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Big data

Big data – the 5 Cs

Our approach to big data is aligned with our Data Delta method to generating value from all corporate data.

Whether it’s capturing and interpreting billions of data points from car engine sensors for a global manufacturer, making sense of the millions of track sections mastered and managed by a national rail operator or helping a government develop their information management strategy, Entity has helped our clients drive meaningful business insights and value from their Big Data assets, while continuing to drive value from existing systems.

We deliver a data reservoir by focusing on the five big data C’s:

  • Completeness: all the relevant data needed by the business
  • Cleanliness: data quality matters, regardless of size (signal to noise ratio declines as data volumes increase)
  • Context: data must be relevant to expected/desired outcomes of the business
  • Control: governance is critical, more so with scale
  • Curation: a complete lifecycle management for data is essential

 

It's not about the bucket

We like to use the analogy of car washing when talking about big data technology choices. This is the idea that the bucket that holds the water is the least important consideration when washing a car. The quality of the water, brush and detergent as well as the skills and attitude of the person doing the washing are much more important.

The Internet of Things and social media are clearly going to continue to develop and interact. Therefore the future for most organisations will rest with the effective management of big data. Effective management does include the technical “bucket” side, but it relies on so much more. It relies on crossing the Data Delta – this is the gap between the data you have and the information you need. For more information you can download our book for free here.

Big data technologies vs the traditional data warehouse

Many organisations keep their existing data warehouse and augment it with a separate big data architecture and stack. We believe that the monolithic data warehouse that acts as the place where all data is physically integrated will probably not be the dominant model for the future. The increases in data volume, velocity and variety make this increasingly unlikely.

We expect to see more Logical Data Warehouses (LDWs), in which there are multiple data sources, types and structures integrated in a federated way. However, most analytic use cases will still need the traditional Data Warehouse platform. The LDW will lean heavily on master and reference data management to act as the indices of a virtualised data store.

Big data and digital disruption

Big data and digital technology will change the core value within businesses:

  • Book sellers no longer need a warehouse of books
  • Movie sellers no longer need a cinema
  • Airlines and hotels do not need travel agents to sell their services
  • Taxi companies do not need to own cars

We should assume that the level of disruption will increase. There will be scope increases in areas such as health and education. Furthermore as we have access to more and more data, new trends and new opportunities will certainly emerge.

How can Entity Group help?

We think about big data and related technologies in the context of data management more broadly. We are experts in all aspects of data management and we invite you to discuss your big data challenges with us so we can provide you with ideas and practical steps towards achieving your business goals.

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