Gartner Data & Analytics Summit: How to scale the value of data and analytics?

Publish date:

With over 70 sessions ranging from keynote addresses to presentations, has the Gartner Data and Analytics Summit lived up to its expectations? Read this blog to find out.

In more than 70 sessions, Gartner analysts and industry speakers have looked into what it takes to become an insight-driven enterprise. At the Gartner Data & Analytics Summit which was held on  October 23, 2018, at Frankfurt, many of the presentations focused on how to do AI right. Speakers endorsed governance on the data front. They emphasized cataloging the data landscape, ensuring data quality, and enforcing data access control with transparent policies and strong encryption at rest and in transit. The presenters also stressed evaluating the value of data and balancing investments accordingly.

On the analytics front, ethics were on everybody’s mind. Analytics and artificial intelligence may be transforming our lives, but the industry has to reconsider privacy, fairness, transparency, and trust to avoid the inherent risks. These requirements can be partially incorporated into the data scientist’s toolbox and methodology, but the responsibility rests also on the shoulders of the organization. For this reason, many companies and associations have started defining a code of conduct for big data analytics.

Behind the scenes

Honestly, many participants didn’t come here to talk about their concerns over AI. Instead, they were looking for ways to accelerate their journey in machine learning (ML) – and, they found a plethora of ideas in overcrowded rooms where start-ups promised a bright future with automated machine learning (AutoML). These modern AutoML platforms probably won’t take data scientists’ jobs away. They will instead take over repetitive tasks and substantially accelerate the building and deployment of predictive models. So, now is a good time to jump on the AutoML bandwagon.

At the Capgemini booth

The Capgemini booth highlighted artificial intelligence. We met both potential and existing clients, and their main interest inevitably was finding a killer AI use case for their business. We showed them real Capgemini use cases related to their industry and discussed how to approach them in their IT landscape.

To wrap it up: We have received much guidance from Gartner on the strategy for data and analytics plus brilliant ideas from the contributing vendors for the real world problems. Now it is our turn to drive the journey to the insight-driven enterprise even further and meet again next year at the Gartner summit.

Authored by: Rudiger Eberlein

Email ID: rudiger.eberlein@capgemini.com

 

Related Posts

AI

The impact of artificial intelligence (AI) on business and insights

punamchavan
Date icon December 4, 2018

The premise behind AI is to mimic a human brain inside a machine. But what is AI and what are...

AI

Financial services firms are leveraging RegTech solutions to keep regulatory compliance costs in check

Amit Choudhary
Date icon December 3, 2018

RegTech can automate procedures that were formerly done manually to streamline difficult...

AI

AI and the Janus face of the GDPR – chance or challenge?

Pierre Adrien Hanania
Date icon November 30, 2018

Since artificial intelligence (AI) is driven by data, experts in this field will have to shed...

cookies.

By continuing to navigate on this website, you accept the use of cookies.

For more information and to change the setting of cookies on your computer, please read our Privacy Policy.

Close

Close cookie information