Making sense of big data

  • There are some organisations which do a good job explaining big data
  • Others, however, ignore a reality that is far more dynamic and complex

Making sense of big dataIN the late 1990s, every web business wanted to be known as an Application Service Provider (ASP), Since then, the same folks are now Software-as-a-Service (SaaS) companies.
Similarly, almost every hosting business during the mid- to late 2000s (not to be mistaken for data centre providers) scrambled to print new business cards claiming to be the leading Information-as-a-Service (IaaS) provider.
Big data is currently the latest fad, as almost every database, data warehousing, business intelligence, visualisation and to some degree analytics player is either pondering or already in the midst of reprinting its business cards to project itself as a big data business.
This article will attempt to demystify the proverbial blind men’s big data elephant.
Too much big data mysticism
I have nothing against big data. In fact, I find Google’s open source gesture of releasing the technology base to Apache as humbling.
As I look back at the data industry – if business intelligence was the prophecy, then big data may as well be the harbinger that clears the path, because no one has really seen the prophet yet.
And I dare say that big data in its current ‘oversold’ form will likely make Asimov’s Psychohistory a reality. (Note: Sarcasm for those who do not know who Isaac Asimov is).
Fortunately, there are in the market better organisations which do well at explaining big data, such as Cloudera, Informatica, Teradata and even Oracle and IBM, given their pedigree in data technology.
Other aspirants, however, focus too much on the mysticism surrounding big data while ignoring a reality that is far more dynamic and complex.
The crux for me is the business leadership and capability to ask the right questions for decision making executed by integrative thinkers; else, the big data elephant acquisition will likely be stricken with albinism.
The big data technology reality
The difficulty in attaining a solution and outcome from data technology lies in the need for real people to be heavily involved.
Here’s an attempt at clearing up the major components of data management. Note that these are my own abstracted terms:

Making sense of big data
Making sense of big data
Making sense of big dataMaking sense of big dataMaking sense of big dataMaking sense of big data
I do hope that business leaders, CIOs (chief information officers) and fellow vendor peers would celebrate big data not as an ostentatious ego-boosting technology with hopes of appearing in CIO Asia 100, but to unleash the technology’s potential through the ability to ask the right questions, to perform analytics with the intent of affecting positive business impact from the results, and finally; the discipline and ethics to capture reliable data in the first place.
To close, technology alone does not differentiate; even more so when the ecosystem is still grasping at straws as to ‘how’ they can wield the technology. Humbly, true differentiation is only achieved from proven business outcomes and satisfied customers.
Bernard Sia is head of strategy at Mesiniaga Alliances Sdn Bhd. His opinions here do not necessarily reflect the views of Mesiniaga.
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