Fractal Analytics Blog

How much horse power does an elephant have?

How much horse power does an elephant have?

Raunak Jhawar
By Raunak Jhawar
July 6, 2015

Well, it’s kind of hard to compare power since it depends on how you are measuring it and I cannot give you meaningful number if I am comparing apples to oranges.

Elephants are usually not used to pull carts like horses, so their useful “power” lies more in their trunk than their leg muscles.

Interestingly, the same mass of horses can pull more weights than a same mass of elephants (horses are more efficient).

However, each elephant is much bigger than each horse; an elephant obviously has more physical strength. But wait, why we are discussing about animal strength and their capability to do work, I am not a student of Zoology but I am a student of computer science and I have executed and controlled many procurement and spend analytics cubes for my customers delivering precisely what can now be called as ‘Traditional BI’ and, I would not have said I find any missing piece from the information jigsaw puzzle the enterprises of today are solving day in and day out, well not really.

What is Traditional BI?

Before I begin, two of the notable quotes of William Edwards Deming (click here) which I would like to list here are:

The most important things cannot be measured.

The most important things are unknown or unknowable.

The ultimate goal for any successful traditional BI deployment has been the finesse of “traditional IT” team to create charts and share the “historical numbers” to leverage the capabilities of a data reporting/visualization tools of choice. This essentially enabled the sales force and the management to make decisions whether a product is market leader (or a market laggard) in its category or decisions which would eventually change the course of action how for product is perceived by the markets

Most BI vendors have worked on the theme to consolidate data and develop robust data pipelines and/or deploy OLAP cubes on the data which is “readily available” for consumption in popular formats such as delimited files or database platforms of choice.

When talking about predictive analytics such as forecasting how well (or worse) a product will do for next quarter using “traditional BI”, the computation relied on not so sophisticated data extrapolating techniques. Most likely these analyses were based on the already available “historical numbers” from “known” data sources for which a connector or an API is available to read/write data.

Traditional BI – you have done a great service so far and you continue to be a reliable backbone to great management systems powering all scales of enterprises in today’s time and no one, not even the most cutting edge systems built till date will dare to write your epitaph.

But if this were to be true then why is everyone in the tech community talking more about ‘New age BI’?

What is New age BI?

A lot has changed in the BI community since year 2010. The dominant BI vendors in the tech community embraced open source, they started talking about distributed computing (read as herd of elephants), the cloud, and advanced statistical methods to solve the business problems.

The expensive computer hardware (read as horse power) deployed by customers to solve new age data problems are now facing a new challenge in form of low cost counterparts which offer the added benefit of distributed and parallel computing.

More matured BI systems are now being created which offer insights not only from data which can be easily captured and stored and retrieved on demand, but also from new generation of data sources offered by internet of things (IoT) like machine-machine interaction (click here) thereby taking personalization to a whole new level altogether.

To conclude, the new age BI is certainly not an alternate but should be seen as a complementary feature to enrich user experience. After all, “In God we trust, all others bring data.”


About the author:

Raunak is a Computer Science graduate with 6+ years of global IT services experience in large-scale distributed systems and 2+ years in program management in managing, delivering and analytics strategy and consulting assignments across a wide range of industries.

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