Data analysis is the process of turning raw information into insights to aid your business decisions and operations. It begins by identifying the issue you are trying to resolve, obtaining all the relevant data and then analyzing it using a variety of statistical techniques to identify patterns or connections. The result is often an increase in profitability or efficiency.

First, you must establish the objective. This goal could be as simple as like predicting churn among customers. Then, you must decide on the type of data analysis will lead you to your goal. Diagnostic data analysis searches for established relationships between data points to explain observations, while predictive modeling relies on past data to predict the future.

The next step is obtaining the data, which may include gathering it from internal sources such as CRM software, internal reports and archives. It could also require importing external data, which requires working with data from multiple sources in a variety of formats. Once you have the data, you can begin to prepare it for analysis by organizing and cleaning it, changing it if necessary, and analyzing it using diverse statistical techniques.

After the data has been analysed and analyzed, you must write a report to present the findings in a format that is easy to comprehend by your readers. This could require you to write in a way that is accessible to lay people, or collaborate with a statistician in order to translate technical terms and procedures into usable text.