What Does Big Data Have For Financial Institutions In 2016?
May 28, 2016 | Big Data, Technology
Big Data’s focus is going to shift from IT-driven infrastructure projects to business-driven data solutions. This is going to happen due to the adoption of industry standards and more mature platforms. Organizations opting for big data strategies earlier in the day will benefit in the form of operational efficiency and will also experience top-line growth.
2016 is going to witness solutions to most of these challenges and powerful differentiated strategies will emerge from organizations that use their big data assets to advantage. Let us talk about some of the trends predicted by experts for 2016.
The Emergence of Powerful Big Data Use Cases
A challenge that has been quite concerning in the case of big data adoption is the ever-present disconnect between business and IT. There have been numerous instances where IT has led the way, building a big data infrastructure and taking up countless new tools, usually without considering the context of a specific business problem. This eventually graduates into a solution looking for a problem to solve.
Organizations acting smartly take a different approach and build solutions addressing specific business issues or making a data-as-a-service offer. This gives the business a chance to choose the tools they need to tackle their specific problem. This year we can expect to see a higher adoption of these approaches.
Talking about some of the important use cases behind big data adoption we need to mention – compliance, regulatory risk reporting, cyber-security and trade surveillance. The year 2016 will see interest rising in revenue-generating use cases like customer 360.
The Smart Data Lake
It was during the last year that we saw the emergence of Data Lake – a single store for all enterprise data basis these characteristics: The ability to collect huge volumes of data in its native and untransformed format at a very low cost.
Though the data lake promises a lot, it also has its limitations at the same time. Some of the major challenges for organizations are – how to catalogue data sources, harmonizing disparate data and adding meaning to the data.
The democratization of Data Access
There’s another benefit of data lake tools which is providing end-user access. Data lake solutions usually require manual coding in order to transform and prepare data for consumption by Business Intelligence tools. Having a smart data lake allows semantic models, generally used to add meaning to the data, to provide critical end-user capabilities like data cataloguing, data meaning, data provenance and self-service data analytics.
Data expressed by semantic models do not assume the queries and analytics it needs to support. By describing the semantics, it allows the end users to identify the data required by them and to question it in terms of business, without any coding.
Broad Deployment of Big Data Solutions to Mid-Sized Organizations
Till today the complex and immature nature of the big data solutions implementation tools has limited it to the domain of large and technically sophisticated companies. Another notion that’s set in our minds is that “big” is the most important dimension of big data. Variety is an equally important dimension of big data too. Irrespective of the magnitude of the companies, they all have variety in their data.
The Rise of Big Data Governance
EDM Council did a survey recently which showed that the world is at an inflexion point for data governance in the financial service industry. Majority of the companies have realized that they need enterprise data governance and have either set or have started to set their strategies. BCBS 239 is driving these programs but it is still in its early stages and it is not possible to measure the business value of these programs as of today. Having said that we must stress on the inevitable i.e. the year 2016 will create more demand for data governance and we will witness a rise in Big Data initiatives. Processes, controls and securities which are currently applied in data silos will be required to be enforced on the shared enterprise data lake.
Since Big Data has started penetrating into the financial service industry, it will only open more gates to big data opportunities. Skilled professionals will not only be in demand by IT companies now. This trend is also going to affect other industries and will have a snowball effect. Cognixia runs great training programs on Big Data Analytics which makes you understand the anatomy of Big Data and acquaints you with the nitty-gritty of this amazing technology. This is just the beginning, there’s a lot more to come.
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