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5 Key Components of a Solid Big Data Strategy – BigDataHerd 5 Key Components of a Solid Big Data Strategy | BigDataHerd



5 Key Components of a Solid Big Data Strategy

For most organizations, the answers to many questions lie in Big Data – the massive volumes of structured and unstructured data generated both inside and outside the organization. Being able to analyze all of this data in a meaningful way can be a daunting task if the proper infrastructure is not in place, and if you don’t have the means to process data from multiple sources quickly and effectively. And once you have processed it, it’s a whole other battle to make it meaningful to the people in your organization who need to understand it. To help organizations build the right Big Data strategy, here are five key components they should consider:


  1. Establish a common data model. Ensure that all of your data is centralized in a common data model to provide a single accurate view of the business. The common data model establishes conventions such as fields, naming, attributes and relationships so that everything is aligned across transactional and other systems.
  2. Harness the power of external data. Truly capturing meaning from Big Data means effectively integrating foundational data from internal data sources with external data from third-party environments (i.e. vendor data, social media, and demographics). The platform must be able to harness information in multiple ways, from structured databases and distributed predictive analytic systems, to mining unstructured data.
  3. Focus on scalability and open standards. By using an open-standards platform, organizations can leverage existing systems while reducing IT costs and gaining flexibility in terms of serving the business. Systems adhering to open industry standards are readily available and are preferred to proprietary systems for a number of reasons, not the least of which is their ability to integrate with existing legacy systems, systems from multiple other vendors and future add-on solutions.
  4. Model once consume anywhere. Today, information can be accessed on almost every mobile device, and from cloud-based netbooks to in-store portals. Organizations need to ensure a common infrastructure for producing and delivering enterprise reports, scorecards, dashboards, and ad-hoc analysis while empowering end-users with real-time, 24 * 7 access to self-service BI, mobile BI, and the ability to create their own BI content and personalized dashboards using a simple, easy point-and-click interface.
  5. Provide users with actionable insights.  Users need to be able to act on information without leaving the application and opening another.  This type of closed-loop, cross-domain analytics ensures that Big Data will have an immediate informative and beneficial impact on day-to-day operations.

Establishing the foundation for leveraging Big Data is worth the effort.  When business users can take action right from the retail analytics dashboard, the impact on operations and customer experience is immediate.


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