data analytics

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By: IBM     Published Date: Jun 05, 2014
Whether in high-performance computing, Big Data or analytics, information technology has become an essential tool in today’s hyper-competitive business landscape. Organizations are increasingly being challenged to do more with less and this is fundamentally impacting the way that IT infrastructure is deployed and managed. In this short e-book, learn the top ten ways that IBM Platform Computing customers are using technologies like IBM Platform LSF and IBM Platform Symphony to help obtain results faster, share resources more efficiently, and improve the overall cost-effectiveness of their global IT infrastructure.
Tags : ibm
     IBM
By: IBM     Published Date: Sep 16, 2015
According to our global study of more than 800 cloud decision makers and users are becoming increasingly focused on the business value cloud provides. Cloud is integral to mobile, social and analytics initiatives – and the big data management challenge that often comes with them and it helps power the entire suite of game-changing technologies. Enterprises can aim higher when these deployments are riding on the cloud. Mobile, analytics and social implementations can be bigger, bolder and drive greater impact when backed by scalable infrastructure. In addition to scale, cloud can provide integration, gluing the individual technologies into more cohesive solutions. Learn how companies are gaining a competitive advanatge with cloud computing.
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     IBM
By: IBM     Published Date: Sep 16, 2015
Are you trying to support more variable workloads than your environment can handle? Can you benefit from a high performance cluster, but do not have the budget or resources to deploy and manage technical computing infrastructure? Are you running out of data center space but still need to grow your compute capacity? If you want answers to any of these questions, then please join us for an informative webinar describing the advantages and pitfalls of relocating a high performance workload to the cloud. View this webinar to learn: - Why general purpose clouds are insufficient for technical computing analytics and Hadoop workloads; - How high performance clouds can improve your profitability and give you a competitive edge; - How to ensure that your cloud environment is secure; - How to evaluate which applications are suitable for a hybrid or public cloud environment; - How to get started and choose a service provider.
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     IBM
By: IBM     Published Date: May 20, 2015
Whether in high-performance computing, Big Data or analytics, information technology has become an essential tool in today’s hyper-competitive business landscape. Organizations are increasingly being challenged to do more with less and this is fundamentally impacting the way that IT infrastructure is deployed and managed. In this short e-book, learn the top ten ways that IBM Platform Computing customers are using technologies like IBM Platform LSF and IBM Platform Symphony to help obtain results faster, share resources more efficiently, and improve the overall cost-effectiveness of their global IT infrastructure.
Tags : 
     IBM
By: IBM     Published Date: May 20, 2015
Are you trying to support more variable workloads than your environment can handle? Can you benefit from a high performance cluster, but do not have the budget or resources to deploy and manage technical computing infrastructure? Are you running out of data center space but still need to grow your compute capacity? If you want answers to any of these questions, then please join us for an informative webinar describing the advantages and pitfalls of relocating a high performance workload to the cloud. View this webinar to learn: - Why general purpose clouds are insufficient for technical computing analytics and Hadoop workloads; - How high performance clouds can improve your profitability and give you a competitive edge; - How to ensure that your cloud environment is secure; - How to evaluate which applications are suitable for a hybrid or public cloud environment; - How to get started and choose a service provider.
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     IBM
By: Adaptive Computing     Published Date: Feb 21, 2014
Big data applications represent a fast-growing category of high-value applications that are increasingly employed by business and technical computing users. However, they have exposed an inconvenient dichotomy in the way resources are utilized in data centers. Conventional enterprise and web-based applications can be executed efficiently in virtualized server environments, where resource management and scheduling is generally confined to a single server. By contrast, data-intensive analytics and technical simulations demand large aggregated resources, necessitating intelligent scheduling and resource management that spans a computer cluster, cloud, or entire data center. Although these tools exist in isolation, they are not available in a general-purpose framework that allows them to inter operate easily and automatically within existing IT infrastructure.
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     Adaptive Computing
By: Data Direct Networks     Published Date: Dec 31, 2015
Parallelism and direct memory access enable faster and more accurate SAS analytics using Remote Direct Memory Access based analytics and fast, scalable,external disk systems with massively parallel access to data, SAS analytics driven organizations can deliver timely and accurate execution for data intensive workfl ows such as risk management, while incorporating larger datasets than using traditional NAS.
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     Data Direct Networks
By: BitStew     Published Date: Jun 23, 2016
If we examine the root cause of the IT organization’s pain, it continues to be the inability to integrate data from many disparate and operationally focused systems. A recent survey found that only 18% of the respondents had extensively integrated their analytics initiatives across operations and realized their objectives, which pointed to the diversity of datasets and formats and poor data quality. Indeed, data integration is causing the analytics burden to be placed on IT professionals. Download the white paper to learn more.
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     BitStew
By: Aberdeen     Published Date: Jun 17, 2011
Download this paper to learn the top strategies leading executives are using to take full advantage of the insight they receive from their business intelligence (BI) systems - and turn that insight into a competitive weapon.
Tags : aberdeen, michael lock, data-driven decisions, business intelligence, public sector, analytics, federal, state
     Aberdeen
By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
As organizations develop next-generation applications for the digital era, many are using cognitive computing ushered in by IBM Watson® technology. Cognitive applications can learn and react to customer preferences, and then use that information to support capabilities such as confidence-weighted outcomes with data transparency, systematic learning and natural language processing. To make the most of these next-generation applications, you need a next-generation database. It must handle a massive volume of data while delivering high performance to support real-time analytics. At the same time, it must provide data availability for demanding applications, scalability for growth and flexibility for responding to changes.
Tags : database, applications, data availability, cognitive applications
     Group M_IBM Q1'18
By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
For increasing numbers of organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements. To accelerate innovation, improve the IT delivery economic model and reduce risk, organizations need to combine data and experience in a cognitive model that yields deeper and more meaningful insights for smarter decisionmaking. Whether the user needs a data set maintained in house for customer analytics or access to a cloud-based data store for assessing marketing program results — or any other business need — a high-performance, highly available, mixed-load database platform is required.
Tags : cloud, database, hybrid cloud, database platform
     Group M_IBM Q1'18
By: IBM     Published Date: Oct 17, 2017
The data quality tools market continues to show strong revenue growth, driven by cost, process optimization and digital business initiatives. Applying data quality tools to existing and emerging business scenarios will enable data and analytics leaders to deliver greater business value.
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     IBM
By: IBM     Published Date: Nov 08, 2017
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
Tags : ibm, cloud, cloud computing, database, ibm db2
     IBM
By: IBM     Published Date: Nov 08, 2017
In this paper, you'll learn how organizations are adopting increasingly sophisticated analytics methods, that analytics usage trends are placing new demands on rigid data warehouses, and what's needed is hybrid data warehouse architecture that supports all deployment models.
Tags : data warehouse, analytics, ibm, deployment models
     IBM
By: Group M_IBM Q1'18     Published Date: Jan 23, 2018
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
Tags : db2. blu accelaration, big data, data analytics, disaster recovery
     Group M_IBM Q1'18
By: Group M_IBM Q1'18     Published Date: Jan 23, 2018
In this paper, you'll learn how organizations are adopting increasingly sophisticated analytics methods, that analytics usage trends are placing new demands on rigid data warehouses, and what's needed is hybrid data warehouse architecture that supports all deployment models.
Tags : data warehouse, analytics, hybrid data warehouse, development model
     Group M_IBM Q1'18
By: Snowflake     Published Date: Jan 25, 2018
To thrive in today’s world of data, knowing how to manage and derive value from of semi-structured data like JSON is crucial to delivering valuable insight to your organization. One of the key differentiators in Snowflake is the ability to natively ingest semi-structured data such as JSON, store it efficiently and then access it quickly using simple extensions to standard SQL. This eBook will give you a modern approach to produce analytics from JSON data using SQL, easily and affordably.
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     Snowflake
By: OpenText     Published Date: Jan 31, 2018
Read this white paper to learn how to minimize, consolidate, and protect your data and how data identification and analytics play a key role in overcoming GDPR compliance concerns.
Tags : opentext, gdpr, gdpr compliance, data protection, data identification
     OpenText
By: Mindfire     Published Date: May 07, 2010
In this report, results from well over 650 real-life cross-media marketing campaigns across 27 vertical markets are analyzed and compared to industry benchmarks for response rates of static direct mail campaigns, to provide a solid base of actual performance data and information.
Tags : mindfire, response rates, personalized cross-media, marketing campaign, personalization, personalized urls, purls, performance data
     Mindfire
By: Cisco EMEA Tier 3 ABM     Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
Tags : big data, analytics, virtualization, cloudera, ibm, sas, sap, splunk
     Cisco EMEA Tier 3 ABM
By: SAP     Published Date: May 18, 2014
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
     SAP
By: SAP     Published Date: May 18, 2014
Download this whitepaper to learn the results of this latest exploration of the emerging world of in-memory database technologies.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
     SAP
By: SAP     Published Date: May 18, 2014
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
     SAP
By: SAP     Published Date: May 18, 2014
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
     SAP
By: SAP     Published Date: May 18, 2014
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
     SAP
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