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Data Analytics

Data analytics is the systematic and pervasive use of automated processes, mathematical and statistical tools, data analysis, and advanced computer technology such as AI and machine learning to provide information and insight. It is used by organizations to help them make decisions based on relevant data of various types, including structured and unstructured, numerical and categorical, actual and theoretical. Data analytics is often applied in business and is a major component of business intelligence. But it can also be applied in other fields such as education and government to aid in planning strategies and in implementing policies.

Data analytics is a broad term that is further differentiated by where it is applied. For example, web analytics provide valuable information related to websites and other users. Other examples of specific analytics applications are project management analytics, big data analytics, and embedded analytics.

Analytics has become an essential tool, especially in business, because of several factors.

  • The volume and frequency of data has tremendously increased
  • The ability of technology to capture, organize, analyze, model, and display data has improved
  • And the value and reliability of making data-driven decisions to improve results has been proven

More companies are using data analytics across their organizations. Marketing teams are using CRM software with customer analytics to improve lead generation and conversion. Modern enterprise systems now include analytics to help HR in hiring decisions and workforce management. Senior management is steadily depending on analytics to help them decide which projects provide the most value, which products will sell better, or which undertaking will have the lowest risk. Users do not have to be data scientists to use and appreciate analytics in available software solutions. In fact, bringing analytics closer to employees in a user-friendly way is a major trend.

Data analytics is not exclusive to big enterprises. Cloud computing and SaaS allow small businesses access to affordable solutions with data analytics. The capabilities of these solutions to provide analytics can vary. The more common are:

  • descriptive analytics to show patterns in historical data for comparisons
  • diagnostic analytics to show anomalies and relationships
  • predictive analytics to forecast and show trends
  • prescriptive analytics to suggest options based on results from other analytics.

Data analytics can help businesses of all sizes better understand their markets, customers, costs, demands, and competitors, allowing them to make better decisions to improve their performance and offer the right products and services.










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