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Is There Any Similarity Between Data Analysis & Data Analytics?
The terms data analysis and data analytics are two different terms which are being used interchangeably. Lack of understanding in the concepts that differentiate these technologies will surely lead to adverse affects on the enterprises ability to leverage customer intelligence to their best advantage.
To better understand the difference between these technologies we can relate them with the terms past and future. Data Analysis relates to delivering stakeholders a historical view of what has happened where as Data Analytics looks ahead into the future to present the stakeholders with accurate predictions.
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Differentiating Data Analytics & Data Analysis-
Data Analytics- It is a general form of analytics which is extensively used across business for extracting insights from the data to make informed decisions
Data Analysis- It is a specialized form of analytics used by businesses for analyzing data
Data Analytics- The structure of Data Analytics involves Machine Learning models, Statistical Analysis & as well as computer-based models & is having one or more usage
Data Analysis- The structure of Data Analysis consists of defining data investigation, cleaning, transforming data so as to give it a meaning outcome
Data Analytics- It makes use of sophisticated analytics tools like Microsoft Excel, SAS, R, Python (libraries), Tableau, Apache Spark & more.
Data Analysis- Itmakes use ofadvanced tools like Open Refine, Tableau public, KNIME, Google Fusion Tables, Node XL and more
- Sequence Of Steps
Data Analytics- The sequence of steps involved in Data Analytics lifecycle are Business Case Evaluation, Data Identification, Data Acquisition & Filtering, Data Extraction, Data Validation & Cleansing, Data Aggregation & Representation, Data Analysis & Data Visualization, Communicating the results
Data Analysis- The sequence of steps involved in Data Analysis lifecycle are Data Collection, Data Scrubbing, Analyzing the data & interpreting with the data
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