Data Science Analytics and Analyst

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What is Data Science ?
Collaborative field that combine statistical and mathematical methods or process, algorithm to model data,system to analyze the information behind structured and unstructured data is called Data Science. Machine learning, statistical knowledge, computer programming, domain knowledge and a quick observer are the tools which must be handy to become an expert Data scientist. Analytically and statistically getting keys behind data, wrangling and exploratory data analysis,  testing hypothesized
data and prediction analysis are some key steps which we need to follow when are we going to know the science behind data.

Evolution of Data Science
Nowadays Data Science huge in demand and was originally come in beginning of 21st century. At first William S. Cleveland expressed “Data Science: Provide a Plan for Expanding the Technical Areas in the Field of Statistics.” in 2001. In 2003 Columbia University start publishing “The Journal of Data Science.” Amazon , Google and Yahoo! Type company produces huge number of data which we called Big Data. To handle these data cloud computing comes in picture and Map Reduce is one of the important discovery   within cloud computing and the codified version is Hadoop , in short we can say that Hadoop to go computing on huge amount of data(Big Data) in cloud computing. But the problem didn’t stop here,the data was so huge in amount that it is difficult to handle these data, in-fact we are unable to put everything into the calculation. Rather, we drive numerous duplicates of the calculation out to the data. Here Analytics with simple interface comes in recommended systems,Machine learning and Complex Event processing are some tools of “Mass Analytic Tools” which are being used . For handling these tools we need people who can handle big data and so the role of “Data Scientist” get evolved. The amount of data which generates daily is so huge that no single individual can do every one of the data preparing and scientific analysis synthesis. So Data Science can be best practiced in a team.

Analytics and Analyst
Analytics — exploring truth behind data to know  meaningful information by interpreting and analyzing. Statistics, computer programming and research are the toolkit which help analyst to know about data. Data analysts are those who extract meaningful insights from various data sources.

Working of Data Science Analytics
Let us understand the same using examples,we all love shopping in big market and malls usually,also we notice there is a person well-dressed on gate, welcome us and clicked on some gadget once we are in the market. Can you imagine what’s was going with that click?what is the use of that? Let me tell you,they are collecting data, of how many footfalls they had in their store that day and the use of these data come in,once they are checking their sales figure. Generally we had seen that these stores give us discount on weekend days when count of footfall are more than week days. As they know that as the number of footfall will get high the chances of selling of product will also get high. So here the analyst who comes in role and do analysis on data, result of which company making profit by this. Let’s take another example of,we all are aware of AADHAR Card, which is now mandatory for every Indian citizens. Can you imagine why this card is so mandatory even we have voter-ID card? Why it is so mandatory to link it with Bank? AADHAR helps our government to get exact data of every person once they do transaction with bank. It helps government to track the tax theft and help to reduce this theft,who used to do this practice earlier before implementation of AADHAR concept.

Concept behind Data Science Analytics
FlipkartAlibaba, Amazon etc these are big giant E-commerce platform, where lots of data generate every moment. Obviously lots of question comes in front of company to make this platform more profitable and competitive to other firms. Like Amazon show us the product we want to buy and other related product according to our search criteria, discount on product according to the demand. More active on seasonable product. Also send notification to customer who used to shop a lot. These analyses which comes in picture is done by Analytics and Analyst who figure out data and tell company about this analysis. So there are lots of example where analytics help us to solve our complex problem. In fact, we can say that analytics is all around us, but we used to talk it in business term specially.

As we know a huge amount of data generate every day from Bank, Health-care, Social platform, E-commerce sites and its impossible for human mind to handle these data manually. Here Analytics come in the form of solution which help us to deal with data and result as an output. Analytics allow us to use sophisticated statistical algorithms and leverage computing power to explore, analyze and understand the data to generate insights from it and to discover hidden patterns that once we understand we will be able to make better decisions and run the business better.

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