Big Data Analytics
The term "big data" refers to digital stores of information that have a high volume, velocity and variety. Big data analytics is the process of using software to uncover trends, patterns, correlations or other useful insights in those large stores of data.
Data analytics isn't new. It has been around for decades in the form of business intelligence and data mining software. Over the years, that software has improved dramatically so that it can handle much larger data volumes, run queries more quickly and perform more advanced algorithms.
Benefits of Big Data Analysis for Modern Enterprises
Big Data Analytics enables enterprises to analyze their data in full context quickly, and some offer real-time analysis. With high-performance data mining, predictive analytics, text mining, forecasting, and optimization, enterprises that utilize Big Data Analytics are able to drive innovation and make the best business decisions.
Specifically, Big Data Analytics enables enterprises to narrow their Big Data to the most relevant information and analyze it to inform critical business decisions. This proactive approach to business is transformative because it gives analysts and decision makers the power to move ahead with the best knowledge and insights available, often in real time.
Application areas of Big Data Analytics Tools & Solutions:
Clinical research is a slow and expensive process, with trials failing for a variety of reasons. Advanced analytics, artificial intelligence (AI) and the Internet of Medical Things (IoMT) unlocks the potential of improving speed and efficiency at every stage of clinical research by delivering more intelligent, automated solutions.
Financial institutions gather and access analytical insight from large volumes of unstructured data in order to make sound financial decisions. Big data analytics allows them to access the information they need when they need it, by eliminating overlapping, redundant tools and systems.
For manufacturers, solving problems is nothing new. They wrestle with difficult problems on a daily basis - from complex supply chains, to motion applications, to labor constraints and equipment breakdowns. That's why big data analytics is essential in the manufacturing industry, as it has allowed competitive organizations to discover new cost saving opportunities and revenue opportunities.
Big data is a given in the health care industry. Patient records, health plans, insurance information and other types of information can be difficult to manage – but are full of key insights once analytics are applied. That’s why big data analytics technology is so important to heath care. By analyzing large amounts of information – both structured and unstructured – quickly, health care providers can provide lifesaving diagnoses or treatment options almost immediately.
Certain government agencies face a big challenge: tighten the budget without compromising quality or productivity. This is particularly troublesome with law enforcement agencies, which are struggling to keep crime rates down with relatively scarce resources. And that’s why many agencies use big data analytics; the technology streamlines operations while giving the agency a more holistic view of criminal activity.
Customer service has evolved in the past several years, as savvier shoppers expect retailers to understand exactly what they need, when they need it. Big data analytics technology helps retailers meet those demands. Armed with endless amounts of data from customer loyalty programs, buying habits and other sources, retailers not only have an in-depth understanding of their customers, they can also predict trends, recommend new products – and boost profitability.