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Data analysis is the process of transforming raw data into meaningful insights that helps guide decision-making. It is used in different industries to improve the efficiency of operations as well as identify opportunities and issues, and make more informed decisions. Data analytics can be a valuable tool for businesses to gain competitive edge, improve the engagement of customers and boost sales.

For a successful implementation of data analysis, you should define clearly what you would like to achieve and create a data investigation strategy that can help you determine the kind of information you require. These objectives should be SMART (specific, measurable and achievable as well as time-bound and relevant) to ensure that they align with the overall goals of the company.

Descriptive data analysis addresses the question “what occurred” by analyzing performance over time and providing information using your benchmarks. This is the most common type of data analysis and is seen in many KPI dashboards and sales reports. Diagnostic data analysis analyzes these insights and identifies reasons for the specific results giving more information to your understanding of how things function.

Predictive data analysis aims to predict future events using your existing data. This type of data analysis is used to do things like forecasting the behavior of your target audience and generating more effective marketing campaigns.

Data analysis requires a set of strong skills, such as critical thinking, problem-solving and communication. It is also important to have the best data analytics tools to turn raw information into actionable intelligence. These tools should have a range of options like enhanced analytics, which boosts human intuition by providing insights and analyses such as data visualization and exploration, automation of natural language interactions and advanced analytics calculations.