Defining, articulating and representing business problems is a crucial initial step in any Big Data initiative. To deliver quick results from big data, it is good to have powerful and well organized analytic capability. And, if not? Nothing to worry. Reach out to a right big data partner who can deliver quick results – this could be a Proof Of Concept (POC). Once recognize the POC is successful and could generate business value – yes, go ahead to the next level.
Always, it is good to have internal analytic team who can work on data to solve problems and help finding innovative ways to serve customer better. Analytics team must have enough and good amount of data and an effective communication to deliver results. They also need appropriate tools according to the size and nature of data to perform operation. Analytic team has to look at big data life cycle – from data preparation to final report/model delivery or including model monitoring, if modelling is a part of final outcome. Each and every stage of the big data journey effects the final result and business impact and hence, it is important to have involvement of data expert – we may call him data scientist.
Companies are investing resources on technologies, operations, training and development of skills. But during the analysing of big data the most important factor is understanding of data and connecting with the business background and leverage them for decision support. If the analyst doesn’t have the understanding of these things then the corporate information doesn’t help them to find out the appropriate solution. For delivering quick results, analyst should pay enough time to understand the data and the business problem and more over the business itself. Analyst should have the understanding of customer issues and according to the issues they have to decide, what can be done about it and what tools to leverage.
Let us review factors that drive success when companies try to deliver quick results with big data. To deliver quick results with big data, we will need to consider some of the these points..
Business Understanding – “If I were given one hour to save the planet, I would spend 59 minutes defining the problem and one minute resolving it,” Albert Einstein said. Before making an attempt to solve any problem, we should step back and invest time and effort to improve the understanding of the question that what we are trying to solve. For delivering quick results, we need to have good understanding of the business.
Strong Strategy – Drive to Solution: To run any successful operation a strategy is essential. There should be a strong strategy having a vision that what needs to be done before starting to analyse the data. The whole big data approach should have a strong and clear vision and drive to final output.
Data understanding – Data is the main and the most important factor during the analysis. Whole analysis is around the data. Analyst should have knowledge to use and structure data according to their needs. Data should be organised and well structured, so that it will be easy to work on that. Data should be clustered according to their logical type. So an analyst will target the focus area for the data operations. The area will be identified according to their impact on business.
Smart analytics team: Not size of the team – but, quality of the team. While recruiting the analyst or statisticians, recruiter needs to look for high problem solving capabilities, and reasoning power of candidates. Candidates should have the skills that – how and why to approach a problem. Engineering background candidates may be a good analyst.
Expertise on Big data tools and technologies– To deliver quick results, big data team should have expertise in big data tools and technology. It will help the big data team to get in the core of data.
In a recent survey of “The Economist Intelligence Unit” which has been done after completion of a big data project, one-half of analyst said that they didn’t had enough structured data to support decision-making, compared with only 28% who said the same about unstructured data. In fact, 40% of respondents complain that they had too much unstructured data
Ability to leverage right tool – Once you have the skilled analyst and right data with a strong strategy, you need to look for the correct technology on which the data would be analysed. Technology acts as a bridge between the skilled analyst and the right data. So right technology is needed to operate those data by the analyst. There are different technology which can be leveraged for this purpose according to the requirement.
Governance – It is very necessary to connect all the resources and technologies as a single unit to deliver quick results. Governing the whole process in well-mannered way plays an important role in delivering quick results. Governance body need to evaluate the team and assign the works according to their potential and skills.
To deliver quick results, start with a POC and ensure that result is out and useful. In order to start the POC, it is necessary to have deep business understanding, right mix of skilled people, ability to choose right tools and techniques with a powerful strategy that makes the result faster and accurate.