Taking analytics to the cloud

This is a Guest Post by Georges Bory, Co-founder and MD at Quartet FS.

With the Big Data challenge only set to intensify, businesses across the board are increasingly looking to data analytics tools to make sense of the valuable insights this mine of information can provide. Content sharing website Pinterest recently launched a data analytics tool which shows business users precisely how many visitors the service is referring to their own websites. This ability to monetise the information currently available in the digital universe is hugely attractive to organisations seeking to make the most of limited technology investment at a time when budgets are tight. 

A desire to economise on IT has been especially prevalent in the financial services industry, much of which is relying on legacy technology having reduced or completely frozen tech investment in the wake of the financial crisis. February saw Deutsche Bank admit that legacy technology is holding it back in the quest to make the most of the data available, largely due to the difficulties associated with marrying their existing systems with innovative and more productive tools.

With regulatory developments currently high on the boardroom agenda, there is an increasing priority placed on risk management at Board-level. With the likes of Basel III, the Vickers reforms, IT glitches, and rogue trading scandals continuing to dominate headlines, firms are keen to ensure they are doing all in their power to minimise risk. Many regulatory challenges require better data aggregation methods to analyse information on the fly – something which can be achieved through the use of in-memory analytics. In-memory analytics is a method of operational intelligence used to decipher complex and time-intensive scenarios, for example risk calculations, in real-time, using the most accurate and up-to-date data possible.

Firms need to ensure they are prepared with the most efficient ways to take advantage of this technology. This is particularly relevant given the new breed of cloud solutions now coming to market to bridge the gap between existing banking systems and modern data analysis. Private clouds allow data to be hosted and managed in grids, due to the large influxes of information being analysed at any one time. This makes them suitable for firms that need to crunch data stretching across a variety of business areas. Data aggregation is a natural candidate for cloud platforms, since the scalability options are relatively economical. In addition, they provide unlimited infrastructure to accommodate intensive computation as businesses expand. 

Cloud provides the perfect platform for super fast in-memory analytics solutions and should be a top priority for firms seeking to meet workload and cost demands. Cloud ultimately makes the integration of real-time risk technologies less expensive, more scalable, and simpler for the firm, and can consequently revolutionise what has become a notoriously tricky integration process.

Industries outside of the financial services arena are also seeing the benefits of in-memory technology. Complex processes and fast-moving data exist in many areas, such as supply chain management and e-commerce. Actionable intelligence delivered from multiple data sources on the fly is now required for a variety of business cases. This includes the consolidation of dense and siloed facets of the supply chain, or the generation of pricing intelligence on competitor products in order to ensure retailers’ pricing structures entice consumers to buy.

As Pinterest’s new analytics tool shows, many types of organisations, ranging from social media companies to major banks, can benefit from intelligent analytics. However, the regulatory and operational challenges in-memory analytics technology can solve are certainly hastening the need for banks to take advantage of the benefits of a cloud solution. Of particular use is that it is flexible enough to adapt for a number of use cases and business scenarios. This perfectly places the financial services industry to pave the way as an early adopter of data analytics in the cloud.

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