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Bloomberg’s VDR Offers Data Fitting Room to Tackle Information Overload

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Data overload is a phrase that’s being more commonly heard as the volume of digital information available to financial institutions swells. More than that, finding the data that best suits their specific needs has become an arduous task, especially given that it can take the best part of a financial quarter to onboard new data feeds.

Bloomberg says it has found a way around this increasingly difficult task with its Virtual Data Room (VDR), a kind of fitting room for companies that want try different datasets for size before deciding whether to buy. In the VDR, customers can test datasets for a limited time to see if they are suited to the jobs that need doing. If they do, then the firms will buy. If not, companies will simply hand the items back to the cashier at the desk.

The rationale behind the new concept is not only to showcase Bloomberg’s huge pool of bulk datasets but also to make it easier, quicker and less risky for customers to find data.

“Trialling data gives firms the confidence that they are making the right decision,” Bloomberg global head of data license Brian Doherty told Data Management Insight. “Traditional methods require firms to implement the data pipelines to onboard the data in their own environment; this can be very time consuming as most data requires a substantial amount of pre-processing to be ready to evaluate.

“Bloomberg’s VDR streamlines this time-consuming process by providing an environment where users can immediately test and validate Bloomberg’s data quality, linking abilities and usefulness for firms’ specific workflows.”

Try For Size

The growth in data generation and usage is staggering and posing new headaches for financial firms that are increasingly reliant on information to power their operations and inform decision making. By next year, data managers will be having to cope with a 175-zettabytes datasphere, according to figures from IDC, with an annual growth rate of 61%.

To help them, Bloomberg said its VDR offers a secure, hosted python environment that enables firms to interact with the company’s catalogue of data and historical data. There’s no need to install software, download files or onboard files, explained Michael Beal, head of data science. Firms get immediate access to structured data in an environment that they are comfortable working in, he added.

“Clients’ need for high quality data to drive their investment decisions continues to grow – the challenge for them is how do they find the right content when there are so many sources and providers,” Beal toldData Management Insight. “Clients want to quickly discover, validate, and test data so that they can make well informed decisions, rapidly.”

Customers can interact with the data by pre-loading into Jupyter notebooks. From there, customers can test key determinants of data selection, including loading, coverage, integration and customisation.

More Sales

Bloomberg expects, also, that by opening its vast troves of data to inspections and assessment, more customers will decide to buy.

“This new tool will likely increase the adoption of Bloomberg data because it gives clients an intuitive environment to explore Bloomberg’s rich array of bulk datasets spanning company data, sustainability data, pricing, reference data, and more,” said Beal.

He said that the VDR neatly chimes with modern data trends. Despite the proliferation of new data vendors – especially in novel and growing categories such as ESG, alternative investments and regulatory reporting – digitalisation models are becoming more focused as the financial sector’s technological transformation matures.

“Data has evolved; in the early stages of the cycle, firms tended to focus more on quantity over quality – for example, ‘big data’,” Beal said. “Now the industry is very focused on the quality of the data powering their models. In the case of Bloomberg’s VDR, it lets clients tangibly test out and ascertain how Bloomberg’s bulk datasets offer differentiated quality.”

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