Data analytics is the process of collecting and interpreting data to uncover meaningful patterns, trends, and insights. It involves using various techniques and tools to extract valuable information from complex datasets. It can be used to inform decision-making, solve problems, identify opportunities, and improve business processes across various industries. In essence, data analytics helps to derive actionable insights from their data to support informed and data-driven decision-making.
Data analytics is a fundamental tool for businesses in today’s data-rich environment. It empowers organisations to make smarter decisions, improve operations, innovate and stay competitive in an increasingly data-driven world.
The process of data analysis involves gathering all the information, processing it, exploring the data, and using it to find patterns and insights. This process entails the following:
Understand the purpose of the analysis, what type of data needs to be extracted, and what data needs to be analysed.
Data sources include case studies, surveys, interviews, questionnaires, and direct observation.
Not all of the data will be useful, so it’s prudent to clean it up. This process includes removing duplicates and basic errors. Data cleaning is mandatory before sending the information on for analysis.
This part of the process makes use of data analysis software and other tools to help you interpret and understand the data and arrive at conclusions.
At this point, the data collected needs to be interpreted to come up with the best courses of action based on the findings.
Data visualisation requires showing the results graphically and in a way that people can read and understand. This could take the form of charts, graphs, maps, bullet points, or a host of other methods. Visualisation helps to derive valuable insights by helping to compare datasets and observe relationships.
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