Difference between Data analysis and Data analytics

It all started with a question! Can you differentiate between Data Analysis and Analytics? I tried but failed to find the answer. It forced me to think, why was it so difficult to find the differences between them. Why people use these terms interchangeably, as if they are the same? Anyways, to find the answer, I took out the dictionary and not just any but the dictionary of computing to figure out their formal definitions. Ok here we are – Analog signal - Analog to digital converter - analysis of variance What no entry for analysis? Anyways, let’s look for analytics. Analytical engine - analyzer Seriously no definition for analytics also?!!! Apparently, the dictionary was of no help. So, I had to dig up my class notes from my college days. Voila, found something – Seems like, college does help! Now, that I found something concrete which is enough for me to do this video. Let’s do it! While researching for this video I noticed that on one website data analysis is defined as a process of data collection, data cleaning and data organization. Whereas on another website data analytics was defined as the same. You will be surprised to know that neither of them is the process of data collection, cleaning or organization. In fact, these are the initial steps of data processing. Just think, without having a well-organized dataset, how will you perform an analysis. Or for that matter data analytics to forecast a near perfect future. Now What is Data Analysis? Analysis, in layman language is the process of answering “How” and “Why”. For example – How was the growth of my YouTube channel in last quarter? Or why did the sales of my store dip last winter? To answer these questions, we take the data that we already have. Out of that we filter out that what we need. This filtered data is a finer dataset of the larger chunk that we already have collected. And that becomes the target of our analysis. Or sometimes we take multiple datasets and analyze them to find a pattern. For example, take the winter sales data for 3 consecutive years.

Finding out if that dip in the sale last winter was because of any specific product that we were selling or it’s just a recurring problem. It’s all about looking for the pattern. We do an analysis on things or events that have already happened in the past. Taking all this information we can define data analysis as – The Process of studying the data to find out the answers to how and why things happened in the past. Usually the result of an analysis is a finer dataset, pattern or a detailed report that you can further use for data analytics. So, you are done with analysis. You have all your results, reports and final datasets in your hands. Now what? Next you will take a step towards decision making and that step is known as data analytics. In data analytics we take the dataset or the outcomes of data analysis and process them to find out the events that are likely to occur in the future. For example - Let’s say you own a business and sell dairy products. Your business model is pretty simple. You buy products from the suppliers and sell them to your customers. Let’s assume that the biggest challenge for your business is to find the right amount of stock at a given time. You can’t stock excess dairy products as they are perishable. And if gone bad you can’t sell them. Resulting in a direct loss for you. At the same time, you cannot understock as it may result in loss of potential customers. But data analytics can help you in predicting the strength of your customer at a given time. Using that result you can sufficiently stock your supplies. In turn minimizing your loss. In simple words, using data analytics you can find out that time of the year when your store has the least or the most customers. Using this info, you can stock your supplies accordingly. Another good example of data analytics is the recommendations of products offered by ecommerce websites like amazon. These recommendations are purely based on your buying behaviour plus the time you spent there searching for something.

While analysis is all about analysing the past data. The data analytics is about using that data for forecasting the future. In analytics we put the data under mathematical operations like statistics or various computational and logical reasonings to find an event that can occur in the future. But I heard only data analysis is a decision-making process? No, that’s not true. Because both data analysis and data analytics are decision-making processes. See, You use analysis to find out what has happened in the past and then you use data analytics to figure out what we can do about things that has already happened in the past. Combining both these together you can have a concrete data or report that you can use to make a decision. That will in turn help you in growing your business. This is the simplest explanation that I could come up with to explain you the differences between data analysis and data analytics. Hope this video helped you paint a clear picture of data analysis and analytics. If so then please hit the thumbs up button. Also do subscribe to the channel if you haven’t already and press the bell icon to get notified for the next video. And, for behind the scenes come and join me on Instagram. Find the link in the description. Thanks for watching. This is Manish from RebellionRider.com.