The bimodal BI journey

October 04, 2016

After the post, watch the video detailing how TARGIT can help you find the Holy Grail of bimofal BI to transform your approach to data discovery and data management. The future of BI is here, it's time to embrace it.

I work in a company with a long history in the BI Landscape. The 1.0 version of our TARGIT Decision Suite goes back to the previous millennium. In those days (and up until recently) BI was all about some of these mantras:

1. One version of the truth 
“Let’s once and for all agree on the right way to measure our organizations performance and bring that validated and agreed truth to the masses.”

2. Data governance 
“Let’s create a central all-knowing admin – Big Brother knows exactly what data you access and who you share it with.”

3. Pervasive BI 
“Let’s share actionable insights with the full organization custom tailored for the intended receiver and accessible on all platforms."

In short: enterprise BI.

The first part of our history was a long journey of developing and refining tools that supported those ideal virtues of the enterprise BI platform, all wrapped in drag-and-drop functionality requiring no technical skills.
  • A simple architecture dictating central control of data sources available
  • Fully extended governance of data access and user rights done by central administration 
  • Real pervasive BI supported by:
    • Dashboards and reports easily shared in the organization (and outside if required) on all platforms
    • Distribution tools on ad-hoc basis or by schedule 
    • Data-driven alerts monitoring data by user defined rules
    • Storyboards reflecting live data ready for public display or sharing internally
  • A theoretical basis behind our single all-in-one platform 
    • OODA philosophy – every feature in TARGIT Decision Suite supports a phase in our perception of the typical decision process (Observation, Orientation, Decision, Action).
    • TARGIT Momentum – the implementation process, defining which personas in the organization requires what information on what level. 
    • Your “cookbook” to building a portal of information serving the full organization so to speak…
    • Later to be supplemented with the TARGIT Journey philosophy, but I’ll get to that in a minute.
In the meantime, you should familiarize yourself with the TARGIT Journey with this free eBook that describes the steps: 3 Stages of Becoming a Data-Driven Organization.

BI Journey

Fast forward to today: The data discovery wave has rocked the boat. The speed of change in the world around us requires a supplement that allows self-service BI and has introduced the buzzword “bimodal.”

Bimodal means that you embrace both "old school" enterprise BI and "in vogue" data discovery.

“Old school” enterprise BI as described above is well-organized, validated data accumulated in formalized data warehouses. Data is secured and trustworthy and access to data is regulated by roles defined by central admin.

“In vogue” data discovery allowing quick, ad-hoc import of practically any data source and quick mashup with existing data.

The typical gain of modern data discovery is speed and flexibility, which is needed in a volatile modern world. The typical loss is certainty around the validity of data. Business logic applied to data may be lost or interpreted differently from analyst to analyst and the overview of who is sharing what with who is non-existent.

Quite a few tools were born as a part of the new wave. These tools are by nature data discovery tools created for analysts and data scientists for exploration purposes. However, the initial versions launched by these vendors offered practically no data governance options. That's because the validation process was sacrificed in favor of speed. Additionally, the sharing and distribution options were typically absent or inadequate (they were meant for one-man armies, not pervasive BI).

The core purpose of these early versions was to arm single individuals in the organization to go out and do real data discovery. Analysts on the hunt for new insights beyond the ones uncovered using the enterprise tools.

As time passed, data discovery tools became very popular. Typically, someone in an organization downloaded one of these tools and dazzled his colleagues by bringing in new data sources, mashing them up, and showing visual representations of data in a matter of minutes. This is something that previously would have required expert help and time consuming processes of validation and data modelling.

The tool was then adopted by other parts of the organization and these data discovery vendors succeeded in such “land-and-expand” strategies. This brought new user groups into the world of data discovery and raised the question if enterprise BI was becoming redundant.  

A complication arises

And then something interesting happened. Data discovery tools were chosen as the standard tools (and only tools) in some organizations. Instead of an explosion of new useful insights however, the only outcome from this was chaos.

No one was sure if data was valid. Different analysts could come up with conflicting “truths” because their analysis was based on different data sources or calculated using slightly different business rules. Sharing data in the organization proved to be cumbersome at best.

Something was wrong.

Now we have arrived to current time. The data discovery vendors today talk about central admins, data governance, validation processes, and forcing business logic implementation in formalized data warehouses. Even scheduled distribution of reports has become fashionable again.

So here we are. The data discovery tools are maturing by integrating all that stuff they left out in the first versions. They are on a journey towards becoming bimodal.

In the meantime, the enterprise BI tools went for bimodal territory from the other angle. TARGIT was no exception. We recognized the customers’ need for speed and agility and introduced TARGIT Data Discovery as an integrated part of our TARGIT Decision Suite. 

Our journey towards being truly bimodal had a starting point where all the fundamentals were in place. That makes a huge difference.

In that context – getting back to the TARGIT Journey philosophy – we addressed the journey involved for everyone in the BI marketplace and described the journey of becoming a truly data-driven organization.

Every journey has a starting point, and in the TARGIT Journey, your first goal must be to establish a data foundation that is a trusted reference point to everyone in the organization and then you are ready for exploring what is beyond the horizon.

After all, how can you possibly understand the world around you if you don’t fully understand yourself?

Exploring beyond the horizon

Having a solid understanding of your organization's general state based on valid, trustworthy data will be a big help on your journey towards data discovery.

In the journey we describe, you learn as you go. Your first attempts at data discovery will be more or less experimental. But as every scientist will tell you: it’s the knowledge you already have that helps you set up the right experiment using the right data. You can leverage the comprehensive knowledge that already exists in your enterprise data warehouse to choose exactly which experiments to go with and which hypothesis to test.

Now you add some external data and mash it up with existing in-house data to test a hypothesis on correlations that might or might not exist. As experiments go, some of your hypothesis will be falsified, which helps the organization to know what not to focus on.

Other experiments might show correlations that really add value and make you change operational decisions or even adjust strategy. You’ll often want to consolidate this type of knowledge. Your data discovery model will be promoted to be a part of your enterprise BI setup. Data discovery will be your prototyping tool that helps develop your enterprise BI strategy.

Embrace the journey

Every traveler knows that every journey is different. In this case, everyone’s journey seems to have the same goal: bimodal BI. This is the Holy Grail of balance between validity, pervasiveness, governance, and agility.

The direction of travel however seems to be drastically different for vendors in the market. At TARGIT, our journey has been going in the same direction as we recommend our customers to travel:

From a valid, trustworthy, pervasive, governed data foundation to support decision makers in alignment with company strategy ...

... To making discoveries that require agile action and adjustments to strategy and processes involved. 

That seems to the natural and healthy way to travel, doesn’t it? Watch the video below to see how TARGIT can help you find the sweet spot of bimodal BI to transform your data and your company.

Niels Thomsen

Solution Architect
I’m eager to study the trends of the BI market and compare them to the actual implementations that take place worldwide. My position of Solution Architect at TARGIT has me covering all aspects of turning data into insight, from technical setup to end-user training. I create data warehouses and user friendly analyses and reports that enable our custom..
Continue Reading...

We use cookies to improve your site experience, but they also provide us with information on your use of our website.
To find out more about the cookies we use and how to delete them, see our Privacy Policy. By continuing to browse the site, you are consenting to our use of cookies.