The Internet of Things (IoT) unleashes valuable business insights through data that’s gathered at every level of a retail organization. With IoT and data analytics, retailers now have the capability to gather insight into customer behavior, offer more personalized experiences, achieve better inventory accuracy, create greater supply chain efficiencies, and so much more. But with data comes great risk. A recent report by security firm Thales and 451 Research found that 43 percent of retailers have experienced a data breach in the past year, with a third reporting more than one breach.1
Intel® technology-based gateways and Asavie, a provider of next-gen enterprise mobility management and IoT connectivity solutions, offer a security connectivity solution that minimizes the effort and cost to businesses to ensure safety from cybersecurity attacks. In addition, the Intel/Asavie IoT solution provides retailers with a solid basis to build their smart, connected projects:
However, big data and analytics solutions can have shortcomings. Proprietary and best-of-breed approaches can require valuable time and resources to build, integrate and maintain — while outsourcing data analytics can constrain reporting frequency and timeliness. In a world where operational efficiency and fast, reliable information is paramount, these limitations can put payers at a competitive disadvantage.
To better understand the benefits, costs, and risks associated with implementation of SAP Business Objects Analytics solutions, Forrester interviewed four organizations with multiple years of experience using these analytics solutions from SAP across one or more of the following key analytics areas: planning, business intelligence, and predictive analytics. A composite, or representative, organization was developed to provide the conclusions of this cost and benefit analysis.
To better understand the benefits, costs, and risks associated with implementation of SAP BusinessObjects Analytics solutions, Forrester interviewed four organizations with multiple years of experience using these analytics solutions from SAP across one or more of the following key analytics areas: planning, business intelligence, and predictive analytics. A composite, or representative, organization was developed to report cost and benefit findings
Today’s organizations are becoming more innovative and dynamic by adopting mobility, IoT, analytics and cloud technologies. With this, come growing demands for network scale, agility and threat protection which call for an intent-based network. The Cisco® Digital Network Architecture (Cisco DNA) gives you comprehensive intent-based networking across your campus, branch and WAN with robust wired, wireless, and routing solutions.
The Industrial Internet of Things (IIoT) is flooding today’s industrial sector with data. Information is streaming in from many sources — equipment on production lines, sensors at customer facilities, sales data, and much more. Harvesting insights means filtering out the noise to arrive at actionable intelligence.
This report shows how to craft a strategy to gain a competitive edge. It explains how to evaluate IIoT solutions, including what to look for in end-to-end analytics solutions. Finally, it shows how SAS has combined its analytics expertise with Intel’s leadership in IIoT information architecture to create solutions that turn raw data into valuable insights.
Insurers have long been plagued by fraud, error, waste, and abuse in health care payments. The costs are huge – amounting to as much as 25 percent of payments made. Today’s data management and
analytics platforms promise breakthroughs by incorporating comparative and behavioral data to predict as well as detect loss in all its forms. To explore the opportunities and how insurers can capitalize on them, IIA spoke with Ben Wright, Sr. Solutions Architect in SAS’s Security Intelligence Global Practice.
Published By: LogMeIn
Published Date: Mar 19, 2015
Remote support technology, including remote control, desktop sharing, and web collaboration, is one of the most popular platforms used across TSIA service disciplines. Today’s remote support solutions offer much more than just remote control for PCs, their functional footprint is expanding to include support for more devices and richer analytics for trend analysis and supervisor dashboards. Remote support solutions are typically well regarded by users, consistently delivering one of the highest average satisfaction scores in TSIA’s annual Global Technology Survey. Service executives should acquaint themselves with the new features and capabilities being introduced by leading remote support platforms and find ways to leverage the capabilities beyond technical support. Field services, education services, professional services, and managed services are all increasing adoption of these tools to boost productivity and avoid on-site visits. Download this white paper to learn more.
Healthcare and Life Sciences organizations are using data to generate knowledge that helps them provide better patient care, enhances biopharma research and development, and streamlines operations across the product innovation and care delivery continuum. Next-Gen business intelligence (BI) solutions can help organizations reduce time-to-insight by aggregating and analyzing structured and unstructured data sets in real or near-real time.
AWS and AWS Partner Network (APN) Partners offer technology solutions to help you gain data-driven insights to improve care, fuel innovation, and enhance business performance.
In this webinar, you’ll hear from APN Partners Deloitte and hc1.com about their solutions, built on AWS, that enable Next-Gen BI in Healthcare and Life Sciences.
Join this webinar to learn:
How Healthcare and Life Sciences organizations are using cloud-based analytics to fuel innovation in patient care and biopharmaceutical product development.
How AWS supports BI solutions f
IT leaders working on customer service projects must display an incredible amount of diligence. An organization’s CRM system has become its lifeline to customers, but as customer needs evolve so has the requirements of CRM. According to Gartner, today’s CRM solution must include a laundry list of capabilities outside its traditional core functionality including: native mobile support of the vendor's customer service and support business applications; real-time analytics; industry-specific functionality and workflow; context mining of voice and text; scalable cloud-based systems; social media engagement; suggested next agent action; multimodal capabilities, such as chat within mobile self-service; and even co-browsing. Gartner surveyed the CRM field and evaluated each vendor including Pegasystems.
Download this Gartner Magic Quadrant analysis and gain a better understanding each vendors’ CRM Customer Engagement Center solutions.
Marketing leaders rely on analytics teams to deliver better measurement,
insights and optimization. Use this research to evaluate your organization's
current analytics tools and identify new solutions aligned to your goals.
Adobe is the only Leader in Digital Intelligence Platforms.
Digital intelligence with scope and depth. Your customers come to you from different places, so your data insights should do the same thing. Adobe Experience Cloud’s digital marking and analytics solutions help you combine insights from existing, new, and emerging channels. Read the Forrester Wave™: Digital Intelligence Platforms, Q2 2017 to find out why we stand alone among DI platform vendors.
Published By: Oracle CX
Published Date: Oct 19, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make better
Published By: Oracle CX
Published Date: Oct 19, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business,
mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and
enough compute power to deliver the performance required in a rapidly evolving digital marketplace.
Customers increasingly drive the speed of business, and organizations need to engage with customers
on their terms. The need to manage sensitive information with high levels of security as well as
capture, analyze, and act upon massive volumes of data every hour of every day has become critical.
These challenges will dramatically change the way that IT systems are designed, funded, and run
compared to the past few decades. Databases and Java have become the de facto language in which
modern, cloud-ready applications are written. The massive explosion in the volume, variety, and
velocity of data increases the need for secure and effective analytics so that organizations can make
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.
The Internet of Things (IoT) didn’t just connect everything everywhere; It laid the groundwork for the next industrial revolution.
Connected devices sending data was only one achievement of the IoT—but one that helped solve the problem of data spread across countless silos that was not collected because it was too voluminous and/or too expensive to analyze.
Now, with advances in cloud computing and analytics, cheaper and more scalable factory solutions are available. This, in combination with the cost and size of sensors continuously being reduced, supplies the other achievement: the possibility for every organization to digitally transform.
Using a Smart Factory system, all relevant data is aggregated, analyzed, and acted upon. Sensors, devices, people, and processes are part of a connected ecosystem providing:
• Reduced downtime
• Minimized surplus and defects • Deep insights
• End-to-end real-time visibility
Published By: IBM APAC
Published Date: Jun 07, 2017
This Total Economic Impact (TEI) analysis has been prepared exclusively for you based on your inputs. The analysis provides a high-level estimate of the impact of implementing IBM customer behavior analytics solutions.
The more you know about your people, the more you can enable them to do their best work. And in turn, the greater the chance of business success. Yet, a rapidly changing world of work makes it difficult for companies to achieve this. There is a growing global skills crisis, and it’s getting worse. A shortage of skilled people makes it tough to find and attract the people you need — and it’s even tougher to get them through the door once you find them. To win the war for talent, you need to understand and engage with your candidates better than ever before.
SecureWorks provides an early warning system for evolving cyber threats, enabling organisations to prevent, detect, rapidly respond to and predict cyber attacks. Combining unparalleled visibility into the global threat landscape and powered by the Counter Threat Platform — our advanced data analytics and insights engine —SecureWorks minimises risk and delivers actionable, intelligence driven security solutions for clients around the world.
"With the introduction of Oracle Database In-Memory and servers with the SPARC S7 and SPARC M7 processors Oracle delivers an architecture where analytics are run on live operational databases and not on data subsets in data warehouses. Decision-making is much faster and more accurate because the data is not a stale subset. And for those moving enterprise applications to the cloud, Real-time analytics of the SPARC S7 and SPARC M7 processors are available both in a private cloud on SPARC servers or in Oracle’s Public cloud in the SPARC cloud compute service.
Moving to the Oracle Public Cloud does not compromise the benefits of SPARC solutions. Some examples of utilizing real time data for business decisions include: analysis of supply chain data for order fulfillment and supply optimization, analysis of customer purchase history for real time recommendations to customers using online purchasing systems, etc.
Data is growing at amazing rates and will continue this rapid rate of growth. New techniques in data processing and analytics including AI, machine and deep learning allow specially designed applications to not only analyze data but learn from the analysis and make predictions.
Computer systems consisting of multi-core CPUs or GPUs using parallel processing and extremely fast networks are required to process the data. However, legacy storage solutions are based on architectures that are decades old, un-scalable and not well suited for the massive concurrency required by machine learning. Legacy storage is becoming a bottleneck in processing big data and a new storage technology is needed to meet data analytics performance needs.
Published By: Teradata
Published Date: Jan 30, 2015
Big Data analytics are a top priority at many companies today. Most hope to derive new insights from all available data to improve productivity, cut costs, reduce churn, enhance the customer experience, and seize new business opportunities.
Published By: Teradata
Published Date: Jan 30, 2015
This report is about two of those architectures: Apache™ Hadoop® YARN and Teradata® Aster® Seamless Network Analytical Processing (SNAP) Framework™. In the report, each architecture is described; the use of each in a business problem is illustrated; and the results are compared.
Published By: Teradata
Published Date: Jan 30, 2015
It is hard for data and IT architects to understand what workloads should move, how to coordinate data movement and processing between systems, and how to integrate those systems to provide a broader and more flexible data platform. To better understand these topics, it is helpful to first understand what Hadoop and data warehouses were designed for and what uses were not originally intended as part of the design.
Workforce analytics solutions are the key to answering such questions and getting the metrics and insights needed to make informed HR decisions and create actionable workforce plans. This paper explores the business case for investing in workforce analytics. It focuses on how cloud-based solutions hide complexity associated with HR data, as well as deliver best practices, minimize maintenance costs, and provide quick time to value.