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SmartData Collective > Big Data > Data Mining > More Data, More Problems? Not for Thomson Reuters
Data MiningData Warehousing

More Data, More Problems? Not for Thomson Reuters

GCerami
GCerami
4 Min Read
More Data, More Problems? Not for Thomson Reuters
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
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As companies big and small struggle with the amount of Big Data that floods the web each year, they are continuously challenged to manage their data and make beneficial use of it. Thomson Reuters, the world’s leading source of intelligent information for businesses and professionals, was among one of those companies that was trying to find the perfect solution to bring the best of the Web to their users.

Thomson Reuters found that in order to help monitor, collect and process data from Web sources, they needed an innovative approach in place.  Manually processing their data was time consuming, error prone and quite cumbersome; it also had to be validated for accuracy and completeness.  Another process that proved ineffective for the company was the use of computer scripts and data collection programming tools. Information had to be modified whenever any changes were made to the source site while also requiring costly programmers to devote large amounts of time to create and maintain them.

To transform the data into valuable information, Thomson Reuters developed its Rapid Source Automation (RSA) program to help automate the process of collecting information quickly and accurately. The RSA program is well‐received as an easy‐to‐use solution with a high success rate in which internal clients can often realize the benefits of data automation in 30 minutes.   This team of 3 people provides benefits such as:

•    Sharing of data for reuse across the organization
•    Improved completeness, quality and timeliness of data
•    Consolidating and streamlining process across data silos and the organization
•    A “center-of-excellence” approach providing expert leadership across Thomson Reuters

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By repurposing a significant number of employees from manual data collection and analysis functions to more value-add efforts, the organization noticed an increase in operational efficiency and cost savings.

Data aggregation is a tedious process that negates the human element of gaining business insights from online data. The new RSA program covered 80% of the monitoring and harvesting from web sites, improving business simplification, growth and agility for Thomson Reuters. The key to their success was to streamline its data monitoring and collection processes so that they could increase productivity and improve the quality of the data that they brought in. By leveraging a hybrid aggregation process that played to both parties’ strengths, Thomson Reuters was able to turn its data problem into a competitive advantage.

TAGGED:big datadata aggregation
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