Data Analytics
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What is Data Analytics?
Data analytics is defined as The process of collecting, organizing and analyzing data in order to identify patterns or trends. It encompasses many different types of analysis with various purposes.
Data analytics involves many steps that can be utilized for various projects. Combining these elements will give a clear picture of where you are, where you’ve been and what future goals need to be accomplished.
What is the Role of Data Analytics?
A data analyst is someone who lives at the crossroads of information technology, statistics, and business. Data analysts are all about making sure businesses can operate as smoothly and efficiently as possible - where every person counts for something more than just a number or statistic in a system that has too many numbers anyways.
Data analysts work primarily with data throughout the data analysis pipeline. In other words, they handle it in different stages of its completion- from mining to presentation. The four major steps in this process are data mining (collecting raw data), Data Management (handling the dirty stuff), Statistical Analysis (deciding what to do with it) and Data Presentation (serving up the sweet bits).
Why Data Analytics is Important?
Data analytics are very useful in improving efficiency across multiple industries. This leads to increased performance for businesses who want to maintain a competitive edge.
One of the first innovators in this field was the financial sector. Data analysis is central to the banking and finance industry, as it helps anticipate what markets will do next. Credit scores are a specific kind of data analysis that measures how risky someone is based on many different factors before being given credit by a bank or other institution. It can also detect fraudulent activity- this gives these companies more security and reduces risk when trading money.
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