Big opportunities, big challenges

Big data: changing the way businesses compete and operate

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While there is no doubt that the big data revolution has created substantial benefits to businesses and consumers alike, there are commensurate risks that go along with using big data.

The need to secure sensitive data, to protect private information and to manage data quality, exists whether data sets are big or small. However, the specific properties of big data (volume, variety, velocity, veracity) create new types of risks that necessitate a comprehensive strategy to enable a company to utilize big data while avoiding the pitfalls.

We suggest that organizations need to consider the following questions for the seven key steps to success when assessing their readiness to truly start benefiting from big data:

Governance - Good governance encompasses consistent guidance, procedures and clear management decision-making. Organizations need to ensure standard and exhaustive data capture; they need not protect all the data, but they need to start sharing data with in-built protections with the right levels and functions of the organization.

  • Given the ubiquitous nature of big data, does your data governance framework acknowledge the evolving definitions of data owners and consumers?
  • Does your current governance address the risks related to the life cycle of big data?

Management – Integrating and moving data across the organization is traditionally constrained by data storage platforms such as relational databases or batch files with limited ability to process very large volumes of data, data with complex structure or without structure at all, or data generated or received at very high speeds.

  • Do you have the right skills and internal capabilities to deal with the big data technologies and methods which are relatively new?
  • Do you have sufficient control over the big data volumes, variety, velocity and veracity, which may impose additional risks?

Architecture – Data architecture should be prepared to break down internal silos, enabling the sharing of key data sets across the organization and to ensure that learnings are being captured and relayed across to the right set of people in the organization in a timely and accurate manner.

  • Does your IT infrastructure support your big data strategy?
  • Can you flexibly scale processing and storage to meet the demands of big data processing?

Usage – The results of big data can beneficial to a wide range of stakeholders across the organization — executive management and boards, business operations and risk professionals, including legal, internal audit, finance and compliance; as well as customer-facing departments like sales and marketing. The challenge is having the ability to interpret the huge amount of data that can be collated from various sources.

  • Do you have the right talent to be able to process, model and interpret big data results?
  • Is your workforce ready to shift to the new paradigm of data-driven decisions?

Quality – The quality of data sets and the inference drawn from such data sets are increasingly becoming more critical. Organizations need to build quality and monitoring functions and parameters for big data. Correcting a data error can be much more costly than getting the data right the first time — and getting the data wrong can be catastrophic and much more costly to the organization if not corrected.

  • Are your existing methods sufficient to deal with the unstructured data?
  • What level of data quality is required to meet your big data goal?

Security – Companies need to start establishing security policies which are self-configurable: these policies must leverage existing trust relationships, and promote data and resource sharing within the organizations, while ensuring that data analytics are optimized and not limited because of such policies.

  • Is your security infrastructure robust enough to deal with the increasing demands of protecting a growing stockpile of data, while flexible enough to not become bottlenecked by the innovation?

Privacy – The increased use of big data challenges the traditional frameworks for protecting the privacy of personal information, forcing companies to audit the implementation of their privacy policies to ensure that privacy is being properly maintained.

  • Have you defined who owns big data information, and whether there is actual or implied consent to use the same?
  • Do you understand that how the big data is stored and how it is used can also create significant privacy issues?

If one of these key questions has been answered with “No,” it is time for you to take action. We have helped many global organizations to successfully deploy the right people, processes and technologies around data issues and solutions. Contact us today.

For more details about the benefits and risks associated with these drivers and examples of how big data is being leveraged to solve some of the complex issues businesses face today, download the full report.