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November 22, 2015

Democratising data analytics to escape the bottleneck

C-level briefing: CBR speaks to Tom Cahill about the challenges of competition in the data analytics market.

By James Nunns

13 years ago Tom Cahill, VP EMEA, Logi Analytics was using Crystal Analysis, an application designed for analysing business data. In October he joined Logi Analytics and has had previous roles with Jaspersoft and Talend.

Logi Analytics aims to put data analytics in the hands of the everyday user, a democratisation of analytics if you like with its self service product.

Cahill said: "13 years ago I was a bottleneck." This identifies a key element that self-service analytics is trying to remove. By allowing the average user to run analytics, it is no longer the reserve of data scientists who are overwhelmed by being the only source of data analytics.

With words of praise for Salesforce analytics for some use cases and Talend being a: "Trend setter for several years," Cahill certainly identifies that there is a large amount of competition in the big data market, but also said that a lot of Big Data companies are thriving, suggesting that the competition isn’t hurting growth.

On competition, he doesn’t see the moves into the analytics market from the likes of AWS, Google and Microsoft Azure as particularly threatening.

Cahill says that there is a lot of heavy lifting involved in doing analytics in the cloud and although there has been: "Advances in cloud that help agility, it’s still not dependent enough in a single use case."

He went on to say that BI or analytics-as-a-service have very siloed use cases and are limited in terms of moving large amounts of data in the cloud.

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"It’s enormously difficult with all sorts of third party systems to really leverage as-a-service, it’s going to be used for certain use cases."

While the company‘s software aims to be easy to use for the average business person, it also aims to appeal to data scientists and finding the balance between simplicity and complexity is a challenge.

"It’s a critical question, I don’t know if there is a one size that fits all."

The focus on self-service analytics helps to make it more customisable to the user, removing the demand of infrastructure change caused by some larger scale deployments of analytics services.

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