In this post, we look at some of the business challenges that are manifested as a result of data access and delivery latency and bottlenecks, both in terms of analytical and operational business application scenarios. Some of the operational implications affect day-to-day operations, such as longer durations of key cross-functional business processes, delayed accessibility to “warm” data, and the scalability of business intelligence and analytics.
If “big data” is expected to be a mainstay of the operational infrastructure for a broad range of companies (that is, both large companies as well as small/medium-sized businesses), that implies the need for acquiring and integrating those massive data sets that give big data its name (duh!).
Yet in previous blog posts we have already established the existence of a bottleneck in delivering data into big data platforms, and this problem is significantly exacerbated by the (somewhat ingenuous) expectation that massive data sets can be easily provisioned over the Internet. In some cases, the information delivery delays are so oppressive that express mailing hard drives loaded with data sets is preferable to access over the Web!
But before we start to engineer a solution, it is valuable to consider some of the business challenges that are manifested as a result of data access and delivery latency and bottlenecks, both in terms of analytical and operational business application scenarios. Some of the operational implications affect day-to-day operations, such as:
The above two examples are specific cases of a more general operational failure of IT to meet agreed-to service levels across the organization as a result of inadvertent narrowing of the channels for data movement. Next time, we look at some of the analytical implications associated with the information delivery bottleneck.