Data analytics process of analyzing raw data to find trend and answer questions. It has broad scope across field. This process includes many techniques and goals that shift from industry to industry.
The data analytic process has components that help variety of initiative. By combining these components, successful data analytics initiative help answer business question related to historical trend, future prediction and decision-making.
Data analysts work at intersection of information technology, statistic and business. They combine these field to help businesses and organization succeed. A significant goal for data analyst is to increase efficiency and improve performance by discovering pattern in data.
There are four major types of data analytic:
To study sales pattern, consumer behavior, and inventory management, data analytic applied in retail sector. Data analytics use by retailer to make data-driven decision regarding what product to stock, how to price them, and how to organize their store best.
Data analytics use to evaluate patient data, spot trend in patient health, and create individualized treatment program. Data analytic used by healthcare companies to enhance patient outcome and lower healthcare expenditures.
In finance, data analytics used to evaluate investment data, spot trends in financial markets, and make wise investment decisions. Financial institutions use it to lower risk and boost performance of investment portfolio.
By analyzing customer data, spotting trend in consumer behavior, and creating customize marketing strategies, data analytics used in marketing. Data analytics can used by marketer to boost efficiency of campaigns and their overall impact.
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