Measure Filters, Time Series Hierarchies in SAP Lumira 2.1

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In this third blog of our series covering what’s new in SAP Lumira 2.1, we will be covering the new feature of being able to add filters on measures as well as adding some valuable information on how you can use Time Series Hierarchies.

In the last blog, we covered the topics of Trend/Regression Lines and the Formatting of Input Controls which are both very useful new features.  If you missed it, check out the Trend/Regression line blog here.

Measure Filters

One of the most glaring disappointments of Lumira 2.0 was not being able to filter on measures. In Lumira 2.1, this has been added and, as expected, it’s an easy feature to use.

Let’s say for example you are analyzing Sales Revenue by Store Name but you want to filter to where the Quantity Sold is greater than or equal to 8,000, based on the Store Name. The only way to do this was to use the Ranking feature, however, this forced the order of the dimension, sometimes we want to dynamically filter by measure and keep the member order. With Lumira 2.1 you can do this now.

We start out by creating a simple bar chart with Sales Revenue by Store Name.

To add the filter on the Quantity Sold Measure when maximized on your chart, click on the Add Filters button and select the Quantity Sold Measure.

Choose Based on Store Name and Greater Than Or Equal To 8,000.

Now as you can see the chart has changed and has been filtered appropriately.

Time Series Hierarchies

Not all of the features having to do with Time Series Hierarchies are new in Lumira 2.1, but it is a useful feature which is sometimes overlooked.

Building on our example above, we are going to create a Time Series Hierarchy based on the Opening Date and show how this can be used for in-depth analysis and drill-down capabilities.

First, it’s important to note that you can’t create a Time Series Hierarchy based from a date that is a string. In this example, our Opening Date is a string so we will need to convert it to a date before creating the hierarchy.

Do this by right-clicking the Opening Date field and selecting convert to Date/Time.

We then just select the Source Date Format which in this case is mm/dd/yy

Now that we have our date field in date format instead of a string, we can right-click the date field and select Hierarchy – Date/Time to create the hierarchy.

Once you do that you will see that the Date/Time hierarchy is created.

Next, we can use this hierarchy in our bar chart that we created earlier.

First, we’re going to convert our chart to a Stacked Bar Chart, then set the Year from our Time Series Hierarchy as the Y-Axis and the Store Name as the Color.

Now we can see what year each store opened and you can see that in 2018 two stores opened.

If we want to drill down into the year 2018 to see what quarters each store opened, we can right-click and select drill down.

Now you can see that the Los Angeles store opened in Q1 and the New York Magnolia store opened in Q4.

Wrapping it up

It’s obvious that being able to filter measures was something that needed to be added and it’s definitely a valuable addition. We also explored how using Time Series Hierarchies can add an extra level of analysis for your data with the drill down capabilities.

We’ll continue providing tips on the new features in Lumira 2.1.  We hope you enjoy them. Look for future blogs on all topics related to BI!

If this blog didn’t quite answer your question or you have other Business Intelligence questions or concerns, please feel free to contact us.

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By |2018-09-02T17:39:35+00:00July 4th, 2018|Kingfisher, Lumira, New features|0 Comments

About the Author:

Andrew has more than 7 years of experience and specializes in the EIM field, with a solid background in front end as well. He has strong experience with SAP HANA, Data Services, Information Design Tool, Lumira, Crystal Reports and Web Intelligence. He has worked in a number of industries such as Retail, Energy, Manufacturing, and Healthcare with direct experience working with two Fortune 100 companies. Andrew enjoys playing and watching sports, being outdoors, and traveling in his free time. When he’s not busy pulling for the Atlanta Sports teams you can reach him at