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Prescriptive analytics: three ways to maximize customer success through Big Data

@machinelearnbot

"I've invested in analytics and have thousands of data points streaming into our databases, yet life doesn't seem any easier." Unfortunately, this is a very common complaint about Big Data investments. Teams get overwhelmed with too much data, and analysis often takes longer if you throw more data at a problem. A newly emerging trend in this space is the use of "prescriptive analytics" -- rather than simply collecting data, your team can rely on automated analysis tools to generate recommendations (i.e. This means no more lengthy data reviews, but simply allowing the prescriptive tool to make business decisions on its own.


How Prescriptive Analytics Is Changing The Face Of Every industry?

#artificialintelligence

Source Similar to agriculture, data analytics is playing a vital role in the advancement of the healthcare sector. With the easy availability of smart devices including smartwatches, smartphones, and smart wristbands), a new dimension of healthcare has emerged – Smart Healthcare.


Descriptive, Predictive & Prescriptive Analytics will fail to Help You Understand Your Business

@machinelearnbot

Predictive analytics are also useful when it comes to forecasting product or service demand for a particular geography or taking a segment approach for customer services; and adjusting manpower and production, accordingly. Data sets put at task for performing this analytics include data from weather, example, sales data, social media data etc. The usage of historical and transactional data needs a special mention here. They are used to identify patterns, whereas statistical models and algorithms are utilized to assess the relationship between several data sets. With the advent in Big Data, predictive analytics has taken a really big leap.


Prescriptive Analytics Adoption on the Rise

#artificialintelligence

For years, while predictive analytics dominated the analytics spotlight, prescriptive analytics labored in the shadow of its higher profile cousin, despite the myriad advantages it offers. But that is beginning to change. Adoption for prescriptive analytics is at an all-time high, and Gartner predicts the market will reach 1.1 billion by 2019. Profitect CEO Guy Yehiav is among many who consider prescriptive analytics "the next level of predictive analytics." Data Informed spoke with Yehiav about the growing interest in prescriptive analytics, how it differs from predictive analytics, and the advantages that it offers.


Big Data, Predictive, & Prescriptive Analytics: What You Need To Know

#artificialintelligence

We're officially in Q2 of 2017, and it's clear that some of the same industry-leading trends that having been influencing HR for years have continued to advance and will remain hot topics for the foreseeable future. Big Data and its natural counterpart, analytics, showed the potential to impact nearly every aspect of HCM–and recent advancements have made them increasingly instrumental for today's HR and business leaders. Big Data provides a staggering wealth of quantitative information, often mined from millions of complex data points to shed light onto patterns, trends and outliers that can significantly affect organizations. Because of Big Data's sheer enormity, advanced analytics are necessary to glean any usable insights from these massive collections, and current technology is capable of much more than simply detecting organizational trends (although this alone is quite valuable, too). Today's analytical HCM solutions can predict everything from performance success to retention risk, using unbiased mathematical algorithms to forecast future scenarios with tremendous accuracy.