If data is the new oil, then analytics is the new engine to consume this uncertain matter.

As we are rushing towards the new decade, the ways doing the businesses or the processes are going through a huge transition to find their more accurate target audience, fulfil their needs in a much better way and to get an edge over their competitors. So, analytics is one such part of the transition where things are analyzed in the data that a particular company has.

Nowadays many firms no matter online or offline are excessively relying on data to make there both long term and short term decisions. But data comes in many forms and are mostly unstructured, so to resolve that part, analytics takes the wheel in his hands, Analytics has changed the way world used to see the data as it has simplified it in such a way that has made and improved the decision-making skills of the leaders. It completely simplifies and structures the unstructured data. Its doesn't get limited to this but it also supports the viewer or the compiler or the decision-maker to find the trend or the pattern in the data, customer behaviour or the thought process of purchasing a product, prediction on the based of past or current data available and much more depending upon which tool you are using as every analytical tool have its own capabilities. So it depends upon the user that how one implements and understand the results from the structured data. Analytics can be used in any domain whether it Information Technology, E-Commerce, Retail Market, etc. Let's understand it with the help of an example by taking Digital Marketing as our domain for implementing analytics. In digital marketing the most commonly used analytical tools are SPSS, Google Analytics, Facebook Analytics, Firebase for mobile-based analytics, Twitter Analytics and there are several others as well which can be used depending upon one's requirement.

So, let's say we ran a campaign on Facebook for the awareness and consideration of our brand X for a period one month. Now the analytics part will be enabled as soon as some data will be generated or activity will start happening like people will start viewing our advertisement, people will start clicking on our advertisement, in short engagements will happen in one form or the other. Analytics in Facebook Ads Campaign Manager will show us all these data in a structured form like total no. of views, total no. clicks, etc. and it will also that how every day or week our campaign has performed. Everything will be represented in an appealing and desirable format which can be easily understood by the user or viewer. So the data which has been transformed into meaningful information by Facebook Analytics can be used in two ways: firstly, our campaign can be optimized during the tenure it's running like we can A/B testing or change in some text or image to see our campaign can be improved and secondly, at the end of a campaign that we help us to make a decision that we should continue with our brand, what changes can be made in our brand, how our audience is perceiving our brand and all these things can be done with the support or leveraging the strength of analytics with data. Such thing can be achieved with the help of Google Analytics if we integrate our data our ads campaign manager account with google and therefore we come to the benefit of third party analytical tool as it allows data integration from the source of your data generation so that no doping of data can be done.

So the strength of analytics is totally in the hands of the user, as to how one can leverage the raw data it has and get the most benefit out of it with the support of analytics. Analytics is not helping internally in a company but externally in the economy as well. The huge amount of investments are done eventually creating a large number of jobs as well. As this is mostly a skill-based work one needs to keep on updating himself according to the trends in the market or the industry he is working rather than getting more degrees or certification as more of in-hand experience is required to completely master this skill. Analytics is getting deeper day by day with the involvement or integration of various other concepts with it like Big data where analytics is a very important concept in it, Artificial Intelligence to automate analytics and bring out more meaningful data eventually leading to better decision making and all these subjects are going to get more connected and involved together with time to get one's maximum productivity in their field. So, let's see how our student, employee, company or government take these things ahead and get the maximum gain out of it for the industry, economy or country.