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Turbo Charge Enterprise Analytics with Big Data

March 13, 2017   |   1:49 PM
Big Data Analytics
Teradata Articles

by Renato Manongdo, Teradata

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We have been showing off the amazing art works drawn from numerous big data insight engagements we’ve had with Teradata, Aster and Hadoop clients. Most of these were new insights to answer business questions never before considered.

While these engagements have demonstrated the power of insights from the new analytics enabled by big data, it continues to have limited penetration to the wider enterprise analytics community. I have observed significant investment in big data training and hiring of fresh data science talents but the value of the new analytics remain a boutique capability and not yet leveraged across the enterprise.

Perhaps, we need to take a different tact. Instead of changing the analytical culture to embrace big data, why not embed big data into existing analytical processes? Change the culture from within.

How exactly do you do that? Focus big data analytics to adding new data points for analytics then make these data points available using the current enterprises data deployment and access processes. Feed the existing machinery with the new data points to turbo-charge the existing analytical insight and execution processes.

A good starting area is the organisation’s customer events library. This library is a database that contains customer behavior change indicators that provide a trigger for action and provide context for a marketing interventions. For banks, this would be significant deposit events (e.g. three standard deviations from the last 5 months average deposit) and for Telco’s significant dropped calls. Most organisations would have a version of this in place and would have dozens of these pre-defined data intervention points together with customer demographics. These data points support over 80% of the actionable analytics currently performed to drive product development and customer marketing interventions.

What new data points can be added? For example, life events that can provide context to the customer’s product behavior remains a significant blind spot for most organisation e.g. closing a home loan due to divorce, or refinance to a bigger house because of a new baby, etc. The Australian Institute of Family Studies have identified a number of these life events.

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Big data analytics applied to combined traditional, digital and social data sources can produce customer profiles scores that become data points for the analytical community to consume. The score can be recalculated periodically and the changes become events themselves. With these initiatives, you have embedded the big data to your existing enterprise analytical processes and moved closer to a deeper understanding to enable pro-active customer experience management.

We have had success with our clients in building some of these data points. Are you interested?