Bime V3.5: Bime is going Mobile. [RELEASE]

The Bime team is happy to announce the release of the V3.5 of our platform. We have stacked it full of improvements and new features to make Bime the most advanced analytical tool available in the cloud.

On the menu today: Bime Mobile to consume your dashboard on any device (we mean it), a premium -tailor made- connector for, new calculations and improvements on several visualizations.

Entering Bime Mobile

As the industry is shifting to mobile, we are happy to announce that you can now consume your dashboard on iPhone, iPad, Android Phones and Android Tablets. Most people want native applications on their device not just the time consuming, hard-to-read-on-mobile web page reports you often get. We heard you! Bime Mobile is available right now on the App Store and on the Android Market. The experience of browsing dashboards and visualizations has been optimized for touch and mobile device.

Bime Mobile makes your dashboards consumable on all the major devices available today: Web, Mac Desktop, Windows Desktop and mobile devices. This opens new realms of user options as for the first time you can instantly push data from Google Analytics, Google Spreadsheet, all the major RDBMS and OLAP Engines, Excel, Salesforce, and CSV file to your workforce, partners or customers, even if they are on the move.

Best of all? It's free, it's just included in our current offering at no extra charge. connector

Few companies have been as disruptive as They almost invented SAAS, thus changing forever the way people build, deliver and consume software. You know what? They are about to do the same thing they did with CRM but with Databases. is basically a database-as-a-service. It's built on top of the same tried and tested architecture that fuelled the CRM. So it's multitenant, automatically backed-up and basically free from all the operational aspects of running a database. is not a key-value store like most of the multitenant cloud database out there instead is relatively similar to a relational database. So it's good for BI, as you can join and aggregate data within a query. Bime's connector leverage all that and comes into 2 flavors. This allows us to offer the same flexibility as our relational database connectors so you can take a snapshot of your data in Bime's memory (the in-memory approach) or you use the power of the datasource and each of your actions is translated into the language of that datasource (the delegated approach).

The delegated approach offers the user some interesting features. Most importantly, you don't have any pre-design to do when defining your connection in Bime. Enter your credentials and that's it. You can query and browse all the objects available in the API.

Time comparison calculated measure


How to calculate the percent growth of profits for each month of the current year compared to last years?
How to compare the current month with the average of the last 5 months?
How to calculate the year to date actual turnover compared to the year to date budget ?

These are the kind of questions you can answer with Time comparison calculated measures. Comparison is one of the most common data analysis tasks and time is the most used dimension so we tried to make this analysis simple and flexible.


Let's say we want to answer our first question: How to calculate the percent growth for each month of the current year compared to last years?

Let's begin by creating our calculation.

To create a Time comparison calculated measure, you have to create it from the pivot table - just like any other calculation - by clicking on the calculation menu.

The form gives all you need to configure your calculation.

Define the base measure you want to use. In our case it will be profit as we want to calculate profits growth.

Next, let's pick up the time dimension you want to compare. In our case we have only one, shipping date.

Then we have to choose the level. This one may seems a bit tricky at first, but is actually very simple once you get it. If you pick up "month" then this will compare months together, if you pick up "year" this will compare years together. In our case we want to compare months.

Finally, you'll have to define the offset of the start and the offset of the end. In our case we want to compare the months of the current year with the same months of the past year. To do so, we have to define a -13 months offset for both start and end.

Let's spend a bit of time on this and explain what Bime will do here. When on January 2011 it will go back 13 months and take the beginning of this month. Same thing with the end offset but with the end of the month.

If we had to answer the second question, compare the current month with the average of the last 5 months? We would have defined a start offset of -6 month and a stop offset of -1 month.

Once you are done, let's save this and begin to use it. By dropping year and month in my query as well as my Profits measures I can see what's going once I drop my Time comparison calculated measure.

By doing so I can see that for this calculation in january 2011 I have the data of January 2010. In February 2011 I have the one of 2010 so on and so forth. It worked!

To then get my percent growth of profits each month of the current year compared to last I just have to make a growth computation in classical calculated measure. With the formula: (Profits - Last year profit) / Last year profit * 100

Technical consideration.

If you want to understand a bit more of what's going on under the hood please continue. Bime like most OLAP tools is context based, each cell in your result has a cell coordinate in the original data space. For instance, lets take from the previous example, January 2011. When Bime evaluates your time comparison caculated measures it understands it's current context, that is January 2011, and based on your configuration knows how to move from this context to reach another, for example February 2011.

Calculation delegated to the database.

Bime has it's own full featured calculation engine which provides a consistent set of features on top of all the data sources we support. Nevertheless sometimes you want to use the calculation engine of the underlying data source especially when it's a relational database.


  • Line by line calculation. Bime always works at the aggregated level. In the case of RBDMS we try hard to work on aggregated result as it gives a huge performance boost compared to working line by line. The drawback of this approach is that it prevents some calculations from working the way they should. Let's take a simple example of the computation of Turnover = Unit price * Order Quantity. Bime in RDBMS delegated turns this formula into: Turnover = SUM(Unit price) * SUM(Order Quantity). As Bime works on aggregation, the calculation won't give you what you want, the Unit price * Order Quantity computation on each line. With Calculatation delegated to the database now you can write this formula and ask the database to do the computation.
  • Database specificity: some databases have special capabilities like statistical aggregators, geo spatial calculations which you can use straight from Bime.
  • Performance. Some actions run faster in Bime some run faster in the database. All calculations that involves a lot of different elements will run faster in the database as we won't have to retrieve all the data in Bime to do the computation.


Create calculated measures or attributes that are delegated to the database. Use the SQL syntax of the database to write it, not the Bime syntax... and that's pretty much it!

Enhanced pivot table layout.

In the last version of the pivot table, we gave all the query axis the same weight in the interface. Filters had the same space allowed as rows, explosions or trend line measures. That was wrong.

We learnt from usage that most have queries got one element (max) in explosion. Some queries can have a very large number of measures and filters, usually not that many in terms of row elements.

Now the user interface of the pivot table better reflects your usage. The explosion axis has 2 place holders. It can grow to more but the default is 2.

We have moved the filters place holder to the bottom of the chart. This leaves space to add lots of filters. This is especially important as those filters can be turned into data filter prompts in dashboards.

All that releases a lot space for the measures place holder to accommodate many more measures than before. Also an added benefit is that the measure in the browser are now very close to the measure's query place holder so it's much more convenient.

Mix calculation types together

Have you dreamt of creating a group out of a calculated attribute that is using a set based on another calculated attribute? Now it's possible! Joke aside, more often than not you want to combine the calculation types to achieve the right data transformation and presentation and now it's easily doable in Bime.

Anti-alphabetical sort

Bime has a lot of ways to sort. Some of them are simple and some are more advanced.

Before V3.5 Bime has 3 simple sort: Alpabetical ascending, Sort ascending on the first measure, sort descending on the first measure. Now you have a fourth simple sort: alpabetical descending.

Improved CSV export.

We gave some love to the CSV export: you can define in the account settings, the character of separator (; tab etc...) to suit your needs. We have also tried to make the export better by removing unecessary characters and column names in the export. To define you settings go to: Admin > Account.

Sortable data grid.

You can now sort the datagrid in your dashboards by clicking on the column names, however, this option is deactivated once the datagrid has grouped columns or complex results.

Extended Range Date.

This is a major update of the options you have to restrict the time frame. We included new elements like: "All history", and flexible offsets.

Below is just a short example of how this setting can give you the data of the last complete month.

Fine grained control on data filters in dashboards.

You can now reorder and hide your filters in dashboards. Go in edit mode and click on edit the data filters. From here uncheck the filters you want to hide and click on the up / down button to reorder them. Filters have also been optimized in terms of performance and should be much faster.

Better color settings.

Bime has a(n) (overly?) clever feature for assigning colors. It's a form of cache that affects colors automatically if the element has already be seen. For exemple, one column chart has an element called product 1 and bime will affect it a color red. If a second chart has an element product 1 then bime will also affect it a color red. This is really great to achieve consistency automatically in dashboards.

Nevertheless, it was also a pain. As soon as you begin to define precise color settings in your dashboards the cache would override the user settings and it was really hard to do what you want in fine tuning your color settings.

This has been updated. For the sake of retro compatibility your dashboard has the same behaviour as before but if you update the color settings you'll see that you now have to choice:

  • Let Bime set the color for you, like before.
  • Define colors. This option will now garantee that the color will be applied in your chart even if elements of it have been seen before.

Copy and paste your calculations.

Bime is browser based but has a desktop-like user interface. Users expect the same capability as in their desktop apps. Consequently, you can now copy and paste most things in Bime, including your calculations. Just select copy and paste wherever you want - even in another connection.

Automatically update row selector with new values.

Let's pretend you have a chart with a row selector containing product categories and all of them are selected. Your company launches a new product with a new category. By clicking on the header of the selector you can now tell Bime to select all the elements in it. In our example, the new product will be added to the list of selector AND be automatically selected.

This feature is especially useful in keeping your dashboard up to date without having to keep refreshing your data sources.

The theme for the next release will be performance. The aim is to make your analysis and dashboards run fast without having to do any particular tuning. We call this feature: out-of-the box performance.

It will involve a killer new feature called Bime DB and lots of optimizations. This will ship as usual with a bunch of UI and dashboard visualization improvments.