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Things You Should Know about Big Data Analytics
To name a few applications, big data can be used for real-time fraud detection, complex, competitive analysis, call center optimization

By
Apac CIOOutlook | Thursday, January 06, 2022
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Diagnostic analytics is used to make discoveries or to figure out why something happened. For instance, one can utilize diagnostic analytics to assess the number of posts, mentions, followers, page views, fans, reviews, pins, and so on for a social media marketing campaign.
Fremont, CA: To name a few applications, big data can be used for real-time fraud detection, complex, competitive analysis, call center optimization, intelligent traffic management, consumer sentiment analysis, and smart power grid management. Big data is defined by three primary factors: volume; velocity. Because it draws from various sources and transactions to uncover hidden patterns and relationships, big data can provide richer insight with the right analytics.
Prescriptive analytics is extremely valuable, but it is rarely used. Whereas big data analytics in general sheds light on a topic, prescriptive analytics provides a laser-like focus on answering specific questions. In the healthcare industry, for instance, one can better manage the patient population by using prescriptive analytics to determine the number of clinically obese patients, then adding filters for factors like diabetes and LDL cholesterol levels to ascertain where to focus treatment. Almost any industry target group or problem can be addressed utilizing the same prescriptive model.
Predictive analytics makes use of big data to identify past patterns in order to forecast the future. Some businesses, for instance, use predictive analytics to score sales leads. Some companies have taken predictive analytics a step further, analyzing the lead source, number of communications, types of communications, documents, social media, CRM data, and so on for the entire sales process. Predictive analytics, when properly tuned, can be utilized to support sales, marketing, and other types of complex forecasts.
Diagnostic analytics is used to make discoveries or to figure out why something happened. For instance, one can utilize diagnostic analytics to assess the number of posts, mentions, followers, page views, fans, reviews, pins, and so on for a social media marketing campaign. There may be thousands of online mentions that can be distilled into a single view to see what worked and what did not in previous campaigns.
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