What does it take for a successful data analysis?

As we all know, getting the best value of a company’s data is an underlying factor for the organization’s success. Generally, data analysis is defined as the process of inspecting, cleaning, evaluating and transforming data by means of analytical and statistical tools. And clearly, the objective of this process is discovering useful information which can improve business decision making.

In the modern business world, big data technology holds a tremendous potential. Big data analytics are an obligatory means for data governance in every enterprise. Give it a thought – what is the use of all generated and received data, if you don’t interpret it, arrange it and put it into practice for your most important company aims.

One of the facets of a successful data analytics is having the right team in place. But there are clearly defined key steps which should be followed:

• In the first place, as any study requires, data analysis should begin with defining the objectives. If this stage is performed well-enough, then the outcome will surely be positive. After all, much of the decisions which are eventually made, depending on the clarity of the objectives, set in the very beginning.
• Questioning and identifying goals. This stage is often being neglected or just omitted in the data analysis process but it holds a great importance. Posing questions and making sure if the business is willing to make changes, to improve its key metrics and by what means. This is an essential aspect of the analytical process.
• Collect as much data as possible. In order to build better business models, one should rely on various sources.
• Then comes the data cleaning. As raw data is usually collected in different formats, in the first place it should be sorted, cleaned and converted. This prevents from making incorrect conclusions, and eventually decisions.
• Making conclusions and predictions is the crucial stage which actually depends on all abovementioned key steps. Therefore, after a sufficient analysis of the collected data, it is possible to draw right conclusions and make accurate predictions.

What makes a data analysis successful?

Data analysis, as a complex process, depends on various factors. Some of them we already mentioned, highlighting the key steps in the analytical process. On one hand, it is the team itself. It is worth mentioning that according to data specialists, engaging an outside specialist may be really beneficial for the analysis’s success. Sometimes a fresh look from an outsider reveals new ways of optimizing and making use of the data.

Another aspect, contributing to the successful data analysis is creating an easily navigated solution throughout the process. This ensures making accurate reports and right decision making in the end.

Collaboration is another necessary component. The enterprise should work together with the chosen data analytics provider. This is the basis one can lay for their data solutions in future.

Last but not least, here comes creativity. You might think that it is impossible that data analysis and creativity appear in one sentence. The truth is that some processes can be automated indeed, but the analytical thought behind it requires a real mind. This has much to do with the quality of the team and their approach in creating an optimized solution for using the huge amount of information.

Let’s end with the result from an interesting survey which reveals that most organizations are analyzing about 12 % of their data. This means that they are obviously missing out on essential insights. On one hand, this negligence – yes, we can call it so – may expose the company on specific risks or create major problems. On the other hand, this data surely hold the potential for improved business planning and decision making, therefore – for a successful enterprise.