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Three New Features in MicroStrategy 10 to Make Your Life Easier

“What’s New in MicroStrategy” can read about as smoothly as an iTunes legal agreement and sometimes it feels like feature demos dance over the details. So here’s a quick summary of three new additions to the MicroStrategy v10 dashboarding tool that have made our lives significantly easier as MSTR users – give them a try in your shiny new upgraded server (to those lucky, fast moving MSTR customers), or email to sign up for one of our training classes using our hosted v10 environments starting in September. If you’re interested in upgrading, let’s start discussing your MicroStrategy 10 upgrade strategy!

Duplicating Metrics as Attributes

Converting metrics to be used as attributes may sound like a small feature, but it’s actually a game changer. Think about these questions:

  • Q1: How much money are most of my customers spending with us?
  • Q2: Ms. Bemidji spent $9,000 dollars with us. Is that a lot or a little compared to her peers?

These questions can be answered in numeric terms pretty easily. A percentile rank of Ms. Anderson might tell me what I’m looking for, and a median or average calculation would give an idea on context.
For example, A1 could be explained with $3500 as a median spend and A2 could be stated as Ms. Bemidji residing in the 76th percentile. While this is backed in mathematics, it definitely does not deliver any overarching context of what our customer spend looks like for the whole population of customers. We need a graph, but in v9, we’re limited to scatter plots or bar charts that show every customer’s distinct spend. Cue v10.

Take a look at this graph, thinking about how quickly those questions are visible with context:


  • A1: Most customers are spending around $2300 – $4600 with us.
  • A2: $9000 in spending lands Ms. Bemidji well above most other customers in our distribution, and the distance between her and the majority is sizable.

Now that’s a set of answers I can wrap my head around.

This was impossible in the v9 Visual Insight editor because bars could only display values related to an attribute. In other words, unless there was some field in the database used as a descriptor of each revenue bucket, you were not going to get a histogram graph like this in v9 Visual Insight. With v10, this is an easy task because I can duplicate any metric to be treated like an attribute. That new capability allows me to count the customers, grouping by the ntile revenue buckets.

The key functionality that didn’t exist in prior versions of Visual Insight was duplicating metrics to behave like attributes. That allows users to graph a bar for each of the value buckets. In v10, right-clicking (hooray HTML5!) on any metric lets me treat a metric as an attribute with a “group by,” behavior, and therefore count customers within a set range of sales values.

One more quick example: show me the guys who have scored 2 or 3 goals in the English Premier League this year (after Matchday 2). Treating the metric as an attribute makes this as easy as letting one graph filter on a grid. Here’s the visual:


With metrics acting as attributes (this time, # of Goals), it’s super easy to filter data from one visual to another based on a metric value. This wasn’t possible in v9 because metrics could not be grouped and treated as distinct values of a field.

Adding Reference Lines

Scatter plots showing the correlation between two values are totally under-utilized, partly because looking at a mess of dots on a screen doesn’t convey a lot of information to the untrained eye.

Here’s a quick experiment: looking at this graph, tell me if new Manchester United player Morgan Schneiderlin represents good or bad value in terms of points per minute based on this scatter of minutes played and points scored.


You are probably looking at the graph, recognizing that the slope of a line represents points per game, and so depending on if he’s on a higher or lower angle line from origin, he might be high or low… It looks like he’s somewhere in the middle.

Now imagine putting this in the hands of a business user. He or she cannot make a decision to buy or sell Schneiderlin based on this plot.

But with one click in MicroStrategy v10, I can tell you the answer. When I add a trend line for the average points per game, all I have to tell a user is that if the dot is above the line, the player represents good value (in other words, scored more points than we would have expected given how much he played). If the dot is below, that player needs to improve. It’s as simple as that with a reference line.


Schneiderlin is above the line. He’s got more points per game than we’d expect for a midfielder. It’s as simple as that. V10 makes it easy to compare items against their peers in a scatter. Reference lines can be linear, exponential, logarithmic, and polynomial. So for the data scientists out there, have at it! For the rest, brush up on your algebra so you can explain the new 1-click capabilities in MSTR to the users who add them to dashboards. We’ll stick to a straight linear regression in this example.

One more time: check out the following line chart where I’ve added reference lines for the maximum and minimum in order to indicate what the best and worst values are for our percentage difference between sales and forecasts.



The second graph makes it much easier to tell the overarching trend. Our performances have consistently been between 5% below- and 19% above our Profit forecast. In both cases, it might seem like a subtle formatting change, but to your business users, it can mean the difference for understanding a dashboard or even being willing to adopt your data into their decision-making process. And it takes 1 minute in the new v10.

Conditional Derived Metrics – Case Statements in Metric Formulas

It’s now possible – dare I say, easy – to embed case logic into the metrics you create in your dashboards. This might sounds small, but it actually opens a world of possibilities in your v10 dashboards. Just ask all these people on the forums.

While a number of those threads have answers for reports, standalone metrics, or documents, none of them were possible in the latest and greatest dashboard editor.

This lets me do things like take a daily revenue and calculate the weekend revenue. It could also come up when you want a new metric that aggregates books and electronics together.

And you can’t forget those crazy business use cases where if you’re in category A, the metric should be the sum of M1, M2, M3, and M4, but category B is the difference between M2 and M4. Category C is counted as the average of all four metrics, but not when the first metric is null… and at this point, my head is spinning and I just ask the user to give me a copy of their current report.

Here are two working examples:

sum(Case (Day@DESC in (“Sat”,”Sun”), Sales, 0) {~+}
Sum(Case(Category@DESC In("Books","Electronics"),Revenue,0)){~+}

Watch out for a bug where MicroStrategy takes out the space after the DESC and giving a syntax error because it doesn’t recognize the combined DESCin text.)


I hope this helps you make the case to IT that you need v10 yesterday! Or if you’re in IT – this is why MSTR is sending you all those emails about upgrading!

Reach out to Pandera to get started using MicroStrategy 10 to help make sense of data and get the most out of your analytical system.


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