Mark Barrenechea

Security is Job 1: Machines vs. Machines

By Mark Barrenechea | December 11, 2019

Digital is redefining cybercrime and cyberwarfare Cyberattacks today are multi-stage, hard to discover and highly targeted. Some security threats are

Zdnet

The dark side of IoT, AI and quantum computing: Hacking, data breaches and existential threat

By Cloud Syndicate | January 15, 2020

Emerging technologies like the Internet of Things, artificial intelligence and quantum computing have the potential to transform human lives, but

6 Practices to Realize a Long-Term Data Vision Through Near-Term Work

Over the years, enterprise data strategies have been in a perpetual pendulum swing – from no strategy at all to way too much.

On one extreme, every analyst, data scientist or analytic application development team must find, access, translate and integrate all the data they need. This leads to some success with individual use cases, but burdens practitioners with excessive and redundant work while creating an unmanageable mess of data across the organization.

On the other extreme, data management professionals create a “foundation” of data for any and all uses, deploying one data domain at a time while attempting to identify every attribute and solve every data quality issue within each domain. This leads to projects that take too long, cost too much and deliver a fraction of the value that was expected.

Thus, the pendulum swings back and forth, back and forth.

The solution to this enduring dilemma is to find the middle way; that is, to carefully construct projects to focus directly on near-term value while contributing to an enterprise foundation at the same time.

An effective data strategy delivers (mostly) only the data needed for near-term use cases. To support these applications (preferably delivered by separate projects outside of the data team’s responsibility), the approach integrates only the data elements needed and solves only the data quality problems that affect the in-scope business objectives. And to simultaneously build an enterprise foundation, each small, focused data delivery also contributes its puzzle piece of data to fit into the larger enterprise data puzzle…

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THOUGHT LEADERS

Anurag Kahol Bitglass

Four Trends Driving Demand For Data Security

Data Security Trends 2017 will be a hallmark year for security in the enterprise as all industries have reached a

Shadow It

Four Reasons Why CIOs Must Transform IT Into ITaaS To Survive

CIOs Must Transform IT The emergence of the Cloud and its three delivery models of Infrastructure as a Service (IaaS),

Big Pivot Cios

Big Pivot Podcast: How To Become A More Effective CIO

Become A More Effective CIO The Big Pivot podcast, put together by IDG and Informatica, looks at how CIOs are