Big Data Management: 5 Top Priorities

Big Data Management
HealthManagement.org reports on the developments and potential with Big Data regularly. Whether it is the application of Big Data across the clinical fields of healthcare or how to utilise it for best management, it is a subject that is core to our coverage. This week, we take a look at Top Priorities for Big Data management.

Big Data and Business Value

1. Capture, store, process, and deliver big data in order to repurpose it for customer intelligence, efficient operations and business monitoring.
With Big Data, the quickest route to securing business value is to work with analytics while the process of joining new and old data provides overviews on customers and tapping into streamed data gives valuable insight into time-sensitive business processes.

2.  Training and New Staff
Hiring and training data experts such as analysts, architects and scientists is essential in order to put Big Data at the centre of efficient practice. Such professionals can develop discovery analytics, applications for data exploration and real-time monitoring in order to optimise value from data.

3. Value Collaboration
Big Data is vast needing a diverse range of specialist technology teams to manage it effectively within an enterprise. Coordination is key for success. The broader access to Big Data the better so that all involved know what their roles are and can get their needs met.

 4. Beware of silos
Big Data management may start in a silo but needs to be integrated with other enterprise data management systems as an immediate priority. A decision needs to be made on whether or not Big Data platforms are owned departmentally or are part of a shared enterprise infrastructure.

5. Develop a strategy for Big Data management
Decide on Big Data standards and road maps that best suit your organisation’s needs and culture. What are the most appropriate platforms and interfaces for capturing, storing, and processing each type of data – structured, semi-structured and unstructured?
Design a workflow for the management of Big Data in its original state but also one that can convert it into other forms for analytics.

Source: TDWI Research

Published on : Wed, 15 Jul 2015


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