Data analysis and data analytics are often treated as interchangeable terms, but they hold slightly different meanings. Data analysis is the overarching Data Analyst practice that encompasses the use of data analytics tools and techniques to achieve business objectives.
Data analysis is a broader term that refers to the process of compiling and analysing data in order to present findings to management to help inform business decision making. Data analytics is a subcomponent of data analysis that involves the use of technical tools and data analysis techniques.
Which data analytics tools are used by Data Analysts?
- Tableau Public
- Google Fusion Tables
- Wolfram Alpha
- Google Search Operators
Watch this short video where Norah Wulff, Data Architect and Head Tutor on the University of Cape Town Data Analysis online short course, provides some more insight into how data analytics is different to data analysis.
Data analysis is the process of examining, transforming, and arranging raw data in a specific way to generate useful information from it. In essence, data analysis allows for the evaluation of data through analytical and logical reasoning to lead to some sort of outcome or conclusion in some context. It is a multi-faceted process that involves a number of steps, approaches, and diverse techniques. The approach you take to data analysis depends largely on the type of data available for analysis and the purpose of the analysis.The approach you take to data analysis depends largely on the type and purpose of data available. Click To Tweet
Some of the techniques used in improving the effectiveness of data analytics tools in the business context are:
- Association rule learning
- Classification tree analysis
- Genetic algorithms
- Machine learning
- Regression analysis
- Sentiment analysis
- Social network analysis
Do you want to pursue a career in data analysis?
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The difference between data analysis and data analytics is that data analytics is a broader term of which data analysis forms a subcomponent. Data analysis refers to the process of compiling and analysing data to support decision making, whereas data analytics also includes the tools and techniques use to do so.
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