Data Analytics (DA) is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. It involves a range of techniques and methodologies used to analyze data from various sources in different formats, including structured and unstructured data.
Data Analytics is used across many industries to allow companies and organizations to make better decisions as well as verify and disprove existing theories or models. The focus of Data Analytics lies in inference, the process of deriving conclusions that are solely based on what the researcher already knows. Its applications are diverse, ranging from healthcare to retail, and it's a powerful tool when it comes to making strategies and business decisions.
The main purpose of Data Analytics is to help organizations make informed decisions by analyzing large amounts of data to uncover hidden patterns, correlations and other insights.
Data Analytics is used by businesses, researchers, scientists, governments, and others to make informed decisions, predict trends, and understand complex systems.
There are numerous software tools available for data analytics, including Excel, RapidMiner, KNIME, Tableau, and Google Analytics.
Data Analytics can provide a wealth of benefits to businesses such as identifying trends and patterns, improving business efficiencies, driving business innovation, and maintaining competitive edge.
In conclusion, Data Analytics is a vital tool in the modern business world, providing a wealth of benefits that can help businesses to maximize their potential and stay ahead of the competition.