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The future of data: A 5-pillar approach to modern data management

CIO

This approach is repeatable, minimizes dependence on manual controls, harnesses technology and AI for data management and integrates seamlessly into the digital product development process. Operational errors because of manual management of data platforms can be extremely costly in the long run.

Data 167
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To ensure AI success, map your value streams, says Neudesic

CIO

Australian organisations are not moving as quickly as their counterparts in preparing for and fully adopting AI for business transformation. Research from IBM indicates that only 15% of global businesses have established themselves as leaders in AI implementation, while the majority remain in early experimental phases.

Azure 117
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Enhancing customer care through deep machine learning at Travelers

CIO

s SVP and chief data & analytics officer, has a crowâ??s s unique about the [chief data officer] role is it sits at the cross-section of data, technology, and analytics,â?? s unique about the role is it sits at the cross-section of data, technology, and analytics. s a unique role and itâ??s

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Building a vision for real-time artificial intelligence

CIO

He had been trying to gather new data insights but was frustrated at how long it was taking. All of this needs to work cohesively in a real-time ecosystem and support the speed and scale necessary to realize the business benefits of real-time AI. Real-time data doesn’t exist in silos; it flows in two directions across a data ecosystem.

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DataOps – A Catalyst for Enterprise Business Transformation

RapidValue

DataOps aids data practitioners to continuously deliver quality data to applications and business processes. The end-users of data, like the data analysts and data scientists, work closely with both data engineers and IT Ops in order to deliver continuous data movement.

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Snowflake and Capgemini powering data and AI at scale

Capgemini

But, more practically, data and BI modernization are the creation of a data foundation of secure, trusted, and democratized data to support AI and analytics at scale. This is a critical consideration as many organizations face data-estate hurdles. To read the full whitepaper, click here.

Data 52
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The IBM Press Release on Spark That Every Tech Leader Should Read

CTOvision

They also launched a plan to train over a million data scientists and data engineers on Spark. ARMONK, NY - 15 Jun 2015: IBM (NYSE:IBM) today announced a major commitment to Apache®Spark™, potentially the most important new open source project in a decade that is being defined by data.