The Smart Data Blog

Marty Loughlin

Recent Posts

Show Recap: Gartner Data & Analytics Summit 2017

Posted by Marty Loughlin on Mar 21, 2017 5:02:00 PM

Earlier this month, the Cambridge Semantics team set off for Grapevine, Texas, for the Gartner Data & Analytics Summit 2017 to join more than 3,000 big data industry customers, Gartner analysts and solution providers in the continuing discussion on driving business intelligence and analytics forward.

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Topics: Data Lake, Graph

2016: The Year of the Financial Smart Data Lake

Posted by Marty Loughlin on Jan 21, 2017 2:12:00 PM

With compelling business use cases, adoption of open industry standards and enterprise deployment of high performing scalable platforms, 2016 was a breakout year for the adoption of semantic graph technology and the Smart Data Lake® in Financial Services.

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Topics: Smart Data Lake

Ten Reasons to Dive into the Smart (Semantic) Data Lake

Posted by Marty Loughlin on Jan 11, 2017 12:14:00 PM

The data lake is a modern and rapidly evolving data architecture. It promises ubiquitous access to enterprise data with compelling benefits in terms of cost and agility. Yet, in many cases, this promise has not been realized.

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Topics: Data Lake, Smart Data Lake

Cambridge Semantics Shatters Previous Record of Loading and Querying ‘Trillion Triples’ by 100X - So What?

Posted by Marty Loughlin on Dec 20, 2016 4:37:00 PM

"So what?" you might say. Another hyperbole-fueled headline in tech is hardly a notable event. To answer, let's start with what we did.

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Topics: Big Data, Anzo

Finding Alpha in Diverse Data

Posted by Marty Loughlin on Jul 6, 2016 12:00:00 PM

The challenge for analysts seeking trading opportunities that outperform the market is not a lack of information. It is an over-supply of information from widely disparate sources. How do you sift through the overwhelming flow of reports, news feeds, articles, blogs and social media posts to find the sentiments, relationships, patterns, unique insights and powerful nuggets of information that drive performance?

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Topics: Big Data, Unstructured Data

A New Approach to BCBS 239 and Beyond: The Smart (Semantic) Data Lake

Posted by Marty Loughlin on May 24, 2016 9:30:00 AM

We are at an inflection point in the financial services industry. The evolving and overwhelming demands of regulatory compliance have forced organizations to acknowledge the need for data governance and most are developing their strategy.

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Topics: Data Governance, Financial Services, FIBO, Data Lake, Anzo

FIBO, FIBO, It's Off to Work We Go

Posted by Marty Loughlin on Apr 4, 2016 1:11:44 PM

State Street Bank, The EDM Council, Dun & Bradstreet, Wells Fargo and Cambridge Semantics completed an engagement to harmonize State Street's Interest Rate Swap data with Dun & Bradstreet's entity hierarchy data using the Financial Industry Business Ontology (FIBO) and Cambridge Semantics' Anzo Smart Data Lake®.

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Topics: Smart Data, Big Data, Financial Services, FIBO, Compliance, Anzo, Analytics

5 Reasons Gartner BI & Analytics Summit Attendees Flooded the Cambridge Semantics Booth

Posted by Marty Loughlin on Mar 23, 2016 6:37:52 PM

On my flight back to Boston from Grapevine, TX, where we spent three exhausting and exhilarating days at Gartner BI & Analytics Summit, I am reflecting on the great interest shown in Cambridge Semantics Smart Data Lake at this event.

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Topics: Smart Data, Data Management, Data Integration, Big Data, Analytics

5 Data Lake Capabilites Essential to Business Success

Posted by Marty Loughlin on Aug 31, 2015 9:13:33 AM

Many data lake projects achieve their IT objective: cheap storage of all enterprise data in raw form, but fail in their business objective to deliver value from this data. Why? Because making the data accessible and usable for business users is hard.

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Topics: Smart Data, Data Management, Data Integration, Big Data, Data Governance, Hadoop, Data Lake

Retiring (Your Applications) to the Lake

Posted by Marty Loughlin on Jun 25, 2015 3:27:08 PM

Legacy applications that have exceeded their useful life can be expensive to maintain. They often require specialized skills and old versions of software and hardware to support. But, they can also contain very valuable data that needs to be retained for business or compliance purposes.

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Topics: Smart Data, Semantics, Data Integration, Data Governance, Compliance, Data Lake