data analytics

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By: IBM     Published Date: Apr 19, 2018
This paper presents a cost/benefit case for two industry-leading database platforms for analytics workloads.
Tags : db2, data migration, ibm, oracle
     IBM
By: IBM     Published Date: Apr 19, 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, data migration, ibm, oracle
     IBM
By: Pure Storage     Published Date: Apr 18, 2018
Deep learning opens up new worlds of possibility in artifi cial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Advanced AI applications require a modern all-fl ash storage infrastructure that is built specifically to work with high-powered analytics.
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     Pure Storage
By: Pure Storage     Published Date: Apr 18, 2018
In today’s world, it’s critical to have infrastructure that supports both massive data ingest and rapid analytics evolution. At Pure Storage, we built the ultimate data hub for AI, engineered to accelerate every stage of the data pipeline. Download this infographic for more information.
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     Pure Storage
By: Pure Storage     Published Date: Apr 18, 2018
Data is the fuel driving rapid innovation powered by artifi cial intelligence. Enterprises need modern data platform purpose-built for machine learning, accelerating insight while simplifying complex data pipelines in analytics.
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     Pure Storage
By: CrowdTwist     Published Date: Apr 16, 2018
In order for brands to compete and provide the level of personalization consumers have already come to expect, marketers need to work quickly to develop competencies around their abilities to collect contextual and anticipatory insight and meet customers in the moments that matter most to them. Now is the time for marketers to invest in technology that supports data capture, segmentation, predictive analytics, and machine learning. With these capabilities in place, brands should be on track to build rich first party profiles of customers across all channels and maximize customer lifetime value by creating relevant experiences at all stages of the customer lifecycle.
Tags : customers, predictive, branding, consumers, competition, lifecycle
     CrowdTwist
By: Amazon Web Services     Published Date: Apr 16, 2018
Since SAP introduced its in-memory database, SAP HANA, customers have significantly accelerated everything from their core business operations to big data analytics. But capitalizing on SAP HANA’s full potential requires computational power and memory capacity beyond the capabilities of many existing data center platforms. To ensure that deployments in the AWS Cloud could meet the most stringent SAP HANA demands, AWS collaborated with SAP and Intel to deliver the Amazon EC2 X1 and X1e instances, part of the Amazon EC2 Memory-Optimized instance family. With four Intel® Xeon® E7 8880 v3 processors (which can power 128 virtual CPUs), X1 offers more memory than any other SAP-certified cloud native instance available today.
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     Amazon Web Services
By: Dell EMC & Intel     Published Date: Apr 13, 2018
Your company is collecting more data than ever before; your customers’ pain points, habits, and desires all flow in and out of your business each second. To mine the most value from that data, and to get the answers you need at a competitive speed, you need to employ server solutions powerful enough to handle complex analytics software. In the Principled Technologies datacenter, we compared a legacy Dell EMC™ PowerEdge™ R720xd powered by Intel® Xeon® Platinum processor’ to the new PowerEdge R740xd (powered by Intel® Xeon® Scalable processors) in three storage configurations: with basic hard drives, with SATA SSDs, and with NVMe SSDs. Intel Inside®. New Possibilities Outside.
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     Dell EMC & Intel
By: Dell EMC & Intel     Published Date: Apr 13, 2018
Your company is collecting more data than ever before; your customers’ pain points, habits, and desires all flow in and out of your business each second. To mine the most value from that data, and to get the answers you need at a competitive speed, you need to employ server solutions powerful enough to handle complex analytics software. In the Principled Technologies datacenter, we compared a legacy Dell EMC™ PowerEdge™ R720xd powered by Intel® Xeon® Platinum processor’ to the new PowerEdge R740xd (powered by Intel® Xeon® Scalable processors) in three storage configurations: with basic hard drives, with SATA SSDs, and with NVMe SSDs. Intel Inside®. New Possibilities Outside.
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     Dell EMC & Intel
By: Microsoft Azure     Published Date: Apr 11, 2018
Developing for and in the cloud has never been more dependent on data. Flexibility, performance, security—your applications need a database architecture that matches the innovation of your ideas. Industry analyst Ovum explored how Azure Cosmos DB is positioned to be the flagship database of internet-based products and services, and concluded that Azure Cosmos DB “is the first to open up [cloud] architecture to data that is not restricted by any specific schema, and it is among the most flexible when it comes to specifying consistency.” From security and fraud detection to consumer and industrial IoT, to personalized e-commerce and social and gaming networks, to smart utilities and advanced analytics, Azure Cosmos DB is how Microsoft is structuring the database for the age of cloud. Read the full report to learn how a globally distributed, multi-model data service can support your business objectives. Fill out the short form above to download the free research paper.
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     Microsoft Azure
By: SAS     Published Date: Apr 04, 2018
Location analytics is the process of integrating geographical data into business intelligence (BI) and analytics-led decision making. Location analytics creates meaningful insight from relationships found in geospatial data to solve a broad variety of business and social problems. Location data is found everywhere – with an item or a device, in a conversation or behavior, in machines or sensors, tied to a customer or competitor, attached to a database record or recorded from vehicles or other moving objects. Organizations want to take advantage of location data to improve decisions, create better customer engagement and experiences, reduce risks and automate business processes.
Tags : 
     SAS
By: SAS     Published Date: Apr 04, 2018
Opioid use grabs headlines when important celebrities overdose. Prince is sadly the most recent. But the problem is persistent and pervasive. The marginally good news is that the number of opioid prescriptions written started to decline last year. Overdose deaths, however, continued to rise. Also in the news have been lawsuits against pharmaceutical companies and distributors for helping to create the astounding oversupply of opioids, but the root causes go deeper. Physicians and their patients, medical policy makers and licensing boards, pharma companies and pharmacies all have played roles. And all must work together to stem the opioid epidemic and achieve the fundamental objectives of reducing addiction and deaths.
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     SAS
By: F5 Networks Inc     Published Date: Mar 30, 2018
It seems like every day there’s another article about IoT, big data analytics, and cloud architectures—and their unlimited potential for companies trying to gain a competitive edge in this digital world. If your business is in the midst of a digital transformation (and chances are, it is), you’re probably already enjoying some the benefits of the public cloud: economies of scale, preconfigured solutions that can be spun up with a few clicks, utility billing, and more. What you may not have heard, however, is how the shared security model of the public cloud affects your security responsibilities —and how it can be used to your advantage in these multicloud environments.
Tags : roi, cloud, security, architectures, business, economies
     F5 Networks Inc
By: IBM Watson Health     Published Date: Mar 30, 2018
Chilmark Research, a global research and advisory firm, recently released a report rating vendors and solutions in the healthcare analytics industry. IBM Watson Health, a leader in healthcare analytics, has put together this infographic comparing how its solutions stack up against some of the closest competitors in the industry in areas such as population discovery and definition, predictive analytics, cost and utilization, and claims data contribution.
Tags : analytics, infographic, predictive analytics, cost utilization, population discovery, claims data, healthcare, chilmark, strategy, healthcare analytics
     IBM Watson Health
By: IBM APAC     Published Date: Mar 19, 2018
MongoDB, one of the most popular NoSQL Open databases, helps you take advantage of exploding unstructured data with faster access to data and analytics while reducing your database cost. With the right infrastructure, you can benefit more. By running MongoDB on IBM Power systems, you can achieve: • ?Bring new apps to market faster and reduce the risk for mission-critical deployments • ?2.6x better performance for MongoDB at a much lesser cost than x86 Find out more about IBM Power Systems and MongoDB for today’s applications.
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     IBM APAC
By: Dell EMC & Intel     Published Date: Mar 16, 2018
Your company is collecting more data than ever before; your customers’ pain points, habits, and desires all flow in and out of your business each second. To mine the most value from that data, and to get the answers you need at a competitive speed, you need to employ server solutions powerful enough to handle complex analytics software. In the Principled Technologies datacenter, we compared a legacy Dell EMC™ PowerEdge™ R720xd to the new PowerEdge R740xd (powered by Intel® Xeon® Scalable processors) in three storage configurations: with basic hard drives, with SATA SSDs, and with NVMe SSDs. Intel Inside®. New Possibilities Outside.
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     Dell EMC & Intel
By: Insight Software     Published Date: Mar 14, 2018
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Tags : kpi, business, data, analytics, metrics, hubble
     Insight Software
By: BlueData     Published Date: Mar 13, 2018
In a benchmark study, Intel compared the performance of Big Data workloads running on a bare-metal deployment versus running in Docker containers with the BlueData software platform. This landmark benchmark study used unmodified Apache Hadoop* workloads
Tags : big data, big data analytics, hadoop, apache spark, docker
     BlueData
By: Avi Networks     Published Date: Mar 07, 2018
"Maximizing Operational Efficiency and Application Performance in VMware-Based Data Center Some of the most common challenges in VMware-based virtual data center environments include: - Lack of visibility into applications and end-user experience - Complex and error-prone operations - High capital and operational costs Review our solution brief to learn how the Avi Controller, the industry’s first solution that integrates application delivery with real-time analytics, is able to solve these challenges."
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     Avi Networks
By: SAS     Published Date: Mar 06, 2018
With decisions riding on the timeliness and quality of analytics, business stakeholders are less patient with delays in the development of new applications that provide reports, analysis, and access to diverse data itself. Executives, managers, and frontline personnel fear that decisions based on old and incomplete data or formulated using slow, outmoded, and limited reporting functionality will be bad decisions. A deficient information supply chain hinders quick responses to shifting situations and increases exposure to financial and regulatory risk—putting a business at a competitive disadvantage. Stakeholders are demanding better access to data, faster development of business intelligence (BI) and analytics applications, and agile solutions in sync with requirements.
Tags : 
     SAS
By: SAS     Published Date: Mar 06, 2018
Better health care at lower costs, for everyone – how do health care providers get there? Understanding the gaps in patient care, patient needs, and the geographic distribution of the patient population are important elements to consider when making decisions about improving the quality of care and reducing its costs. To effectively analyze gaps in patient care, the data needs to be in a single place or system. However, in many organizations, data is spread across a myriad of spreadsheets and database systems. Data not organized for visual exploration and coherent analysis isn’t useful for decision making. Hence the need for visually appealing and scalable analytical tools to help organizations be more efficient, effective and economically successful.
Tags : 
     SAS
By: SAS     Published Date: Mar 06, 2018
Location data is found everywhere – with an item or a device, in a conversation or behavior, in machines or sensors, tied to a customer or competitor, attached to a database record or recorded from vehicles or other moving objects. Organizations want to take advantage of location data to improve decisions, create better customer engagement and experiences, reduce risks and automate business processes.
Tags : 
     SAS
By: SAS     Published Date: Mar 06, 2018
Known for its industry-leading analytics, data management and business intelligence solutions, SAS is focused on helping organizations use data and analytics to make better decisions, faster. The combination of self-service BI and analytics positions you for improved productivity and smarter business decisions. So you can become more competitive as you use all your data to take better actions. Instead of depending on hunch-based choices, you can make decisions that are truly rooted in discovery and analytics. And you can do it through an interface that anyone can use. At last, your business users can get close enough to the data to manipulate it and draw their own reliable, fact-based conclusions. And they can do it in seconds or minutes, not hours or days. Equally important, IT remains in control of data access and security by providing trusted data sets and defined processes that promote the valuable, user-generated content for reuse and consistency. But, they are no longer forced
Tags : 
     SAS
By: SAS     Published Date: Mar 06, 2018
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics, and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. With the right end-user tools, a data lake can enable the self-service data practices that both technical and business users need. These practices wring business value from big data, other new data sources, and burgeoning enterprise da
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     SAS
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