High-Performance Data Analytics

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</script>   </div> <div class="sectionenhanced parbase section"> <section data-section-title="Transformative Technology" id="transformative-technology" class=" background-body-copy p-t-75 p-b-0 lap-p-t-75 lap-p-b-0 tab-p-t-45 tab-p-b-0 mob-p-t-30 mob-p-b-0 "> <div id="sectionenhanced_47050a7a9305_4bf9_42b1_a8f9_0d8c9cfc2d6c" class="general-container "> <div class="large-12 large-12 medium-12 small-12 center"> <div class="container"> <div class="page-section-par parsys"><div class="textcomponentenhanced section"> <div id="textcomponentenhance4c2cd2c9_e89c_4453_959b_8914572fd9a8"> <div class="general-container-text small-12 mob-p-content medium-12 tab-p-content large-12 lap-p-cozy large-12 d-p-cozy p-t-0 p-b-0 lap-p-t-0 lap-p-b-0 tab-p-t-0 tab-p-b-0 mob-p-t-0 mob-p-b-0 "> <div class="text-center lap-text-center tab-text-center mob-text-center"> <h2 class="title color-black h2 none" >Transformative Technology for Immediate Results</h2> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"> </div> </div> </div> </div> </div> </div> <div class="columnLayoutEnhanced parbase section"> <div class="background-none p-t-75 p-b-75 lap-p-t-75 lap-p-b-75 tab-p-t-45 tab-p-b-45 mob-p-t-45 mob-p-b-45 " > <div class="column-container clearfix "> <div class="large-12 large-12 medium-12 small-12 center"> <div class="row no-divider equial-h-col" id="columnlayoutenhanced2eed2d90_adcb_475e_a119_2ee9db3c67a2"> <div class="column left-column small-12 medium-6 large-6 "> <div class=""></div> <div class="background-none equi-height-col "> <div class="column-1 parsys"><div class="textcomponentenhanced section"> <div id="textcomponentenhance43d65aa1_71d7_4c85_a512_5a686af8a211"> <div id="industry-challenge-bullet" class="general-container-text small-12 mob-p-content medium-12 tab-p-content large-12 lap-p-content large-12 d-p-content p-t-0 p-b-0 lap-p-t-0 lap-p-b-0 tab-p-t-0 tab-p-b-0 mob-p-t-0 mob-p-b-0 "> <div class="text-center lap-text-center tab-text-center mob-text-center"> <h3 class="title color-black h3 none" >Industry Challenges</h3> <div class="description color-black intro-copy-text"><ul style="font-size: 24.0px;"> <li style="text-align: left;">Data preparation is a complex, time-consuming process that consumes a majority of a data scientist's time.<br> <br> </li> <li style="text-align: left;">Iteration takes substantial time leading to less <span style="white-space: nowrap;">robust analyses.</span> <br> <br> </li> <li style="text-align: left;">Downsampling datasets leads to suboptimal results.<br> <br> </li> </ul></div> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"> </div> </div> </div> </div> </div> </div> <div class="rawHtml section"> <div class=' p-t-15 p-b-15 lap-p-t-15 lap-p-b-15 mob-p-t-15 mob-p-b-15 tab-p-t-15 tab-p-b-15' > <style> /*#industry-challenge-bullet li {list-style: circle;}*/ </style> </div> </div> </div> </div> <div class="singlecolumnborder"></div> </div> <div class="column right-column small-12 medium-6 large-6 "> <div class=""></div> <div class="background-none equi-height-col "> <div class="column-2 parsys"><div class="textcomponentenhanced section"> <div id="textcomponentenhanceaca34aae_4fc3_44e0_a7d8_b7bfcc5916c6"> <div class="general-container-text small-12 mob-p-content medium-12 tab-p-content large-12 lap-p-content large-12 d-p-content p-t-0 p-b-0 lap-p-t-0 lap-p-b-0 tab-p-t-0 tab-p-b-0 mob-p-t-0 mob-p-b-0 "> <div class="text-left lap-text-left tab-text-left mob-text-left"> <div class="description color-black body-text"><p>Businesses utilize analytics to understand their data and drive business decisions. While data analytics has unlocked vast potential, traditional CPU-based data processing and analysis have increased overhead and added complexity to business operations, decreasing the return on investment. Accelerated data science ushers in a new era of data analytics, allowing for organizations and practitioners to get the most out of their data and their infrastructure.</p> <p>Accelerated data science delivers improvements across the end-to-end data analytics workflow, whether you鈥檙e transforming data for enterprise consumption or visualizing terabyte-scale data to understand a particular problem domain. Data practitioners can leverage NVIDIA GPUs with ease using their preferred toolset, bringing the power of high-performance computing to your organization with a minimal learning curve.</p> <p>By harnessing the power of high-performance data analytics, businesses can better serve their customers, develop products faster, and enable innovations across their enterprise.</p></div> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <script> NVIDIAGDC.funcQueue.addToQueue({ id : "columnlayoutenhanced2eed2d90_adcb_475e_a119_2ee9db3c67a2", method : "columnlayoutenhanced", params : [{ columnsNumber: 2, imageBigDesktopUrl1: 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class="background-white p-t-0 p-b-0 lap-p-t-0 lap-p-b-0 tab-p-t-0 tab-p-b-0 mob-p-t-0 mob-p-b-0 " > <div class="column-container clearfix mob-stack-RL"> <div class="large-12 large-12 medium-12 small-12 center"> <div class="row no-divider equial-h-col" id="columnlayoutenhanced29d805fe_1d56_4cc3_9ce8_5fe4c8299164"> <div class="column left-column small-12 medium-6 large-6 order-2 "> <div class=""></div> <div class="background-none equi-height-col "> <div class="column-1 parsys"><div class="textcomponentenhanced section"> <div id="textcomponentenhanced6c1eb73_e549_4533_af53_1cf9c5e598e2"> <div class="general-container-text small-12 mob-p-content medium-12 tab-p-content large-12 lap-p-content large-12 d-p-content p-t-0 p-b-0 lap-p-t-0 lap-p-b-0 tab-p-t-0 tab-p-b-0 mob-p-t-0 mob-p-b-0 "> <div class="text-left lap-text-left tab-text-left mob-text-left"> <h2 class="title color-black h2 none" >Lightning-Fast Performance on Big Data</h2> <div class="description color-black body-text"><p>Results show that GPUs provide dramatic cost and time-savings for small and large-scale Big Data analytics problems. Using familiar APIs like Pandas and Dask, at 10 terabyte scale, RAPIDS performs at up to 20x faster on GPUs than the top CPU baseline. Using just 16 NVIDIA DGX A100s to achieve the performance of 350 CPU-based servers, NVIDIA鈥檚 solution is 7x more cost effective while delivering HPC-level performance.</p> <p><a href="https://blogs.nvidia.com/blog/2020/06/22/big-data-analytics-tpcx-bb/"><span style="font-weight: 700;">Read Post </span><span class="fas fa-angle-right fa-fw"></span></a></p></div> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"> </div> </div> </div> </div> </div> </div> </div> </div> <div class="singlecolumnborder"></div> </div> <div class="column right-column small-12 medium-6 large-6 order-1 "> <div class=""></div> <div class="background-none equi-height-col "> <div class="column-2 parsys"><div class="image parbase section"> <div id="image1be27513_50a7_4676_9c3a_7ea8a5d1c5fe" class="image-container p-t-0 p-b-0 lap-p-t-0 lap-p-b-0 tab-p-t-0 tab-p-b-0 mob-p-t-0 mob-p-b-0"> <div class="imgwidth "> <img 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NVIDIA and its partners provide solutions to run data science workflows from your laptop, to the cloud, as well as on-premises with <a href="https://www.nvidia.com/en-us/data-center/products/certified-systems/" target="_self">NVIDIA-Certified Systems</a>. These solutions combine hardware and software optimized for high-performance data analytics to make it easy for businesses to get the most out of their data. With the <a href="https://www.nvidia.com/en-us/deep-learning-ai/software/rapids/" target="_self">RAPIDS</a> open-source software suites and NVIDIA CUDA, data practitioners can accelerate analytics pipelines on NVIDIA GPUs, reducing data analytics operations like data loading, processing and training from days to minutes. 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