Ramon Chen

While life sciences companies continued to make inroads towards patient-centered thinking, the main pursuit of a complete, 360-degree view of customers typically classified as healthcare professionals (HCPs), still dominated the investments and thinking of the majority of organizations. To that end, great strides were made by taking a significant step up in data management capabilities. Life sciences companies from startups all the way to F500 giants have shunned and started to shed the anchor… Show more

While life sciences companies continued to make inroads towards patient-centered thinking, the main pursuit of a complete, 360-degree view of customers typically classified as healthcare professionals (HCPs), still dominated the investments and thinking of the majority of organizations. To that end, great strides were made by taking a significant step up in data management capabilities. Life sciences companies from startups all the way to F500 giants have shunned and started to shed the anchor of heavyweight, on-premise software that used to cost IT teams millions of dollars in implementation resources. Show less

Reltio' CMO list the Top 5 Predictions for Analytics, Data Management and AI for 2017

Ah, the joys of Christmas mornings. Waking up, seeing the presents under the tree.

It got us thinking. Do B2B marketers have Christmas wish lists? What do they fantasize finding under the metaphorical tree?

Providing a pulse on important new trends leading into next year, insideBIGDATA reached out to a variety of vendors to get their insights, reflections and predictions for what may be coming. Reltio contributed insights in 3 areas related to AI, Big Data and Security.

Offering flexible work schedules requires a bit of trust, but it is worth it. Time is important – perhaps more so today than ever before," he says. "We trust employees to work during the hours that suit them and remove the requirement to commute everyday – an alluring perk in the San Francisco Bay Area.

With consumers using more and more varied shopping channels, and the expectation of hyper-personalization and engagement growing, retailers often struggle to deliver the right messages to the right consumers at the right time. Data can go a long way here, but only when it’s first managed, organized and presented in a way that allows everyday business users, such as those in sales and marketing, to use it in their everyday efforts to reach customers.

Moving forward, MDM can offer tremendous benefits as a component of a modern data management platform, fully integrated with data-driven applications and delivering fast time-to-value across the enterprise. But without a high level of modernization that adapts freely from consumer equivalents, it’s headed toward legacy status.

It’s 2016 – why haven’t the problems surrounding data been solved? Certainly there are better tools, more experience, and better insight into the problem than 10-15 years ago. Why is data still such a big problem for the vast majority of companies?

Rather than viewing compliance as a necessary evil, life sciences organizations have a transformational opportunity as part of a shift towards a data-driven culture. Being able to put in place technology that improves the operational efficiencies of individuals includes freeing them of compliance burdens. This 2-for-1 is a significant competitive advantage that cannot be overlooked by any organization looking to achieve commercial and R&D excellence.

Data volumes show no sign of abating. Although storage and processing is now affordable by companies of all sizes, turning data into actionable information is an increasing challenge. This article describes how you can get a comprehensive, reliable, 360-degree view of people, products, organizations, places and their interactions, to be used for personalized insights and actions.