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Malcolm McRoberts

BI Platform Analytics | Business Intelligence | SAP - 0 views

  • This offering is a complete analytics platform that combines market-leading data integration, data management, and business intelligence (BI) products, pre-certified to run together – for a more effective way to harness big data.
  • zed Analytics Server Analyze massive quantities of data 100 times faster than traditional relational databases – for more accurate insight into performance and market dynamics. Run big data analytics with unsurpassed query performance – for faster decision making Uncover new ways to reduce overhead, storage costs, and maintenance spend Offer accurate, timely information to end users across the organization Gain greater scalability with an open, flexible, column-based architecture SAP Sybase IQ .multilinkwidget a.btn-doc{ padding-bottom:10px; } $(document).ready(function(){ setTimeout(function() { if($("td em button.x-btn-text", $("tr.x-toolbar-left-row")).length > 0) $("td em button.x-btn-text", $("tr.x-toolbar-left-row")).each(function() { if($(this).html()== 'Edit' && $("td em button.x-btn-text", $(this).parents("td.x-toolbar-cell").next()).html() == 'Manage Links'){ $(this).parent().parent().parent().parent().remove(); } }); },3000); }); Less Business Intelligence Platform Make it easy to discover and share insight with a business intelligence platform that gives you flexibility, scalability, and function. Increase the range of data accessible to business users Reduce IT workload with simplified maintenance and administration options Integrate all enterprise data regardless of format or location Centrally manage, control, and configure your BI deployment SAP BusinessObjects BI Platform .multilinkwidget a.btn-doc{ padding-bottom:10px; } $(document).ready(function(){ setTimeout(function() { if($("td em button.x-btn-text", $("tr.x-toolbar-left-row")).length > 0) $("td em button.x-btn-text", $("tr.x-toolbar-left-row")).each(function() { if($(this).html()== 'Edit' && $("td em button.x-btn-text", $(this).parents("td.x-toolbar-cell").next()).html() == 'Manage Links'){ $(this).parent().parent().parent().parent().remove(); } }); },3000); }); Less $(document).ready(function() { // Expand all content by default // $('.rmuc_expandableLI').each(function () { $(this).css('height', 'auto'); }); });
  • Highly Optimized Analytics Server Analyze massive quantities of data 100 times faster than traditional relational databases – for more accurate insight into performance and market dynamics.
Malcolm McRoberts

Big Data Analytics: Descriptive Vs. Predictive Vs. Prescriptive - InformationWeek - 0 views

  • In any big data setup, the first step is to capture lots of digital information, "which there's no shortage of
  • The purpose of descriptive analytics is to summarize what happened. Wu estimated that more than 80% of business analytics -- most notably social analytics -- are descriptive.
  • In the most general cases of predictive analytics, "you basically take data that you have to predict data you don't have,"
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  • "Prescriptive analytics is a type of predictive analytics," Wu said. "It's basically when we need to prescribe an action, so the business decision-maker can take this information and act."
  • In addition, prescriptive analytics requires a predictive model with two additional components: actionable data and a feedback system that tracks the outcome produced by the action taken.
Malcolm McRoberts

Big Analytics For Hadoop and EDWs | Revolution Analytics - 0 views

  • Revolution R Enterprise transparently runs R analytics inside Hadoop and Teradata EDWs, providing your team with:
Malcolm McRoberts

Patient Experience Data and Advanced Analytics - Press Ganey - 0 views

  • Unleash Targeted Insights through Advanced Analytics As hospitals and health systems continue to improve the patient experience, it can be more challenging to identify specific initiatives to drive improvement. Press Ganey’s advanced analytics help health care leaders spark new initiatives by viewing opportunities through a new lens. Sophisticated techniques, such as segmentation, text analysis, multi-dimensional modeling and cluster analysis, evaluate multiple dimensions to uncover relationships, patterns and new insights to reveal targeted opportunities to improve
Malcolm McRoberts

Online Data Science Master's Degrees | Data Analytics & IT | UMUC - 0 views

  • The Master of Science in Data Analytics is designed to help you learn to manipulate data for insights that drive decisions. The Master of Science in Information Technology with a Database Systems Technology specialization focuses on developing the IT solutions that support an organization's data needs—big or small.
  • Learn online any time as you balance your job, family, and education.
Malcolm McRoberts

Online analytical processing - Wikipedia, the free encyclopedia - 0 views

  • The usual interface to manipulate an OLAP cube is a matrix interface like Pivot tables
  • MOLAP stores this data in an optimized multi-dimensional array storage, rather than in a relational database
  • The problem of deciding which aggregations (views) to calculate is known as the view selection problem. View selection can be constrained by the total size of the selected set of aggregations, the time to update them from changes in the base data, or both. The objective of view selection is typically to minimize the average time to answer OLAP queries, although some studies also minimize the update time
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  • Comparison[edit source | editbeta] Each type has certain benefits, although there is disagreement about the specifics of the benefits between providers. Some MOLAP implementations are prone to database explosion, a phenomenon causing vast amounts of storage space to be used by MOLAP databases when certain common conditions are met: high number of dimensions, pre-calculated results and sparse multidimensional data. MOLAP generally delivers better performance due to specialized indexing and storage optimizations. MOLAP also needs less storage space compared to ROLAP because the specialized storage typically includes compression techniques.[15] ROLAP is generally more scalable.[15] However, large volume pre-processing is difficult to implement efficiently so it is frequently skipped. ROLAP query performance can therefore suffer tremendously. Since ROLAP relies more on the database to perform calculations, it has more limitations in the specialized functions it can use. HOLAP encompasses a range of solutions that attempt to mix the best of ROLAP and MOLAP. It can generally pre-process swiftly, scale well, and offer good function support.
Malcolm McRoberts

Integrating R with Cloudera Impala for Real-Time Queries on Hadoop | BigHadoop - 0 views

  • R is one of the most popular open source statistical computing and graphical software. It can work with various data sources from comma separated files to web contents referred by URLs to relational databases to NoSQL (e.g. MongoDB or Cassandra) and Hadoop.
Malcolm McRoberts

How-to: Do Statistical Analysis with Impala and R | Cloudera Developer Blog - 0 views

  • To meet that goal, we have created a new R package, RImpala, which connects Impala to R. RImpala enables querying the data residing in HDFS and Apache HBase from R, which can be further processed as an R object using R functions. RImpala is now available for download from the Comprehensive R Archive Network (CRAN) under GNU General Public License (GPL3).
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