Data analytic uses scientific tools to analyze data in order to draw conclusions. Almost all industry verticals are using data analytic as a tool in order to make better business decisions. Often data analytic is misunderstood as data mining but focus and purpose for both are different.
While data mining is all about sorting through huge databases in order to set up hidden relationships and identify patterns which are not revealed, data analytic focuses on obtaining conclusion.
The science of Data Analysis is generally divided into:
Exploratory data analysis: where new features in the data are discovered.
Confirmatory data analysis: where existing hypotheses are proven true or false.
In order to draw conclusions from non-numerical data like words, photographs or video, Qualitative analysis is used..
Data analysis techniques are useful for virtually any business to gain greater insight into the trends within their business, their industry, and their customer base. Data analysis is also used to determine whether the systems in place effectively protect data, operate efficiently and succeed in accomplishing an organization’s overall goals.
Customer Loyalty, Partner Relationship Programs, Sales Programs generate huge volumes of data. Data Analytic ensures proper analysis and helps to get analyzed information to the most critical points of business process.
Some of the examples of industries which use data analytic to draw facts and conclusions are banks to analyze withdrawal and spending patterns to avoid fraud, call centers for CRM analytic, eCommerce companies or online stores to understand navigation patterns to understand which customers are more likely to buy a product or service. This will also helps to keep a track on the competitors website like what discount they are giving to the customers.
Many retail companies run customer loyalty programs for their customers which generate huge sets of data which is analyzed by the analytic to track most valuable customers understand their behaviors and accordingly modify the communication strategy.