data science

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By: IBM     Published Date: Sep 02, 2014
Learn how GPFS accelerates data intensive work flows and lowers storage costs in Life Sciences, Energy Exploration, Government, Media & Entertainment and Financial Services by removing data related bottlenecks, simplifying data management at scale, empowering global collaboration, managing the full data life cycle cost effectively and ensuring end-to-end data availability, reliability, and integrity.
Tags : ibm, complete storage solution, gpfs
     IBM
By: IBM     Published Date: Sep 02, 2014
Whether engaged in genome sequencing, drug design, product analysis or risk management, life sciences research needs high-performance technical environments with the ability to process massive amounts of data and support increasingly sophisticated simulations and analyses. Learn how IBM solutions such as IBM® Platform Computing™ high-performance cluster, grid and high-performance computing (HPC) cloud management software can help life sciences organizations transform and integrate their compute environments to develop products better, faster and at less expense.
Tags : ibm, life sciences, platform computing
     IBM
By: Bull     Published Date: Dec 04, 2014
Bull, an Atos company, is a leader in Big Data, HPC and cyber-security with a worldwide market presence. Bull has extensive experience in implementing and running petaflopsscale supercomputers. The exascale program is a new step forward in Bull’s strategy to deliver exascale supercomputers capable of addressing the new challenges of science, industry and society.
Tags : bull, exascale, big data, hpc, cyber security, supercomputers
     Bull
By: General Atomics     Published Date: Jan 13, 2015
The term “Big Data” has become virtually synonymous with “schema on read” (where data is applied to a plan or schema as it is ingested or pulled out of a stored location) unstructured data analysis and handling techniques like Hadoop. These “schema on read” techniques have been most famously exploited on relatively ephemeral human-readable data like retail trends, twitter sentiment, social network mining, log files, etc. But what if you have unstructured data that, on its own, is hugely valuable, enduring, and created at great expense? Data that may not immediately be human readable or indexable on search? Exactly the kind of data most commonly created and analyzed in science and HPC. Research institutions are awash with such data from large-scale experiments and extreme-scale computing that is used for high-consequence
Tags : general atomics, big data, metadata, nirvana
     General Atomics
By: IBM     Published Date: Apr 07, 2017
Data science platforms are engines for creating machine-learning solutions. Innovation in this market focuses on cloud, Apache Spark, automation, collaboration and artificial-intelligence capabilities. We evaluate 16 vendors to help you make the best choice for your organization. This Magic Quadrant evaluates vendors of data science platforms. These are products that organizations use to build machine-learning solutions themselves, as opposed to outsourcing their creation or buying ready-made solutions.
Tags : data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations
     IBM
By: IBM     Published Date: May 12, 2017
In today’s world, the data is flowing from all directions: social media, phones, weather, location and sensor equipped devices, and more. Competing in this digital age requires the ability to analyze all of this data, and use it to drive decisions that mitigate risk, increase customer satisfaction and grow revenue. Using a combination of proprietary software and open source technology can give your data scientists and statisticians the analytical power they need to find and act on insights quickly. IBM® SPSS® Statistics provides all of the data analysis tools you need, and integrates with thousands of R extensions for maximum power and flexibility. In this next Data Science Central Webinar event, we will show how SPSS Statistics can help you keep up with the influx of new data and make faster, better business decisions without coding.
Tags : ibm, spss, data analysis, statistics, risk mitigation
     IBM
By: SAS     Published Date: Nov 04, 2015
In a panel discussion at the 12th annual SAS Health Analytics Executive Forum in May 2015, leaders from Dignity Health, Horizon Blue Cross Blue Shield of New Jersey, Janssen Pharmaceuticals and SAS shared what they have done to prove the value of analytics to their business leaders – and what has worked for them as they developed an analytic culture in their organizations and put analytic insights to work.
Tags : sas, healthcare, healthcare models, episode analytics, analytics, data management
     SAS
By: Intel     Published Date: Jun 07, 2017
Using the Integrated Analytics Hub, data analytics projects have already accounted for an estimated quarterly savings on marketing digital-media expenditures of approximately USD 170,000. Download this white paper to find out more.
Tags : intel, analytics, data, data analytics, data science
     Intel
By: Intel     Published Date: Jun 07, 2017
Intel's Bob Rogers, chief data scientist for big data solutions, sat down with Dan Magestro, research director at the international Institute of Analytics (IIA), to discuss the power of asking questions when assessing an organisation's analytics maturity. Read on to find out more.
Tags : intel, analytics, data, data analytics, data science
     Intel
By: Teradata     Published Date: Oct 15, 2012
Does your organization struggle to get new business insights from all data types with rapid exploration?
Tags : data scientists, analyst, statistician, quants, quantitative analyst, scientist, data science
     Teradata
By: Aberdeen Group     Published Date: Nov 13, 2015
Aberdeen’s Content Marketing survey revealed that while 95% of marketers are using or considering using a content marketing strategy, there are some distinct differences between those using content well and those just using content. The Best-in-Class are not only creating content at volume, they are taking a much more data-driven approach to their content marketing strategy — and it’s paying off. Find out how.
Tags : customer acquisition, marketing leads, marketing challenges, marketing messages, contact management, data science, demand generation, email marketing
     Aberdeen Group
By: Aberdeen Group     Published Date: Nov 13, 2015
Aberdeen’s research shows that 90% of Best-in-Class marketers report fueling lead generation efforts with content marketing. What do you need to know to follow this best practice of the Best-in-Class? That’s exactly what this Knowledge Brief is intended to uncover.
Tags : customer acquisition, marketing leads, marketing challenges, marketing messages, contact management, data science, demand generation, email marketing
     Aberdeen Group
By: Aberdeen Group     Published Date: Nov 23, 2015
This report examines the pressing need to break down data silos due to the damage they cause to analytical initiatives and user engagement. Read this report to find out more.
Tags : customer acquisition, marketing leads, marketing challenges, marketing messages, contact management, data science, demand generation, email marketing
     Aberdeen Group
By: Waterline Data & Research Partners     Published Date: May 18, 2015
Waterline Data automates the cataloging of data assets and provides an Amazon.com-like guided shopping approach to data discovery that is intended to take the guesswork out of targeting the right data.
Tags : waterline, big data, automation, cataloging, processing, analysis, assets, data science
     Waterline Data & Research Partners
By: Waterline Data & Research Partners     Published Date: May 18, 2015
In this report, Forrester Research recommends that application development and delivery (AD&D) professionals working on BI and big data initiatives get the best out of both by designing and integrating them in a flexible data platform.
Tags : waterline, big data, automation, cataloging, processing, analysis, assets, data science
     Waterline Data & Research Partners
By: Oracle HCM Cloud     Published Date: Jun 07, 2016
Leveraging analytics to drive business growth is top-of-mind for corporate (C-Suite) leaders, prompting HR executives to take a more strategic, data-driven approach to workforce management. Learn the art and science of combining workforce data, business data and IT expertise together to allow HR departments to make more effective and efficient decisions about people.
Tags : 
     Oracle HCM Cloud
By: IBM     Published Date: Jul 14, 2016
This video describes how data scientists, analysts and business users can save precious time by using a combination of SPSS and Spark to uncover and act on insights in big data.
Tags : ibm, data, analytics, predictive business, ibm spss, apache spark, coding, data science
     IBM
By: IBM     Published Date: Oct 21, 2016
The greatest challenge of the big data revolution is making sense of all the information generated by today's vast digital economy. It's well enough for an organization to collect every slice of data it can reach, but how does it extract value from this massive volume of information?
Tags : ibm, analytics, data science, data, big data, aps data, aps, enterprise applications
     IBM
By: IBM     Published Date: Oct 21, 2016
Between the Internet of Things, customer experience and loyalty programs, social network monitoring, connected enterprise systems and other information sources, today's organizations have access to more data than they ever had before-and frankly, more than they may know what to do with. The challenge is to not just understand that data, but actualize it and use it to recognize real business value. This ebook will walk you through a sample scenario with Albert, a data scientist who wants to put text analytics to work by using the Word2vec algorithm and other data science tools.
Tags : ibm, analytics, aps, aps data, open data science, data science, word2vec, enterprise applications
     IBM
By: IBM     Published Date: Jan 18, 2017
It's all well enough for an organization to collect every slice of data it can reach, but having more data doesn't mean you'll automatically get better insights. First, you have to figure out what you want from your data you have to find its value.
Tags : ibm, aps data, data science, open data science, analytics, enterprise applications
     IBM
By: IBM     Published Date: Jan 18, 2017
In the domain of data science, solving problems and answering questions through data analysis is standard practice. Data scientists experiment continuously by constructing models to predict outcomes or discover underlying patterns, with the goal of gaining new insights. But data scientists can only go so far without support.
Tags : ibm, analytics, aps data, open data science, data science, data engineers, enterprise applications
     IBM
By: IBM     Published Date: Jan 18, 2017
Data matters more than ever to business success. But value does not come from data alone. Rather, it comes from the insights enabled by data. No matter what your role is, or where you are in your data journey, you are looking for ways to drive innovation.
Tags : ibm, analytics, aps data, open data science, data science, apache spark, enterprise applications
     IBM
By: Teradata     Published Date: May 01, 2015
Creating value in your enterprise undoubtedly creates competitive advantage. Making sense of the data that is pouring into the data lake, accelerating the value of the data, and being able to manage that data effectively is a game-changer. Michael Lang explores how to achieve this success in “Data Preparation in the Hadoop Data Lake.” Enterprises experiencing success with data preparation acknowledge its three essential competencies: structuring, exploring, and transforming. Teradata Loom offers a new approach by enabling enterprises to get value from the data lake with an interactive method for preparing big data incrementally and iteratively. As the first complete data management solution for Hadoop, Teradata Loom enables enterprises to benefit from better and faster insights from a continuous data science workflow, improving productivity and business value. To learn more about how Teradata Loom can help improve productivity in the Hadoop Data Lake, download this report now.
Tags : data management, productivity, hadoop, interactive, enterprise, enterprise applications
     Teradata
By: xMatters     Published Date: Sep 22, 2014
When it comes to data breaches and service outages, it’s no longer a question of if but when. Governments worldwide increasingly have new laws, pending legislation, privacy regulations and “strong suggestions” for protecting sensitive information and taking action when breaches or service outages occur. Get the Complimentary White Paper and learn how you need to prepare for these new laws and more. The white paper examines current regional legislation and how you can implement communication best practices for maintaining transparency and trust in the face of consumer-facing service disruptions.
Tags : communication, best practices, data, breaches, enterprise, consumer, confidence, science
     xMatters
By: Oracle     Published Date: Jan 28, 2015
Traditional brick-and-mortar multi-channel retailers have online competitors ruled by data scientists who define retail as a data mining and optimization problem. John Bible, Senior Director of Retail Data Science and Insight at Oracle Retail discusses the science of pricing, and predictions for the role of science in retail over the next five years.
Tags : 
     Oracle
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