Category: Modern Data Architecture

3 Questions for Matt Maccaux of Dell EMC

Matt Maccaux leads Dell EMC’s global Big Data Practice and he’s one of the featured speakers in our upcoming 2/22 webinar, Building a Modern Data Architecture.

We recently caught up with Matt and asked him 3 questions about his work in Big Data Services.

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What’s Next After Self-Service Analytics?

Accelerate Data Preparation for Agile AnalyticsOver at least the last decade, we’ve seen a steady rise in the demand for self-service BI and analytical tools.

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3 Questions for Mike Moreno of Cloudera

Mike Moreno is the Sr. Partner Marketing Manager at Cloudera, and he’s one of the featured speakers in our upcoming 1/31 webinar with Forrester Vice President and Principal Analyst, Brian Hopkins.

We recently had a chance to catch up with him and get his take on the latest trends & happenings in Big Data & Hadoop.

Attivio: What challenges are you seeing among Cloudera clients?

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What is the Point of a Modern Data Architecture?

Good question. What is the point? The point is to create measurable business value from enterprise data. Of course, before measurable business value comes insight. The Modern Data Architecture (MDA) recognizes that insight can lie hidden in data of all types—structured or unstructured, messy or modeled, historical or realtime.

 

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Have You Thanked Your Data Steward Today?

The other day I Googled, “the problem with a modern data architecture.” Of course, at Attivio we’re big evangelists for an MDA, but it’s always interesting to see what the contrarians have to say. There were over three million returns, but none on the first two pages said a word about problems. Lots of articles about how to develop an MDA or how to optimize an MDA or why you had to have an MDA. You get the picture.

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Chief Data Officers and the Challenges of Big Data

Once Chief Data Officers have identified, confronted, and hopefully overcome the challenges at the bottom and in the middle of the Big Data stack, what’s next?

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OEM Partner Tibco Recognized by Forrester Research

The scope and scale of today’s enterprise challenges are unprecedented in terms of their complexity. Vast volumes of information are scattered across the ecosystem and around the globe, and enterprises often are expected to dynamically retrieve precisely the right data set on a moment’s notice to win a customer’s loyalty. If not, other vendors eagerly await to win that customer’s lifetime business. Every transaction is a lifetime transaction.

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Chief Data Officers and the Challenges of Big Data

Writing on the O’Reilly.com site back in August, CEO Jessie Anderson of Smoking Hand, a training company for Big Data technologies, commented on the overall complexity of Big Data, NoSQL technologies, and the distributed systems that deploy them.

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Chief Data Officers and Data Democracy: The Difference Between Theory and Practice

Chief Data Officers have a lot of things on their plates. And one of those things is giving users freer access to the data they need. This is what we call "data democracy." Most CDOs like the idea of data democracy in theory. But in practice, the CDOs we talk to find that efforts to create a data democracy face at least four common barriers:

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The Modern Data Architecture in Financial Services

An entire ecosystem of tools and data processing frameworks have grown up around Hadoop. Almost as soon as someone identifies a weakness or limitation—and there have been more than a few—someone else creates a fix. That's one of the reasons the Big Data ecosystem is so complex. And why many large companies hung back before jumping in. They wanted to see if any leaders would emerge from the chaos.

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