Data Analysis and Data Analytics are often used as synonyms. These are treated as identical terms and might seem similar but in reality, they hold different meanings.
Data Analysis is a process that largely involves collection, inspection, separation, transformation and examination of data. It is about studying a given set of data and inspecting it for inferences, deductions and insights.
Data Analytics is defined as “a process in which a computer examines information using mathematical methods in order to find useful patterns”. This means that in data analytics, data is transformed into actions through analysis.
Tools used in data analytics include:
- Tableau Public
- Apache Spark
Key differences between Data Analysis and Data Analytics
- Data analysis is a process whereas data analytics is an overreaching science or discipline that embodies thorough management of data.
- Data analysis and analytics differ in scope, scale and size. Data analysis is a narrow term and data analytics is a wider term. Data analysis is a subset/subcomponent of data analytics. Data analytics is more expansive and comprehensive in its scope.
- Another way to differentiate data analysis and data analytics is to think in terms of past and future.
- Data analysis is to review and analyse past data set. Analysis looks back over time and provides insights on what has happened. For example, data analysis is used to analyse sales data of an organisation for the past two years and helps to understand profit trends.
- Data analytics includes analysis of data to know what occurred in the past but it is more focussed on conducting systematic, logical, computational and deductive reasoning. For example, data analytics is used to determine where and when to launch new products and services.
- Data analytics for advertising and marketing insights: Data analytics can ensure that the marketing campaigns are powerful. With the help of this technology, marketers can observe online activity and monitor the point of sale transactions. Businesses can run more personalised and targeted campaigns. The most used OTT platform, Netflix, uses data analytics. Netflix collects huge chunk of data and analyses it based on its users search history and past watch data. This data is then used to send its users movies and shows suggestions based on their interests.
- Data analytics for products: With the help of data analytics, companies can develop and innovate their products. The giant conglomerate, Titan, has used the data analytics technology to develop its various brands like Tanishq, Fastrack, etc. Data analytics provides an insight into products that are performing well and products that are not up to the mark. This helped the Titan group to decide which merchandise should go in stores across all regions. Due to data analytics, they were able to influence ₹800 crores plus purchases across various businesses.
- Data analytics for sales forecasting: Data analytics can be used to reach accurate sales forecasting in different parts of the world and at different times. Titan group used this technology to forecast sales. The group was able to achieve 93% accuracy in sales forecasting in the last financial year.
Data analytics helps organisations to identify new opportunities by predicting the future results. Data analytics answers the question “what will happen next”. To be able to undertake data analytics, businesses must conduct data analysis first. Both data analysis and data analytics are important for an entity to make informed and evidence-based business decisions.
Square Mile Global Consulting is a London-headquartered financial training and consulting company. We have partnered with the American Institute of Certified Public Accountants (AICPA) to offer certificate courses on Data Analysis, Cybersecurity and Blockchain.
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