All this used to be fields – changes in database design revolutionize Business Intelligence
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All this used to be fields – changes in database design revolutionize Business Intelligence

Sponsored By Dimensional Insight

Massachusetts’s own Dimensional Insight business intelligence (BI) company have an admirable turn of phrase. They refer to the fetching and presentation of complex data sets as a ‘Dive’. The organization’s overarching code base is, perfectly logically, called the Diver Platform (currently in its 7.0 iteration).

And while the company’s BI offering continues to go from strength to strength across all types of enterprise (professed specializations include healthcare, supply chain management, and alcohol/beverage concerns), the internal development team never rests on its laurels.

Anyone who’s had more than a passing interest in BI will be aware of the trend in recent years to move the data structures required to produce useful, actionable data, to a format that is more efficient.

Relational database design is nearly as old as computing itself, but the underlying structure of most databases remains the same as it was back in the 1970’s. Data is based on rows (records), each containing multiple fields of differing data:

UiD Name Description Price Percentage
Unique Short text Long text FP numeric FP calculation
Unique Short text Long text FP numeric FP calculation
Unique Short text Long text FP numeric FP calculation…etc

However, for even basic reporting, it’s effective in computing efficiency terms, to be able to take a column in its entirety in order to, say, calculate an equation vertically.

Transferring database records to a columnar (or column-based) schema and working from that cuts processing time and can take advantage of the latest breakthroughs in memory speed, multi-thread parallel processing, and fast, cheap storage.

In environments where massive datasets are drawn from varied systems, opening markers of multi-tabs which encompass multiple time frames can involve a wait which involves seriously expensive chunks of decision-makers’ time.

By employing Dimensional Insight’s Spectre technology, the data is seamlessly rendered (in the background) into this more efficient structure, and calculations are rendered in pure machine language.

The outcome? Truly remarkable speed increases, with obvious initial time-savings. Across the enterprise, then, the ability to quickly search deeper, more complex data sets more often: thereby achieving greater insights to improve an organization’s function.

columnar-databases-400x250

Such effective harnessing of computing power would be, of course, of little value if it didn’t underpin some truly remarkable solutions. The Diver Platform presents the right information in the right way, allowing users to drill (or dive!) into data in any path they see fit (no templates here to constrain investigation areas).

A single Diver platform can contain multiple cBases (columnar databases) as well as instances of the company’s other engine, Model.

As well as a mobile portal, the company’s offering also includes data governance (data cleaning and organization, if you will), product training and consultancy services.

Dimensional Insight has carefully positioned their product so it’s accessible by a standard point-and-click GUI, rather than cloaking the business functions behind a query language interface.

This makes the product viable in real-world situations where multiple data instances need to be collated and processed without specialized tech guidance – across modern healthcare organizations’ different departments, for example.

To find out more, or speak to a representative, get in touch with Dimensional Insight today to request a demo. The company also offers an attractive reseller program for qualified distributers.

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