![]() ![]() This example clearly indicates the basic English difference between analytics and analysis. With analytics, the apparel brand can design its plan of when to launch new products over the coming weeks and months to get the maximum profit. In practice, this means the brand will employ advanced (machine learning) tools and algorithms to make the best use of the historical review and predict future sales patterns. Whereas, analytics combines the results from the analysis of last year’s sales data with logical reasoning to predict future sales pattern and design and plan accordingly. This analysis of what has happened is basically an in-depth review of the past facts. The business/brand owner analyzes last year’s sales data to gain insight into profit trends and sales trends as per seasons, months, and weeks. To gain a deep understanding of what is the difference between analysis and analytics, let’s take an example of an apparel brand. And, the analytics uses this analyzed information to predict what may happen. In other words, the analysis restructures existing available information or data. While analysis looks backward over time and works on the facts and figures of what has happened, analytics work towards modeling the future or predicting a result. According to Merriam Webster, analysis is the division of a whole into small components, and analytics is the science of logical analysis. Let’s start with a general comparison of analysis vs. Key Difference between Data Analysis and Data Analytics.analytics and fully understand both approaches and how these are helpful for businesses. That’s the basic difference, let’s dig further to get in-depth knowledge about data analysis vs. The main difference between data analysis and analytics lies in their approach, as analysis looks toward the past while analytics towards the future. And, this is the part where lies the importance of understanding the difference between data analysis and data analytics. While both of these help in converting the raw data into actionable insights to deliver business value, both terms seem similar in meaning but are quite different. But data is just merely data until it is worked upon to get the business advantage it promises. If you are looking for a career in the field of Data Analyst or data science, then the lack of understanding can affect your ability to make use of customer intelligence to get the best advantage.Īs the use of smartphones, tabs, and laptops is increasing day by day, the data explosion is also increasing many folds. However, these words are used interchangeably but they are significantly different and possess different meanings and importance. With data being the new fuel for businesses that helps gain critical insights and enhance business growth, the need to understand the difference between analysis vs analytics is very important.
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