Data Analytics. The science of analyzing raw data to make conclusions based on information gathered. A lot of techniques and processes of data analytics have been automated into mechanical processes and algorithms that work on the raw data for human consumption.

With tons of data to be processed, firms have a high risk or neglecting or missing useful information like trends or metrics which are information that can be used to optimize internal processes and increase the overall efficiency of a business or system.

Data Analysis Steps

  1. Determine the data requirements: The first step in data analysis is knowing how the data is grouped. Analysts can separate data by age, demographic, income, or gender and data values may be numerical or divided into several categories.
  2. Data collection: Data can come from a variety of sources like computers, online sources, cameras, environmental sources, or within the business itself such as employees.
  3. Data organization: This process can be done on a spreadsheet or a form of software that takes statistical data.
  4. Data clean-up:  Cleaning the data means scrubbing and checking for duplicates, errors, and incompleteness before being sent for analysis.

Importance of Data Analytics

With the help of data analytics, businesses are able to optimize their processes and overall performance. Implementing the insights gathered from the analysis can help businesses reduce costs by identifying more efficient ways to do their processes and storing huge amounts of data.

Businesses can also make use of data analytics to come up with better decisions and analyze customer trends and satisfaction which can help them produce and create better products and services.

Types of Data Analytics

  1. Descriptive: Describes the changes that have happened over a given period of time.
  2. Diagnostic: Gives focus on why a certain event or situation happened which involves more diverse data inputs and some hypothesizing.
  3. Predictive: Focused on what is likely to happen in the near future.
  4. Prescriptive: Suggests a course of action.

Looking for ways to efficiently and effectively analyze your data? Contact Proactive Logic today!

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