Data analysis is a set of steps that gather raw information and transform it into insights that help guide your business operations and decision-making. It begins with identifying the problem you’re trying to solve, then gathering all the relevant data and then analyzing it using a variety of methods of analysis to discover patterns or relationships. The result is usually an increase in profit or efficiency.

It is essential to first establish the goal. This goal could be as simple or complicated such as predicting churn of customers. It is then up to you to decide what kind of data analysis you will use to achieve your goal. Diagnostic data analysis seeks to discover known connections between data points in order to explain observations. Predictive modeling is the opposite. It makes use of past data to predict the outcome.

The next step involves obtaining data. This may involve collecting data from sources like CRM software, internal reports, and archives. Importing data from outside sources could be required, and involves working with data in multiple formats from various sources. Once you have the data, you can begin preparing it for analysis by cleaning and organizing it, changing it as needed, and analyzing it using different statistical techniques.

After the data has been examined and analyzed, you need to create a summary of the findings and presents the results in a way that is easy for your readers. Based on the level of expertise of your readers, this may require writing for non-experts or working with a statistical expert to translate technical concepts and processes into easily understood information.

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