Data analysis is the process of transforming raw information into insights to guide your business decision-making and operations. It begins with identifying the issue you want to solve, collecting the relevant information, and analysing it using a variety of methods of analysis to discover the underlying patterns or relationships. Often, the result is increased profitability or efficiency.
To begin the process, identify a goal. This goal could be as simple or complex like predicting churn among customers. You must then decide which type of data analysis will use to accomplish your goal. Diagnostic data analysis aims to identify known relationships between data points in order to explain the observations. Predictive modeling, on the other hand makes use of past data to predict the outcome.
The next step involves obtaining data. This may require collecting it from sources such as CRM software, internal reports, and archives. Importing external data could also be required, which involves working with data in multiple formats from various sources. Once you have your data you can begin prepping it for analysis by cleaning, organizing and transforming as required.
After the data has been analysed after which you write a written report to summarize the findings in a manner that is easy to understand for your readers. Depending on the level of experience of your readers, this could be a task for the layman or working with a statistician expert to translate technical terms and processes into readable information.
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