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Data Analysis: Home

Learn how to interpret and explore data to use data confidently, find answers and make smart decisions.

What is Data Analytics?

Data analytics refers to qualitative and quantitative techniques used to study behavioral data and patterns with a view to improving decision making.

Data analytics is used in many industries to allow companies and organization to make better business decisions and in the sciences to verify or disprove existing models or theories.

Benefits of Analytics

1) Improving The Decision-Making Process

2) Uncovering Fresh Business Insights

3) Boosting Productivity

4) Increasing Sales

5) Improving Financial Efficiency

6) Streaming Internal Processes

7) Improving Customer Loyalty

8) Optimizing Inventory

Steps to perform Data Analytics

The process involved in any data analysis involves several different steps:

  • The first step is to determine the data requirements or how the data is grouped. Data may be separated by age, demographic, income, or gender. Data could be be numerical or text.
  • The second step in data analytics is the process of collecting it. This can be done through a variety of sources such as computers, online sources, cameras, environmental sources, or through personnel.Be ware that the data you collect must be open source and not proprietary!
  • Once the data is collected, it must be organized so it can be analyzed. Organization may take place on a spreadsheet or other form of software that can take statistical or textual data.e.g CSV format
  • The data is then cleaned up before analysis. This means it is scrubbed and checked to ensure there is no duplication or error, and that it is not incomplete. This step helps correct any errors before it goes on to an analytic software to make predictions or identify trends.

Types of Data Analytics

Diagnostic  : A look at past performance to determine what happened and why. The result of the analysis is often an analytic dashboard.

Descriptive : Analytics designed to get you basic expository information: who, what, when, where, how many? Current trends based on incoming data. To mine the analytics, you typically use a real-time dashboard and/or email reports.

Predictive : Analytics that help you identify trends in relationships between variables, determine the strength of their correlation, and hypothesise causality.

Prescriptive : This type of analysis reveals what actions should be taken. This is the most valuable kind of analysis and usually results in rules and recommendations for next steps.