Data analysis is the process of transforming raw data into meaningful insights which aids in decision-making. It is utilized in different industries to improve their processes as well as to detect issues and make better decisions based on data. Data analytics is a powerful tool that can aid businesses in gaining a competitive edge, increase customer satisfaction, and increase sales.

To successfully implement data analysis, it’s essential to set clear business objectives for what you’d like to accomplish and then create an investigation plan for data that will help identify the kinds of information that you require. These goals must be targeted, measurable and achievable. (specific that is measurable, feasible and time-bound) to ensure that they are aligned with your overall company objectives.

Descriptive data analyses answer the question “what has happened?” by summarizing previous performance and providing insights into your benchmarks. This is the most common kind of data analysis and can be found in many KPI dashboards and sales reports. Diagnostic data analysis gleans these insights and identifies why certain results happened, giving you more details on how things are working.

Predictive data analytics seeks to anticipate future events using the existing data to determine the likelihood of certain outcomes occurring. This kind of data analytics is used to forecast the behavior of your audience and create more effective marketing campaigns.

Data analysis requires a set of high-quality skills, including critical thinking, problem solving and communication. It also requires access to the most effective tools for data analysis to transform your data into useful intelligence. These tools must offer many features including enhanced analytics that improves human intuition by providing suggestions for insights and analyses, data exploration and visualization, automation, search & natural language interaction, as well as advanced analytics calculation.