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Big data projects can frustrate end users thanks to an often slow time to value. Channel partners, meanwhile, may enjoy business from consulting around this, but there is greater opportunity to be had in proper data wrangling.

International SI Excelerate Systems started building its big data practice in 2009. CEO David Bennett says until it partnered with data wrangling vendor Trifacta, it was spending a lot of time getting customer data ready for ingestion.

As a result, Bennett saw customers’ big data projects take as long as years before providing desired results.

“Customers get excited [and ask] ‘when can we do the new business insights? When can we do the analytics we think big data can provide to us?’. And it takes sometimes…two years to get the data ready,” he toldChannelnomics.

“It was all about this issue with wrangling the data into a form that the users can actually use. That’s good for us because it obviously generates a significant amount of consulting activity, but in terms of time to adoption, time to value and ROI for customers, that’s obviously a very frustrating process. And the more data you have and the more resources you have, it becomes a more time consuming and ultimately expensive process.”

When it comes to big data, channel partners are looking to make projects productive as soon as possible because there is often a “long line” of use cases behind a customer’s current project, according to Bennett.

The executive says that using data wrangling to shorten the time it takes to get customer data ready speeds up adoption of new use cases, as well as the expansion of the big data infrastructure a customer is trying to build.

“So we’re able to travel up the value chain…from just ingesting and transforming the data into building the use cases,” Bennett said.

And while data wrangling may help a channel partner better earn a spot in customers’ big data projects, Bennett notes that in the end, a big data project cannot be successful if end users are not investing in learning more about the emerging technology.

“We learned that a couple of years ago,” Bennett said. “Customers willing to invest in training, knowledge transfer and skills acquired inside their own organization are much more likely to be successful.”

This article was originally published on www.channelnomics.com and can be viewed in full

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