a better way to do this! So thanks to Milan Grahovac for the new hotness! I’ve decided to keep the old method in this post, because it does give a good intro to the Advanced Editor. Plus I’m sure some people will appreciate two ways to do something. With that said, let’s walk through the old method first.

Dividers can help you look like a Power Query Ninja if anyone ever digs into your models. Have any of you EVER looked at a workbook (or code) that was organized or had added comments, and NOT thought it looked professional? Take a minute to ponder that…you’ll realize that it almost ALWAYS left a better impression than one that didn’t.

I’m sure many of you are wondering “What the heck does this technique look like?!” Let’s seen an example! I create a calendar table in many of the models I build.  Building it requires a lot of steps, and many of which are related and can easily be grouped together. Below is a before and after screenshot of the steps from that query, before and after adding Dividers between applied steps.

Giant hand man (let’s call him Steve from now on) is back to pass judgement on my organizational skills:

PQ Dividers Before And After thumb Power Query (M)agic Part 3: Divide & Conquer

A keen observer (sarcasm much?) will notice extra lines I’ve added on right image, visually grouping sections of my applied steps. Adding these is easily accomplished by adding a few lines into the Advanced Editor window. It’s really easy to add them, but can be tricky to remove later.

Before I demo the technique, let me explain some important Power Query fundamentals. These concepts will help you understand how the applied steps work, and how they connect to each other. It’ll be important to know this if you ever want to remove these dividers later, or add/move steps to your query.

Fun Fact! Whenever you make a new transformation (new step) to your list, by default it references the previous step. In the image below the highlighted step (Added Calendar Year) references the previous step (Added Calendar Month), in the body of the M code. Every step will have a reference similar to the one you see here (make note as we’ll circle back to this later).

Example of how Applied Steps relate to each other:

Power Query Step Link thumb Power Query (M)agic Part 3: Divide & Conquer

Interested in Learning How to Do this Kind of Thing?

Our New Online Power Query Course just launched this year. You’ll learn Power Query from the best in the business, two Excel MVPs Ken Puls and Miguel Escobar. We’ve included 7 Hours of Self-Paced Video over 31 Courses, with lots of example files, and a Digital Badge powered by Acclaim. CLICK HERE to claim your spot!

PQ training Power Query (M)agic Part 3: Divide & Conquer


Let’s start by walking through how to add these dividers into our Applied Steps. First order of business, you need to know where the Advanced Editor Window is located! It’s found under the View ribbon (same place you turn on the formula bar to see the M Code).

Opening the Advanced Editor window:

Advanced Editor Window thumb Power Query (M)agic Part 3: Divide & Conquer

Advanced Editor Window – Not as scary as it looks, promise:

Advanced Editor Unedited thumb Power Query (M)agic Part 3: Divide & Conquer

As you gaze into the depths of code within the Advanced Editor window, you can see that each step is nicely given it’s own line. This is the typical layout for any unmodified query in Power Query. It makes it relatively easy to see where one applied step ends, and the next begins. Next I’m going to insert a dividing line into the code, to provide some degrees of separation. I’ll go ahead and insert it right before I start making all my custom columns (E.g. before #”Added Calendar Month”).

Advanced Editor window AFTER adding in the code for my dividing line:

Advanced Editor Added Steps thumb Power Query (M)agic Part 3: Divide & Conquer

Let’s break down this line of code to understand why I added what I did. Each applied step at is core is essentially two parts. The first part is the applied step name, and the second part is the data output. The name in this instance is #”===START Custom Columns===”. NOTE that you’ll ONLY see the applied step name in the Advanced Editor Window; the Formula Bar only shows the data output.

For any Applied Name, you technically don’t NEED the #”…“ part before and after the name unless it contains spaces. However, as a best practice, I always use them for habit and consistency. And the equals signs in my step name aren’t anything special or required, but rather a way to fill out the row and create a distinctive look compared to other steps.

The second part of any applied step is the data output. This is where the transformation goes whenever you create a new applied step. Some data (either a table output or single value) is REQUIRED here for any applied step. Hence the reason I’ve created “dummy” data in mine as a single numerical value. It doesn’t do anything other than make sure this artificial step works.

Applied Step results after adding my dividing line (Note the 1 value output when selected):

Adding a dividing step thumb Power Query (M)agic Part 3: Divide & Conquer

The Applied Step Added Calendar Month still references the SAME STEP before the addition of the divider:

Previous Step connection thumb Power Query (M)agic Part 3: Divide & Conquer

The divider step is essentially hidden between the other two, there to provide visual separation and nothing else. I’m a HUGE FAN of this technique because it’s a great way to slowly introduce users to the logic and components that make up each applied step. Now if you want to delete a divider step, you can easily just select the delete (X) icon next to the step to get rid of it, just like any other step.

Power Query can get finicky if you start trying to add and/or move steps around after creating your divider steps. If you do this, there are a few ways that a new or existing step could accidentally get referenced. If that happens it will temporarily break the query unless you redirect the step back to the correct one.

Error message after moving a step in front of my custom step:

Moving applied step error thumb Power Query (M)agic Part 3: Divide & Conquer

Moving the Added Calendar Year applied step in front of my custom step caused it to break…but why? Well, whenever a step is reordered, it will always default to using the previous step in the list. So by reordering this step right after my custom one, it assumes it should reference that as it’s data source…which we DO NOT WANT.

Circling back to the M code basics you learned earlier, you can FIX THIS by reassigning that source back to the correct step. You’ll want to change the step name in the Formula Bar to point it back to the Changed to DATETYPE applied step. Once you’ve done that the divider step will go back to ninja mode, hidden amongst the other steps.

Query working correctly after updating the step (data) source for Added Calendar Year to Changed to DATETYPE:

Moving applied step fixed error thumb Power Query (M)agic Part 3: Divide & Conquer

Alright folks, now let me show you how to do this WITHOUT the Advanced Editor! Again, as Milan Grahovac graciously mentioned in the comments. There’s an easy way to add these note line notes without touching M code. Same concept, but without the issue of accidentally breaking a step if you delete the custom line of code. That same dropdown menu we go to when renaming a step, well there’s another option in there we can use. There’s a button called Insert Step After that essentially references the previous step, but without doing any actual transformations. What this means is no performance hit, and a beautifully integrated step you can rename as a divider!

Same process as renaming. Right click, and select Insert Step After:

Inserted Step After thumb Power Query (M)agic Part 3: Divide & Conquer

Boom, new custom step:

New Integrated Step thumb Power Query (M)agic Part 3: Divide & Conquer

The beauty of this is twofold: no Advanced Editor needed, and it’s less prone to break. You can observe how this custom step is simply referencing the previous step, without any transformation applied. So this won’t slow down your refresh AT ALL. All this does it provide us a line in our Applied Steps to create a line or section. Just simply rename it like you would any other step. Now the old method is still a great gateway drug to the world of M coding. Next thing you know you’ll be inserting functions, folding queries, and appending tables oh my! If this managed to wet your appetite for the possibilities with M, then mission accomplished for me. Stay tuned for the next post in this series! Until then folks!

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I am now an MVP :-)

November 10, 2017 / Erik Svensen

I am now an MVP icon smile I am now an MVP : )

Last week I received an e-mail from Microsoft that I had been awarded the MVP Award.

 I am now an MVP : )

This made me glad and proud.

My colleagues, friends and family all know me as a very passionate and loyal Microsoft fan – and now I can show that it has been noticed from Microsoft as well

I want to say thanks for all the people that has attended my talks during the years, people that have allowed me to talk and the great community of SQL Saturday, MS BIP Denmark and finally the Power BI Community.

I will continue my work for especially the Power BI community and have set a few goals for the coming year – one them is of course to get the MVP Award for 2019-2020.

A special thanks to Ruth Pozuelo for nominating me.





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Erik Svensen

Power BI Desktop November Feature Summary

This month conditional formatting gets a major update with the ability to control the color based on rules. If you have a slow data source, we now have report options that help limit the number of queries that are sent to the source. Finally, we are also adding several formatting features, including cell alignment for table and matrix, and precise control over the order of overlapping charts on your report.

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Don’t forget you can now get Power BI Desktop from the Windows Store if you’re on Windows 10!

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Here’s the complete list of November updates:



Data connectivity

Query editing

For a summary of the major updates, you can watch the following video:

This month we’re extending conditional formatting to include rule-based conditional formatting. Now, if you have specific business logic to reflect in your table or matrix, you can create rules to conditionally color the background or font color of a column.

To start formatting based on your rules, open the color scales dialog and check the Color by rules box. This enables you to choose colors by your business logic.

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In each rule, you can pick a color to use when a cell value is between two values, is equal to a specific value, or is blank.

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When finished, click OK to apply your rules. Each rule is applied in order, top to bottom. This means that if a value meets the criteria of two different rules, the bottom rule applies.

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Watch the following video to learn more about the conditional formatting improvements:

This month we’ve also added cell alignment control to our table and matrix visuals. You can specify left, right, or center alignment for your row and column headers, or you can set the alignment for one specific field in the Field formatting card.

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Watch the following video to learn more about cell alignment:

Last month, we introduced the selection pane, which lets you easily select all the objects on your report page. It also lets you control if the object is visible. We are extending this pane to let you easily change which overlapping objects show on top on the canvas. The selection pane is sorted so the objects higher in the list show in front of objects lower in the list. You can drag and drop to change the order or use the arrows on the top of the pane to move things up and down.

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Watch the following video to learn more about the selection pane update:

When you’re interacting with your report, either to test it out or as part of your analysis process, it’s easy to accidently nudge a chart a little to the left or right. To help with this problem, we’ve added a button to the View tab to lock all the objects on your report. This will turn off resize and move, so you don’t have to worry about messing with your layout as you interact with your report. This setting isn’t saved with the report, so you’ll need to enable it any time you want to use it.

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Watch the following video to learn more about locking objects:

Esri’s ArcGIS Maps for Power BI was announced at Ignite 2016 and became generally available in June of 2017. Since then, Esri’s map has been empowering Power BI users to get more from their geospatial data. Now, Esri is releasing a new subscription service called Plus that enables ArcGIS Maps for Power BI users to do even more with their geospatial data.

Using Plus, you can get richer mapping capabilities, including:

  • More street address geocodes – up to 5,000 data points per map
  • Additional basemaps, including: Imagery, Imagery with labels, National Geographic, Oceans, Terrain with labels, Topographic, USA Topo Maps, and USGS National Map (USA)

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  • Living Atlas reference layers that help add more context to your maps

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  • World Demographics within the Infographics feature for categories like Education, Population, Income, or even Segmentation.

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To start using Plus, all you need to do is sign up for a subscription or sign into an existing one through the plus button on the top right.

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You can try the Plus subscription for 60 days at no charge and after that you can subscribe for $ 5 per user per month. When you use Plus features within the map, any user you share the report with needs to also have a Plus subscription to view the content. You can learn more about Esri’s Plus subscription from Esri’s web site. The free capabilities included with Power BI remain the same.

Watch the following video to learn more about Esri Plus:

If you are working with either a very large or very slow data source in DirectQuery, some actions will take a while to get a response from the underlying data source. To help with that, we’re giving you some options in the report to send fewer queries, making it easier to interact with the report.

To access these options, go to the Options dialog under File > Options and settings > Options, and select Query reduction.

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From here, you can turn off cross highlighting automatically throughout your whole report. (You can still manually turn it on for specific visuals using the Visual interactions feature, but the default will be off.)

You can also add an Apply button to slicers and filters. Depending on what you select, the Apply button is added to slicers, filters, or both. You can make as many selections as you want, but no queries will be sent until you select the Apply button. Your selections will then be used to filter all your data.

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Of course, these changes will apply to your report while you interact with it in Power BI Desktop as well as when your users consume the report in the Power BI service.

Watch the following video to learn more about our slow data source improvements:

We’ve recently made some updates in our filtering implementation, which improves performance for certain scenarios, such as when using strings. We’ve also removed our 500 value limit on how many values you can match when filtering for all data sources except Live connections to analysis services models.

This month there are four custom visuals recently released to the custom visuals store that I’d like to call out. As a reminder, all custom visuals can either be imported directly from the store in Desktop or you can individually download visuals from the custom visuals store for importing.

Image Timeline

The Image timeline custom visual displays events along a horizontal timeline. These events can either be represented as a circle or a custom image. You can then click on events to filter down your report to that event. If you have lots of events on your timeline, it also has an interactive date “brush” that lets you zoom in on the timeline.

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Watch the following video to learn more about the image timeline visual:

Social network graph

The Social network graph custom visual can be used for visualizing connections between people. One common scenario for this is visualizing an organization structure where employees report to managers in a hierarchy. You create the visual by giving it the source and target for each connection, and then you can format it with size and color based on other fields in your model.

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Watch the following video to learn more about the social network visual:

Venn diagram by MAQ Software

Venn diagrams are good for finding commonality between different categories. Each circle is a collection of data points for a given category and where the circles intersect, there are data points that represent both categories.

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Watch the following video to learn more about the venn diagram visual:

HTML viewer

The HTML viewer visual is lets you display your HTML text strings, for example rich-text columns from SharePoint, in its original formatting. You can also do some basic formatting of alignment, color, and size for the text as well.

Here’s an example comparing the HTML text in a Power BI table and the HTML viewer visual.

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Watch the following video to learn more about the HTML viewer visual:

We are extending our cell-level formatting support to multi-row cards this month. This means that for table, matrix, single value cards, and multi-row cards, cell-level formatting defined in your multi-dimensional Analysis Services (AS) model will automatically flow through and be applied.

This month we’re adding support for Windows Authentication to the Impala connector. This was a common request from existing Impala connector users. In the next month, we will also add support for Windows authentication to the On-premises data gateway, as well as Kerberos-based Single Sign-On support for the Impala connector via the Gateway.

After specifying an Impala cluster to connect to from Power BI Desktop, you can now select Windows as the authentication type in the Credentials dialog. Within the Windows authentication option, you can select whether to use the “current Windows user” or impersonate a different user.

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We’ve added support for generating “Conditional Columns” transforms as part of the “Add Column From Examples” experience.

This addition opens up a lot of additional scenarios for “Add Column From Examples”:

a) Basic Conditional Column: It is now possible to define a mapping between values in an input column and the desired output by providing a set of examples.

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b) Conditional Column Ranges: We’re making it possible to define a new column with non-uniform ranges based on an input column. This new capability is supported for columns where the output values don’t encode the range boundaries.

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c) Null fallback: A very common scenario for “Conditional Column” is using a value from a given column, or the value from a fallback column when the first column value is missing for a given row.

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d) Bucketing (uniform ranges): Last but not least, we’ve also enabled bucketing via “Add Column From Examples”. Users can now specify the upper/lower boundaries of a range for a certain row and we will automatically extrapolate to all other rows by using uniform ranges.

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Watch the following video to learn more about the Column from Example update:

That’s all for this month! We hope that you enjoy these updates and continue sending us your feedback. Please don’t forget to vote for other features that you’d like to see in the Power BI Desktop.

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DAX Reanimator: Moving Averages Controlled by Slicer (Part 2, including GFITW)

Today, I’ll show you how to bring the awesome to moving averages with DAX text formulas for slicers and titles…  and yes, I’ll throw in a Greatest Formula In the World (GFITW) version, too. In Part One, I used What-if-parameters in Power BI to control the moving average period with a slicer. And the original post from 2013 is Moving Averages Controlled by a Slicer, which brought the awesome to Moving Averages, Sums, Etc.

Last time, I promised to go beyond what can be done right out of the box using What-if-parameters. I’m going to help you take your reports from ordinary to awesome by using features like:

  • Small sets of values to choose from:  -12, -6, -5, -4, -3, -2, 2, 3, 4, 5, 6, 12.  By itself, the GENERATESERIES() function can only make sets that follow a fixed pattern: +1, +.05, +2, etc.
  • Moving average slicers with text labels, but what-if-parameters only generate numbers.
  • Dynamically generated title for the chart.

But wait, there’s more! I also added some bonus items:

  • Viewing multiple parameters at the same time. AND…
  • The Greatest Formula in the World (GFITW) version of the moving average formulas. For those who use specialized calendars for manufacturing or retail, like a 4-4-5 calendar.

NewTableButton DAX Reanimator: Moving Averages Controlled by Slicer (Part 2, including GFITW)
The first thing I noticed about GENERATESERIES() is that it’s a table function. It returns a table instead of just one value. That means we can go straight to the New Table button on the Modeling tab. This button lets us create a new table in the data model from a table formula.

The New Table button is handy for quickly adding a simple calendar table to a model. For example, the table created with this formula below is trimmed to the Order Date column of the Sales table. Note that the calendar starts on the first day of the month, because otherwise it could throw off the time intelligence functions.

Calendar =
    DATE ( YEAR ( MIN ( Sales[OrderDate] ) ), MONTH ( MIN ( Sales[OrderDate] ) ), 1 ),
    MAX ( Sales[OrderDate] )

And New Table is also a great place to look at table functions used in formulas, for troubleshooting, or for learning DAX.

Here is a formula to generate a table made up on non-regular intervals. Tables are held in variables at the top of the formula (Yes! Tables in variables!). I use UNION to mash up the different series into one MA Length table. Matt Allington blogged this approach when GENERATESERIES was introduced.

This result is a table that’s not entirely continuous, but the order doesn’t matter because the numbers will be sorted automatically.

Moving Average Label, sorted by length value

ma reanimator2 6 DAX Reanimator: Moving Averages Controlled by Slicer (Part 2, including GFITW)

Next, we add the text for the table. The text for the rows comes from a calculated column we added to the Moving Average Length table by clicking the New Column button on the Modeling tab and entering this formula:

Months to Include =
VAR MonthText =
    FORMAT ( ABS ( ‘MA Length'[MA Length] ), “General Number” )
VAR S_Text =
    IF ( ABS ( ‘MA Length'[MA Length] ) = 1, “”, “s” )
    SWITCH (
        TRUE (),
‘MA Length'[MA Length] > 0, MonthText & ” Month”
& S_Text
& ” Forward”,
‘MA Length'[MA Length] < 0, MonthText & ” Month”
& S_Text
& ” Back”,
‘MA Length'[MA Length] = 0, “Current Month”

This applies our diabolical old friend Switch TRUE(), and also includes a test for a value of 1 for values that are singular. When creating a text equivalent for a value, be sure to set the sort by column in the Modeling tab so that it doesn’t come out alphabetical.

This makes a text label for the top of the report. I put it onto the report in a using a Card visualization. Make sure to set the sort by column to sort the calculated column by the MA Length value.

Chart Title =
IF (
    COUNTROWS ( ‘Moving Average Length’ ) > 1,
    “Monthly Sales vs. 3 Months Back Moving Average “,
    IF (
        COUNTROWS ( ‘Moving Average Length’ ) = 1
&& [MA Length Value] = 0,
        “Monthly Sales”,
        “Monthly Sales vs. “
‘Moving Average Length'[Months to Include],
[Variable Moving Average]
& ” Moving Average”

Text formulas are also great for static titles:

Chart Title2 = “Actual Sales vs. Multiple Moving Average Periods”

Why? Because they have more formatting options and you can also make them match dynamic titles.

Picture1 thumb DAX Reanimator: Moving Averages Controlled by Slicer (Part 2, including GFITW)

Because we used disconnected tables, we can compare multiple months back and forward at the same time by putting ‘MA Length'[Months to Include] column on the legend of the line chart. The slicer is still to the left of the chart above, so we don’t have to see all the ranges at the same time. In the first version, we compare different measures: Total Sales and a dynamically set moving average period. In this version, however, we comparing different values of the disconnected table. This is why I have 0/Current Month in my series: so that it could be compared with multiple moving averages. Our SWITCH() statement just substitutes Total Sales for the moving average calculation when the Current Month is active.

This version of the measures have the same results, but are used when an organization uses a custom calendar, like a retail 4-4-5 calendar. The formula depends on having a column in the Calendar table which is an index of all months, where Period 13 of Fiscal Year of one year is one less than Period 1 of the following year. Year + Month won’t work because it has gaps. My year month index is [Year] * 12 + [Month], which only works if your calendar always has exactly 12 months. The Power Pivot and Power BI book gives a great synonym for GFITW formulas: “Clear Filters, then Re-Filter.”

GFITW Variable Moving Sum =
VAR End_Month =
    IF (
[MA Length Value] > 0,
        MIN ( ‘Calendar'[YearMonth Index] ) + [MA Length Value]
        MIN ( ‘Calendar'[YearMonth Index] )
VAR Start_Month =
    IF (
[MA Length Value] < 0,
        MIN ( ‘Calendar'[YearMonth Index] ) + [MA Length Value]
+ 1,
        MIN ( ‘Calendar'[YearMonth Index] )
[Sales Amount],
        FILTER (
            ALL ( ‘Calendar’ ),
‘Calendar'[YearMonth Index] >= Start_Month
&& ‘Calendar'[YearMonth Index] <= End_Month

I redefine the variables in both formulas instead of using measures, because it was the easiest way to avoid a filter context transition (formula breaking because of the measures being evaluated within the FILTER statement).  And let me tell you, if you really want to appreciate the convenience of time intelligence functions, try writing some GFITW versions of things!

GFITW Variable Moving Avg =
VAR End_Month =
    IF (
[MA Length Value] > 0,
        MIN ( ‘Calendar'[YearMonth Index] ) + [MA Length Value]
        MIN ( ‘Calendar'[YearMonth Index] )
VAR Start_Month =
    IF (
[MA Length Value] < 0,
        MIN ( ‘Calendar'[YearMonth Index] ) + [MA Length Value]
+ 1,
        MIN ( ‘Calendar'[YearMonth Index] )
VAR NumberOfMonths =
        DISTINCTCOUNT ( Calendar[YearMonth] ),
        FILTER (
            ALL ( ‘Calendar’ ),
‘Calendar'[YearMonth Index] >= Start_Month
&& ‘Calendar'[YearMonth Index] <= End_Month
    IF (
[MA Length Value] = 0,
[Sales Amount],
[GFITW Variable Moving Sum] / NumberOfMonths

Filters section under Visualizations: Page Level and Report Level

dax multiple moving averages slicer gfitw Filters 4 DAX Reanimator: Moving Averages Controlled by Slicer (Part 2, including GFITW)
And as a finishing touch, I add some page filters to the report in Power BI. On the first page, I set MA Length <>0, so that the Current Month won’t display in the slicer.  And, on both moving average charts, I set visual level filters to show only completed months.

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Deciding Whether to Use Azure SQL Data Warehouse

From time to time I publish on the BlueGranite team blog. My newest post is a decision tree about whether or not Azure SQL Data Warehouse is a good fit.

In Azure you have several technology choices for where to implement a data warehouse. Since Azure SQL DW is an MPP (massively parallel processing) platform, it’s only appropriate in certain circumstances. Hopefully the decision tree can help educate people on the best use cases and situations for Azure SQL DW, and prevent making the wrong technology choice which leads to performance issues down the road.

Please head on over to the BlueGranite site to check out the post

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Blog – SQL Chick

How Data will Influence the Future of Storytelling

Microsoft Power BI is empowering all types of people to tell stories with data. We’ve seen journalists using Power BI to understand and illustrate the news, customers using Power BI to interact with their fans, and business analysts justifying a budget ask from their managers. Modern storytelling requires the effective use of data.

Recently, we showcased Power BI’s storytelling prowess at the Future of StoryTelling Summit (FoST) in New York City. FoST is ‘an exclusive event, gathering a stimulating mix of thinkers and practitioners from diverse fields who are shaping the art, science, and business of storytelling in the 21st century.’ We are always excited to interact with our customers and learn from the ways they are using the tool to achieve more.  At this event we had the opportunity to introduce a variety of creative storytellers to the potential of using data to tell their stories with Power BI.

FOST How Data will Influence the Future of Storytelling

“An exceptional story is at the heart of every memorable communication,” said Charles Melcher, President of Melcher Media and Founder and Director of Future of StoryTelling. “Data-driven storytelling connects to my passion for telling stories that are enduring, authentic and innovative.”

While at the Summit, our team learned some valuable lessons for data-driven storytelling. We wanted to share how these lessons, combined with Power BI, can strengthen your storytelling skills.

Identifying your story

identifying How Data will Influence the Future of Storytelling

Power BI can help you discover your story. Often when working with data, you may not know exactly what the story is until you visualize it. Visualizing your data in Power BI is a great first step in identifying the truth in your data.

Once you understand what your data is telling you, you can begin to plan your story arc. Identifying what you want the reader to take away from your story when interacting with your data visualization will set the stage for an effective story. Rather than trying to show every aspect of the data, think about what you want your audience to understand and how to best guide them through the data. The most effective stories leave the reader with insights carefully brought to life through the visualizations you create, with the ability to continue to explore.

The most effective way to do this is to know your audience. Put yourself in the reader’s shoes, think about how they might want to interact with the data, how you want them to interact with the data and how this relates to your goals for your data story. Identify what is inherently interesting about your dataset and present that to your reader in the most effective way you can.

One way to do this is by connecting with the reader on an emotional level. At the Future of Storytelling Summit, we presented a story about the history of artificial intelligence using the Timeline Storyteller custom visual for Power BI. Knowing this audience had a keen interest in artificial intelligence (AI), mixed reality, and how technology continues to play an integral part in writing history, we connected with our audience by showing a story that highlighted works of fiction across literature and film that included AI themes. Including these data points set the scene for the rest of the story, sparked curiosity, and engaged the audience on an emotional level as they thought back to movies and books they may have loved or even hated!

Compared to what?

The most effective data stories provide the whole picture. After identifying key insights in your data, a great question to ask is “compared to what?” Providing context to the reader helps a data story feel more honest and unbiased. It shows the reader how the data being highlighted fits into the bigger picture.

In the demo we created for the Future of Storytelling Summit, we wanted to show the audience all the exciting contributions Microsoft has made to the field of artificial intelligence. While creating the report, we asked the question “compared to what?” With Power BI, we were able to include a full timeline that was inclusive of all major contributions to the field of artificial intelligence. We showed our audience that there is more to the field of artificial intelligence than just Microsoft, and our story came off much more authentic and honest.

Presenting your story

datagrowth How Data will Influence the Future of Storytelling

Once a data story has been created, finding an effective way to present it has historically been a challenge for our customers. Our goal with Power BI has always been to enable users everywhere to experience data in the best way possible. This goes for authors as well as the audience of the reports. Power BI Publish to web allows users to tell compelling stories with interactive data visualizations in minutes. You can use “Publish to web” to embed Power BI visualizations in your blog, website, emails, or even social media accounts.

Additionally, in the October Feature Update to Power BI Desktop, our team announced an exciting new preview of a tool called “Bookmarking.” This was one of the features our team demoed at the Microsoft Data Insights Summit to save and share out your insights with others. It can also be an extremely effective storytelling tool. Report authors can now create a list of bookmarks, organizing a story arc for the readers of a report. More information on how to create bookmarks can be found here.

Getting Started

We have several resources on the Power BI data journalism site to help you get started building your data story. We even teamed up with renowned visualization expert Alberto Cairo to share the methodology behind graphics and how they can support data storytelling by developing five Data Visualization and Storytelling courses.

We are always interested in hearing more from our customers about how they are using Power BI to tell stories. We’re committed to optimizing Power BI storytelling capabilities, and creating new features to enable more powerful storytelling. We’d love to hear your feedback, and we welcome the opportunity to hear more about your work in the Data Storytelling Discussion forum.

Additional Resources

Future of Storytelling Summit

History of Artificial Intelligence Report

Power BI Publish to Web

Power BI Bookmarking Preview

Power BI Data Storytelling Discussion forum

Data Journalism Course with Alberto Cairo

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Tuesday and Thursday Posts on DAX, Power BI, Power Query, and Other Data Topics – FOREVER

On September 5, 2011, I announced an ambitious initiative:  I committed to a blog post EVERY Tuesday and Thursday, indefinitely.  At the time I wasn’t sure if I could sustain it for more than a month or two, but a funny thing happened and I sustained it (with some help for sure) for about four solid years.  At that point, the pressures of running a full-on consulting company “overflowed the river banks” and our regularly-scheduled program petered out.  But those were some glorious years, and I credit that clockwork, “come-hell-or-high-water” schedule for a lot of the growth of this site (and subsequently, our company).

Beginning this coming week, you will see posts go live here EVERY Tuesday and Thursday morning.  From now until the end of time.

You see, the same thing that distracted me from the schedule in the first place (having a company that depends on me) has also become a massive advantage.  We have many amazing people here on staff – people with with amazing stories and techniques they can share.  We have the ability to hire an editor to keep the quality bar high when I’m not available.  We have someone who can “whip” the schedule and make sure we hold true to our promise.  And yes, that whole process ALSO can hold ME more accountable, so that I myself post more frequently as well.

(Speaking of the advantages of being a robust consulting company, have you considered hiring us to implement some kick-ass analytics for your firm, and/or adopt an empowered, non-dependent, business-driven data culture?  No one does it better or more rapidly than we do.  Not even close.)

This morning we held the final kickoff meeting for this new process.  The team is in place.  We already have a healthy series of posts in the hopper awaiting finishing touches.  It’s go time.

So, while I hate comparing myself to Longshanks, and certainly don’t condone HIS policies, well, the first part of the quote is just too perfect, and it forced me to learn some rudimentary Latin which can’t be all that bad.

Two reasons.

1) I want YOU, dear readers, to be able to depend upon this.  I’ve been listening to podcasts lately and have really grown to love even just the “looking forward to the next one” feeling.  I want that feeling for OUR data community.

2) Once we commit, we can’t go back.  So I’ll leave you with one last movie quote…

image 2 Tuesday and Thursday Posts on DAX, Power BI, Power Query, and Other Data Topics – FOREVER

See you Tuesday… wlEmoticon smile Tuesday and Thursday Posts on DAX, Power BI, Power Query, and Other Data Topics – FOREVER

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