There are huge opportunities locked in your Big Data. The challenge is most enterprises lack the tools to aggregate all the structured and unstructured data sources housed on disparate legacy systems. Fortunately, technological advances in data analytics are opening the locks on Big Data and providing businesses with actionable insights for growing and managing their organizations.

Still, there are many challenges to unlocking Big Data potential –

  • the lack of skilled data scientists to examine data, growing infrastructure and upholding maintenance costs,
  • anxiety over data security and privacy,
  • lack of data governance capabilities

How to Manage Risk in Big Data Projects

These difficulties remain when considering analyzing large volumes of data. Managing Big Data projects will vary depending on organizational business expectations and its ability to successfully execute. The risks of managing Big Data projects can be mitigated by planning, defining technical necessities, and creating a Total Business Value Assessment that leads to competitive advantage and drives business outcomes.

Enterprise decision-makers are offered analytics framework for managing risks associated with Big Data projects. This process of identifying risks can determine the organizational level and objectives, identify the problem area relating customer care and business development behind the project and navigate the process for initiating new projects. Organizations identify new ways to process data and conduct systematic analysis to identify and address privacy issues. The organization must cope with PIA decision-making tool in order to identify and mitigate over data risks throughout development cycle over product, system or service. It also helps industries to better understand the personal information being collected, accessed, stored and shared. Risk analytics provides solutions that increase return on capital by making risk-informed decisions, improves decision making, streamlines risk processes to minimize costs and manages operational risk.

The probability of occurrence of various risks factor in Big Data projects can be used and redesigned in order to mitigate risk by adapting operational supply model in chain network. Understanding the organizational perception over Big Data, selecting partners for risk mitigation and communicating the mitigation plans, developing contingency plans based upon analytics can help managing Big Data projects.


Scalable Systems data management services can help you get the most out of all your data-quickly and painlessly. Our data management services include big data, integration, quality, governance and security using data management tools. Our data management services offer full-scale implementation and consulting to help organization work more efficiently to integrate, manage and govern data.


How to Manage Risk in Big Data Projects