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Big Data

The big data strategies powering growth

Balloons are inflated at the Bristol International balloon fiesta in south west England August 6, 2015. Photographer: Toby Melville
Photographer: Toby Melville

Big data is often broken down into the five Vs. How can businesses maximize the ‘value’ element and boost growth strategies through open data?

As a leader in collecting and dispensing massive amounts of information and data, Thomson Reuters is ideally placed to explain the power of big data and its value in business.

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Watch video — How can you maximize the value of big data?

In partnership with banking group Barclays, Dan Bennett, Head of Enterprise Data Services, recently spoke to members of the start-up community at Barclays Eagle Labs in Cambridge, UK.

His address aimed to encourage innovation and show audience members how they can utilize Thomson Reuters big data strategies to bolster their own business growth.

Dan Bennett quote

The talk started by breaking down “big data” into its five different types, or the “Five Vs” as they are commonly known: volume, variety, veracity, velocity and value.

While the first four are objective, Bennett explained that “value depends on what you want to do with [the data] and if you are comfortable with sharing what you have”.

Use Intelligent Tagging to turn large amounts of unstructured data into precise advantage

The business of big data

The talk then offered some insight on the Thomson Reuters enterprise content platform, which is used by our business units to build product and share content.

Bennett said: “It has a standard programing model and we provide standard tooling for our developers, which explain how to check-in a program, how to build the program, how it gets deployed onto the cluster — all the operational management around the outside.”

Intelligent Tagging from Thomson Reuters
Intelligent Tagging from Thomson Reuters

Use Intelligent Tagging to turn large amounts of unstructured data into precise advantage

Within the enterprise content platform, there’s a Hadoop cluster, Graph store, which is open source, Kafka, which is a queuing mechanism, and another open source package called CDAP, which is a programing model with monitoring and maintenance.

Creating this platform has allowed Thomson Reuters to simplify IT processes, make content sharing easier, and shorten the time it takes products to go to market.

Big data solutions

Bennett finished his talk by explaining some of the solutions from Thomson Reuters around big data.

PermID from Thomson Reuters

One of these resources is PermID, the open, permanent and universal identifiers where underlying attributes capture the context of the identity they each represent.

PermID from Thomson Reuters
PermID from Thomson Reuters

Use the Record Matching service to match your own entity data to Thomson Reuters’ identifiers

In response to customer demand, we decided to make available our Permanent Identifiers, or PermIDs, and the associated entity masters and metadata to the market.

Discover CM Well – a data warehouse for your knowledge graph

Another platform is CM-Well (Content Matrix Well), an open source, writable Linked Data repository.

PermID from Thomson Reuters
PermID from Thomson Reuters

Find out more about PermID from Thomson Reuters

Bennett explained: “We’re storing over 100 billion relationships in this program. We use it as a warehouse — a lot of our mining of relationships, tags and information about content becomes part of our Knowledge Graph that goes into this system.

“Then we have feeds out of this to what you might term a ‘data mart’, serving different product needs.”

Thomson Reuters Knowledge Graph contains information about organizations, instruments and people in the world of finance, but you can use CM-Well for any kind of linked data.

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