DATA – FROM VOLUME TO VALUE

By Shahbaz Ali, President and CEO, Tarmin

Traditionally, big data and data storage was a conversation only happening in the IT and technology space. However as of late, the conversation has more specifically been taking place in the banking and financial services sectors, which, according to a recent study commissioned by New Vantage Partners LLC, is further along than most other industries in making use of predictive analytics.

Predictive analytics and the management of Big Data go hand in hand. Historically, and certainly for banks and Financial Services Organizations (FSOs), data storage has been purchased on an initial cost basis (CAPEX) with little attention being paid to the annual costs of items such as support and maintenance, IT staffing, power and the hardware and software needed to accommodate growth.

The Unstructured Data Explosion: Opportunity or Challenge?

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Shahbaz Ali
Shahbaz Ali

Unstructured data is growing exponentially, to the innovators this signifies increased opportunity for better business insights. However, mass volumes of data, although provide noteworthy potential, can also pose as a substantial challenge if the appropriate underlying infrastructure is not in place to enable organizations to store, protect and understand data, unlocking the value of information as a strategic business enabler.

Banks and FSOs are turning to big data, using insights taken from daily transactions, market feeds, customer service records, location data, and click streams to carve out new business models and services to transform the go to market strategy. Between 60 to 80 percent of all data in the financial services industry is unstructured, causing major cost and compliance challenges that make it difficult to gain value from their data.

These challenges can be solved by implementing an infrastructure based on Data Defined Storage, a data centric management, which marries application, information, and storage tiers into a single, integrated, highly scalable, management architecture. This empowers organizations to look at their data as an asset verses an ongoing cost center.

Innovate with Data Defined Storage

Data Defined Storage is a new approach to managing, protecting, and realizing value from data in this integrated data centric management architecture. Data Defined Storage allows users, applications and devices to gain access to a repository of captured metadata and data that empowers organizations to access, query and manipulate the critical components of the data, transforming it into information, while providing a flexible and scalable platform for storage of the underlying data.

There are many benefits of Data Defined Storage, mainly when it comes to compliance, information governance automation and unification of the data. By improving and automating information governance processes such as the indexing of data, data classifications, tagging and improved corporate compliance, FSOs increase their effectiveness. This is realized through streamlining business processes to improve search capabilities, conducting early case assessments and other enterprise data centric activities. The availability of regulatory compliance reporting allows organizations to stay one-step ahead of regulatory requirements and ensure transparent communication with teams, offices and relevant stakeholders.

For example, as financial data flows into organizations, users can automatically separate the different log data that is generated by the trading platforms as flat text files, and dynamically assess content and type. Then, based on its business value, they can automatically separate and tag data types such as trade log data, relevant market data necessary for best execution retention, relevant market ticker data, and generic ticker data from irrelevant markets. Each of these different data types has different business value and can be deployed for various purposes, ranging from tracking and processing trading activities and satisfying regulatory demands to driving predictive analytics for future trading. The data can be either saved for long-term retention on tape, or destroyed if it is useless, e.g., generic ticker data from irrelevant markets.

Additionally, FSOs often overlook the ability to monetize unstructured data within the business. This data contains the sum total of all knowledge within the enterprise which holds value to third parties as well as improving processes internally. By implementing Data Defined Storage, FSOs are able to mine the net worth of their data and manage through data-in-place dashboarding and analytics. This creates potential cost savings and increases competitive advantage.

Business Value of Data

It is crystal clear that delivering mission-critical business value is inextricably linked to advanced data strategies that can address the spectrum of challenges and opportunities that are dictated by unstructured data. According to a survey by the University of Oxford and IBM’s Institute of Business Value, a massive 71 percent of Financial Services companies were found to already be using big data and analytics. As a result FSOs have realized that data is critical in delivering a competitive advantage in an industry that continues to rebuild after a worldwide financial crisis.

In the quest to optimize data as a strategic asset, the goal is to make data management invisible to end-users, to use an analogy, most car drivers are not interested in how the engine functions, but rather are only concerned with what happens when pressure is applied to the gas pedal. With a Data Defined Storage solution, the equivalent of the car is an application that provides—for instance—a unified approach for compliance and search while enabling security—and all at the data level, not the device level.

Data Defined Storage provides three-core business benefits for FSOs today: improved operational efficiency for reduced total cost of ownership by up to 80 percent over time; reduced business risk by addressing data security and information governance challenges; and enhanced business agility and decision making for improved revenue growth.

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