Business Analytics and Big Data are the next big things judging by the IT industry’s marketing efforts. It appears that no-one wants to be left out, and some vendors surprise by appearing to have a legacy in analytics. In reality there are some vendors whose core activity is principally in analytics and some that operate adjacent to customers’ analytics efforts. In this piece we look at the different practice areas of analytics.

Data warehousing
A data warehouse became the repository for doing business analytics. The practices around data warehousing became established during the 80s and 90s with vendors who developed the IP and the appliances that run data warehouse applications. It was natural to do the analysis off the mission critical IT platforms not to jeopardise their performance. The net result was a niche segment in the IT market which was optimised for the specific task. For customers of a certain size, it became an established effort to mine their in-house data; typically sales focused on customers and prospects, but there were other uses such as fraud analysis. Various tasks evolved dealing with extraction, transformation, load etc. Eventually data warehousing saturated the obvious information repositories in the enterprise, and best practices evolved which others could learn from. The net result of this proliferation was that incremental yields followed the rules of diminishing returns.
Yet, a latent appetite had been created to find more meaning in more sources of data. Practical new ways of delivering business information analysis still belong under the label of business analytics, but Big Data has become associated with the new initiatives post data warehousing.

Big Data and business analytics
We wrote about the poorly named label, a critique which still stands, but what is no less valid is that Big Data has the potential to deliver many benefits to customers. The core attributes of contemporary business analytics are:

  • Spanning many and incongruous information types
  • Alternative repositories to databases
  • Establishing trend data from new media
  • Distributed compute & repositories
  • Commodity IT resources
  • Open source

If there is a justification for the word ‘big’ in Big Data, then it lies in scope and scale. And modern business analytics is benefiting from the work which some of the search engines and e-retailers undertook to serving up fast results and aid decision making by automating their processes.
The business analytics market depends less on purpose built appliances than data warehousing, but customers will have to choose their data repositories. Similarly they will have to make choices in their analytics applications which may well involve old players who made their names in data warehousing. The ability to tie in remote and distributed sources of information adds new layers of complexity. Hadoop is worth mentioning because it is the open source framework which is the basis for other open source as well as commercial vendor offerings.
The world of business analytics is as a result highly dynamic at the moment. The fundamental assumption is that anything that can be expressed as a computable resource is a candidate for business analytics. How to get from data to decision is not straightforward and skilled specialists are needed to deliver solutions for customers. It also means that a wide set of service offerings are evolving.

A market is forming
Even if some vendors conveniently manoeuvre under the analytics umbrella, then adjacent issues such as performance, data protection and cost efficiency apply to analytics just like any workloads. However, it is clearly the new players enabling new smart ways of driving out new value which are especially worth exploring. Acquisitions by the larger players have already taken place and more will undoubtedly follow.
Customers will have to invest time in exploring if Big Data is relevant for them. The new practices, the open source framework, and the various offerings will take time to digest let alone deciding what investments needs to be made. More importantly the whole organisation needs to be involved in assessing if it wants to engage in modern business analytics as it is not an IT-only exercise.

Picture credit: Facets by Rexton

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