The Powerful Potential of Making Data Actionable with an Analyst-Driven Approach

Related Topics: Data & Analytics

by Debashis Rana – 

Knowledge is power.

That’s a commonly accepted truism that has been around for a very long time. There’s only one problem with that truism: It’s not true. Or, to put it differently, that truism must be qualified to remain relevant in this age of Big Data.

Just adding one word makes all the difference in making that old saying modern and accurate: Useable knowledge is power.

But you can only tap into that power by using that useable knowledge.

Banked Data Doesn’t Earn Interest

The term ‘data bank’ has also been around for a while, but you don’t hear it all that much anymore. And that’s a good thing because it’s somewhat of a misleading term.

It implies that data that is socked away in storage is of great value, like money in the bank. But in fact, that banked data is worthless. Unlike stored money, which can at least earn interest income, stored data is of no value.

Data must be used to provide value. And the faster you can put data to work, the more value it provides.

Don’t Bank it; Use it—FAST

The traditional approach to taking data from raw to usable is a very IT-intensive process. This approach is anything but fast; making raw data usable normally takes many weeks or even months. This method of making data actionable typically revolves around the traditional SDLC process, and it just takes forever.

But what if you could cut out the IT middleman, and have a data ingestion and manipulation process that involves no programming? It would be orders-of-magnitude faster.

And that’s exactly what we’re doing. We’ve developed an analyst-driven approach that teams our solution accelerator, RCG|enable™ Data Ingestion, with Trifacta Wrangler Enterprise.

An analyst-driven approach bypasses the need for traditional IT skillsets such as programmers, database administrators, etc.

Massive Time-Savings Potential

How much faster can data be transformed from raw to actionable using this approach? On average, I would estimate an acceleration rate of anywhere from 60% to 75%.

Consider this recent example…

We were building a credit analytics dashboard for an RCG customer: a regional bank. As is typical, we needed to ingest raw source data from multiple systems. The goal was to manipulate the data to take it from raw to actionable by visualizing it on a dashboard. A typical timeline for a project of this type using the traditional approach would be anywhere from 10 to 16 weeks.

We did it in four weeks.

Ancillary Benefits

Cutting out the IT middleman and giving analysts the power to make raw data actionable certainly saves lots of time. But this methodology provides some other direct benefits.

Cost-savings, for example. All of those IT skills that we’re eliminating are expensive skillsets. Eliminating dependency upon those skills provides substantial cost savings. In our bank dashboard example, we did the project with a smaller team than what a traditional approach would have required.

But perhaps the most important benefit of this process takes us back to that old saying: knowledge is power. Because usable knowledge truly is power. In this age of Big Data, massive quantities of data are available. But much of that data is time sensitive; the longer it sits unused, the less value it provides.

More than ever before, making that knowledge easily and quickly usable is the true source of power.

Read more about speeding data integration in one of my previous posts


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