CIO Leadership, Technology, Big Data

Three Big Data Secrets CIOs need to know today

Psst...many of the good BI practices you've followed apply to Big Data

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Big Data or Big Buzz? It's hard to read an IT publication without "Big Data" splashed across the cover. However, there remain three important Big Data realizations for CIOs that deserve special mention.

1. Data Quality Matters

Let’s face it, you take a lot of pain to run ETL (Extract, Transform, and Load) processes before you load data into BI systems, and it’s important that the same (or some) discipline be applied to Big Data before it is placed alongside traditional data in your BI systems.

Before you embark boldly into a Big Data project, it's important to institute data retention, classification, and archival policies, just as you did the first time around. If at all, these practices are even more relevant given the data volumes and growth with which you are dealing. 

2. Unstructured data is most valuable when analyzed in the context of structured data

There's no doubt that unstructured data contains forward-looking insights that we cannot mine from structured data alone which is typically backward looking. Even so, most people roll their eyes when they hear unstructured data because it is likely that they are thinking about it separately from structured data. The sweet spot is at the cusp i.e. when unstructured data is analyzed alongside structured data (think product managers making pricing or design decisions based on past sales and current social media sentiment).

Like with any BI project, you need to first understand which data is relevant to your enterprise. This could get tricky with unstructured data because given the noisy nature of unstructured data, the more data you process, the more statistically significant (and therefore, reliable) your insights will be. 

3. Big Data is a matter of When, not If

Business leaders have been wooed by Big Data. Better insights from data are a top priority for execs, with an overwhelming 89% saying they want better insights through business intelligence and analytics. With good reason too. One study indicates that top performing companies in almost every business sector were five times more likely to be leveraging analytics.

In some sense, the last decade could be described as a distributed era of BI that is about to give way to the rise of a mission-critical era of BI that will transform BI into a true enterprise-class application, fueled by Big Data. The easiest way to think about Big Data is not as a different animal but as a valuable extension and complement to your existing BI systems, which is really the essence of this blog post.

We recently recorded two podcasts on this topic with the amazing Claudia Imhoff at the Boulder BI Brain Trust - you can find links to the podcasts on the top right corner under Related Links.

In the video below, Silicon Angle experts, John Furrier and Dave Vellante, discuss some of the finer points on Big Data at HP Discover 2012. 

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Pearl Zhu 90 Points | Fri, 08/31/2012 - 16:51

Agree, statistically, data quality is the #1 issue need be mastered, then #2 concerns is about tool: easy to use, better visualization,

I would also add,  besides when, business need figure out WHAT: the big picture about future of business: either for product/service innovation; or for customer experience optimization, or for operational excellence. Seeing is believing. thanks. 

Irshad Raihan 7 Points | Sun, 09/02/2012 - 01:41

Yes, consumption of business insights is an industry in itself. Just as graphs and pie charts are easier to assimilate than figures and tables, visualizations are able to capture multiple complex and disparate data sets into decision-provoking tools. 

There is a really neat demo that shows how Big Data platforms such as Apache Hadoop can be hooked up to visualization tools to enable swift decision making: (Click on "Watch The Demo" in the right nav)

Paul Calento 255 Points | Fri, 08/31/2012 - 14:46

Big Data success often comes down to use case and ownership. Does this start with traditional BI infrastructure?

--Paul Calento

(note: I work on projects sponsored by and HP)

Irshad Raihan 7 Points | Sun, 09/02/2012 - 01:53

Yes, that's yet another way the two are similar. Just as with BI, the BU (Business Unit) vs. enterprise trade-off needs to be weighed. While each BU's use case might be significantly different, the data sets they work with or the algorithms they run could be more similar than they might imagine. There are cost benefits to deploying Big Data technologies as enterprise-wide solutions but some companies struggle with friction between BU's to agree on internal SLA's. A third party (BI consultant, vendor, or system integrator) could help in such situations. Here are some success stories of customers who made the right trade-offs and are on their way to Big Data success.