The world of traditional business analysis is well-known. Interesting challenges and state of the art methodologies guide the work of a business analyst (BA) – from the discovery and gathering of requirements through to the design of the business requirements and to the characterisation of a system or technology that supports the business. However, the appearance of new and disruptive technologies seem to be changing the way in which a design is conceived, a project is managed and a product is developed and maintained.
This post will focus on the appearance of Big Data and Predictive Analytics as technological trends that can be capitalised on when approaching projects.
The solution model relating to Big Data technologies needs to consider an approach more similar to an agile methodology, rather than the traditional method, therefore a shift in the mentality of a BA maybe necessary. And, here’s why: Big Data projects are based on the idea of posing a question, solving it and then moving on to the next question. Questions are only one portion of the larger problem and a solution will only lead to the next phase of that problem. It seems, then, that we are talking about an evolutionary and incremental approach, more so than a big bang “I’ll tell you at the end” tactic.
Consequently, the approach of the business analysis stage must be the same. It would be extremely juxtaposed to have a 2 or 3 months analysis phase if the development of the solution takes only 1 week and leads to the next phase of the spiral evolution. Instead, the business analysis for Big Data projects should consider quick interactions with the stakeholders, quick prototype of a potential solution (how the data looks like) and a rapid delivery to the development team. This needs to be done in such a way that the Business Analysis team can start working immediately on the next question, which is normally driven by the behaviour of the data – rather similar to what the Agile manifesto states.
So, stop thinking in big and extensive business analysis phases and start thinking on the next question to be solved. Think about what you can get rid of from the existing methodology because if you don’t, the business owner will hire someone else.
In summary, the future of Business Analysis in the Big Data world will be closely related to raising and developing the right questions: What do we want to achieve and where is the data? Building models using the available data, developing graphic models to show what is being found and quickly moving to the next question to be answered: What if we include data from another repository? Can we cross this information with our supplier’s data?