The benefits of analyzing vast amounts of data, long-term or in real-time, has captured the attention of businesses of all sizes. Big data analytics has moved beyond the rarified domain of government and university research environments equipped with supercomputers to include businesses of all kinds that are using modern high performance computing (HPC) solutions to get their analytics jobs done. Its big data meets HPC \u2015 otherwise known as high performance data analytics. \n\nBigger, Faster, More Compute-intensive Data Analytics\n\nBig data analytics has relied on HPC infrastructure for many years to handle data mining processes. Today, parallel processing solutions handle massive amounts of data and run powerful analytics software that uses artificial intelligence (AI) and machine learning (ML) for highly demanding jobs.\n\nA report by Intersect360 Research found that \u201cTraditionally, most HPC applications have been deterministic; given a set of inputs, the computer program performs calculations to determine an answer. Machine learning represents another type of applications that is experiential; the application makes predictions about new or current data based on patterns seen in the past.\u201d\n\nThis shift to AI, ML, large data sets, and more compute-intensive analytical calculations has contributed to the growth of the global high performance data analytics market, which was valued at $48.28 billion in 2020 and is projected to grow to $187.57 billion in 2026, according to research by Mordor Intelligence. \u201cAnalytics and AI require immensely powerful processes across compute, networking and storage,\u201d the report explained. \u201cAs a result, more companies are increasingly using HPC solutions for AI-enabled innovation and productivity.\u201d\n\nBenefits and ROI\n\nMillions of businesses need to deploy advanced analytics at the speed of events. A subset of these organizations will require high performance data analytics solutions. Those HPC solutions and architectures will benefit from the integration of diverse datasets from on-premise to edge to cloud. The use of new sources of data from the Internet of Things to empower customer interactions and other departments will provide a further competitive advantage to many businesses. Simplified analytics platforms that are user-friendly resources open to every employee, customer, and partner will change the responsibilities and roles of countless professions.\n\nHow does a business calculate the return on investment (ROI) of high performance data analytics? It varies with different use cases.\n\nFor analytics used to help increase operational efficiency, key performance indicators (KPIs) contributing to ROI may include downtime, cost savings, time-to-market, and production volume. For sales and marketing, KPIs may include sales volume, average deal size, revenue by campaign, and churn rate. For analytics used to detect fraud, KPIs may include number of fraud attempts, chargebacks, and order approval rates. In a healthcare environment, analytics used to improve patient outcomes might include key performance indicators that track cost of care, emergency room wait times, hospital readmissions, and billing errors.\n\nCustomer Success Stories\n\nCombining data analytics with HPC:\n\nData Scientists are Part of the Equation\n\nHigh performance data analytics is gaining stature as more and more data is being collected. Beyond the data and HPC systems, it takes expertise to recognize and champion the value of this data. According to Datamation, \u201cThe rise of chief data officers and chief analytics officers is the clearest indication that analytics has moved from the backroom to the boardroom, and more and more often it\u2019s data experts that are setting strategy.\u201d \n\nNo wonder skilled data analysts continue to be among the most in-demand professionals in the world. The U.S. Bureau of Labor Statistics predicts that the field will be among the fastest-growing occupations for the next decade, with 11.5 million new jobs by 2026. \n\nFor more information read \u201cUnleash data-driven insights and opportunities with analytics: How organizations are unlocking the value of their data capital from edge to core to cloud\u201d from Dell Technologies. \n\n***\n\nIntel\u00ae Technologies Move Analytics Forward\n\nData analytics is the key to unlocking the most value you can extract from data across your organization. To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that\u2019s optimized to work with the software you use.\n\nModern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI). Just starting out with analytics? Ready to evolve your analytics strategy or improve your data quality? There\u2019s always room to grow, and Intel is ready to help. With a deep ecosystem of analytics technologies and partners, Intel accelerates the efforts of data scientists, analysts, and developers in every industry. Find out more about Intel advanced analytics.