IT faces the challenge of consolidating, maintaining, and understanding complex configuration data and often this data is found in many different repositories. But there’s a better way to solve these challenges. The configuration management database (CMDB) consolidates disparate IT management systems into a single system of action. This ipaper provides you with the fundamentals to help ensure your configuration data management project with CMDB is a success.

The combination of the SAP HANA platform and Intel® Optane™ DC persistent memory means that enterprises now have new ways to approach data tiering and management. Downtime can be significantly reduced because SAP HANA doesn’t have to reload data back into main memory after a server reboot, and more data can remain in the “hot” tier of main memory, which increases the amount of data that can be analyzed at a time. See this new infographic for a quick summary. Intel® Optane™ DC persistent memory also benefits SAP HANA by providing a higher memory density than DRAM, in addition to being byte-addressable. Up to three terabytes of Intel® Optane™ DC persistent memory is available per CPU socket on systems configured with future Intel® Xeon® Gold processors and future Intel® Xeon® Platinum processors, which means that an eight-socket server can contain up to 24 terabytes of Intel® Optane™ DC persistent memory.

In this case study, a large enterprise with an increasing amount of off-site work from both work-related travel and a fast-growing remote workforce, is faced with a unique challenge to ensure their data security is scalable and impenetrable. Their data access policies rely on physical access management provided at the company offices and do not always provide off-site employees with the ability to complete work-critical tasks. Legacy security solutions only add burden to productivity, sometimes causing employees to ignore security protocols in order to simply complete their work. Upon evaluating security vendors for a frictionless solution, they selected BehavioSec for its enterprise-grade capabilities with on-premise deployment and integration with existing legacy risk management systems.

AA Ireland specializes in home, motor, and travel insurance and provides emergency rescue for people in their homes and on the road, attending to over 140,000 car break downs every year, 80% of which are fixed on-the-spot. “In each of the last five years, the industry lost a quarter billion in motor insurance," says Colm Carey, chief analytics officer. "So, there's a huge push for new data, models, ways to segment and pick profitable customer types—and get a lot more sophisticated. Our goal is to optimize pricing, understand the types of customers we're bringing, and the types we're trying to attract. We would like to tie that across the business. Marketing will run a campaign, trying to attract a lot of customers, but maybe they're not the right type. "We wanted to step away from industry standard software and go with something that was powerful and future-proof. In 2016, we had an opportunity to analyze all software. We chose the TIBCO® System of Insight with TIBCO BusinessWorks™ i

Today, you can improve product quality and gain better control of the entire manufacturing chain with data virtualization, machine learning, and advanced data analytics. With all relevant data aggregated, analyzed, and acted on, sensors, devices, people, and processes become part of a connected Smart Factory ecosystem providing: •? Increased uptime, reduced downtime •? Minimized surplus and defects •? Better yields •? Reduced cost due to better quality •? Fewer deviations and less non-conformance

Over the past decade there has been a major transformation in the manufacturing industry. Data has enabled a paradigm shift, with real-time IoT sensor data and machine learning algorithms delivering new insights for process and product optimization. Smart Manufacturing, also known as Industry 4.0, has laid the groundwork for the next industrial revolution. Using a smart factory system, all relevant data is aggregated, analyzed, and acted upon. We call this Manufacturing Intelligence, which gives decision-makers a competitive edge to: Digitize the business Optimize costs Accelerate innovation Survive digital disruption Watch this webinar to understand use cases and their underlying technology that helped our customers become smart manufacturers.

Big Data and analytics workloads represent a new frontier for organizations. Data is being collected from sources that did not exist 10 years ago. Mobile phone data, machine-generated data, and website interaction data are all being collected and analyzed. In addition, as IT budgets are already under pressure, Big Data footprints are getting larger and posing a huge storage challenge. This paper provides information on the issues that Big Data applications pose for storage systems and how choosing the correct storage infrastructure can streamline and consolidate Big Data and analytics applications without breaking the bank.

Continuous data availability is a key business continuity requirement for storage systems. It ensures protection against downtime in case of serious incidents or disasters and enables recovery to an operational state within a reasonably short period. To ensure continuous availability, storage solutions need to meet resiliency, recovery, and contingency requirements outlined by the organization.

Even after decades of industry and technology advancements, there still is no universal, integrated storage solution that can reduce risk, enable profitability, eliminate complexity and seamlessly integrate into the way businesses operate and manage data at scale? To reach these goals, there are capabilities that are required to achieve the optimum results at the lowest cost. These capabilities include availability, reliability, performance, density, manageability and application ecosystem integration? This paper outlines a better way to think about storing data at scale—solving these problems not only today, but well into the future?

Big Data- und Analytik-Workloads bringen für Unternehmen neue Herausforderungen mit sich. Die erfassten Daten stammen aus Quellen, die vor zehn Jahren noch gar nicht existierten. Es werden Daten von Mobiltelefonen, maschinengenerierte Daten und Daten aus Webseiten-Interaktionen erfasst und analysiert. In Zeiten knapper IT-Budgets wird die Lage zusätzlich dadurch verschärft, dass die Big Data-Volumen immer größer werden und zu enormen Speicherproblemen führen. Das vorliegende White Paper informiert über die Probleme, die Big Data-Anwendungen für Storage-Systeme mit sich bringen, sowie darüber, wie die Auswahl der richtigen Storage-Infrastruktur Big Data- und Analytik-Anwendungen optimieren kann, ohne das Budget zu sprengen.

Companies that are undergoing a technology-enabled business strategy such as digital transformation urgently need modern infrastructure solutions. The solutions should be capable of supporting extreme performance and scalability, uncompromised data-serving capabilities and pervasive security and encryption. According to IDC, IBM’s LinuxONE combines the advantages of both commercial (IBM Z) and opensource (Linux)systems with security capabilities unmatched by any other offering and scalability for systems-of-record workloads. The report also adds LinuxONE will be a good fit for enterprises as well as managed and cloud service provider firms. Read more about the benefits of LinuxONE in this IDC Whitepaper.

Organizations are embracing cloud-based solutions at an unprecedented rate. The transition to a cloud-first strategy is no longer viewed as a luxury but as a necessity for businesses to compete. According to a 2018 study, cloud computing will have the biggest impact on analytics initiatives, followed by big data, AI and machine learning, and IoT. Because today’s state-of-the-art solutions will likely be quickly outdated, organizations now want to invest in systems that can meet their changing needs. Attributes like flexibility and agility will allow these businesses to seamlessly tackle changing business requirements.

The use of analytics has exploded across business, and the value it already has delivered has heightened executives' expectations. Now data can be processed in real time to meet a constantly widening range of analytic needs. How your organization utilizes them in the next decade will be essential to your success. These developments come at an opportune time. Organizations are being over-whelmed by the rivers of data generated by applications and systems on-premises or flowing in via the cloud. At the same time, the cost of computational power has declined dramatically, making it practical to apply analytics and generate information on just about anything. But no advance comes without challenges. While the widespread availability of analytics has created seemingly valuable insights, executives and managers are finding that those insights are not easily linked to steps that will improve business outcomes or optimize actions. So the challenge is to make analytics impactful in eve

The use of analytics has exploded across business, and the value it already has delivered has heightened executives' expectations. Now data can be processed in real time to meet a constantly widening range of analytic needs. How your organization utilizes them in the next decade will be essential to your success. These developments come at an opportune time. Organizations are being over-whelmed by the rivers of data generated by applications and systems on-premises or flowing in via the cloud. At the same time, the cost of computational power has declined dramatically, making it practical to apply analytics and generate information on just about anything. But no advance comes without challenges. While the widespread availability of analytics has created seemingly valuable insights, executives and managers are finding that those insights are not easily linked to steps that will improve business outcomes or optimize actions. So the challenge is to make analytics impactful in eve

Are you blindly relying on manually-entered data from your systems and waiting for the recovery audit to claw back duplicates and overspend? Now with AI, you can discover rather than recover. Review every invoice and expense for risk before you pay without delaying supplier payments or employee reimbursements.

Six Steps to Smarter Accounting.Smarter accounting is just six easy steps away. This Getting the Basics Right Guide offers actionable ways for midsize organizations to spend less time reconciling financial data from disparate systems and more time making strategic, data-driven decisions.

Financial institutions are one of the most regulated by the mega-regulator. Issues of backing up information systems, including data backup and restoration of activities in case of failures and emergencies, are one of the most important for credit and non-credit financial organizations, as well as subjects of the national payment system, the activities of which are regulated and controlled by the Bank of Russia.

Support for Microsoft Windows Server 2008 R2 will be discontinued soon, and organizations need to prepare for the transition from the old system to new platforms, such as Microsoft Windows Server 2019. This article details how to work with Veeam ® DataLabs and provides information on using Veeam with Microsoft Azure. After reading this article, you will learn about the popular way to use Veeam DataLab. It will help to eliminate obsolete operating systems and to feel confident in the transition to new versions. The main topics of the article: Veeam DataLab working principles; principles of transition to the new version of Windows Server; testing updates.

The damage caused by ransomware is widely discussed in the media. But this is far from the only danger that threatens the availability of your data. In this webinar, you will learn about the basic concepts of IT system availability and how Veeam® can help you implement these concepts in your company. The following issues will be highlighted: backup rule "3-2-1"; why snapshots are not a backup; how to prevent implicit data corruption.

A recent survey of CIOs found that over 75% want to develop an overall information strategy in the next three years, yet over 85% are not close to implementing an enterprise-wide content management strategy. Meanwhile, data runs rampant, slows systems, and impacts performance. Hard-copy documents multiply, become damaged, or simply disappear.

Organizations realize they need analytics to run, grow, and differentiate their products and services. More than just driving strategic decision making, they need to incorporate analytics into their high-volume operational and transactional decisions every minute of every day. This means that analytics is no longer just the responsibility of the data science team. Organizations have to continuously deliver analytics into operational systems in a systemic, high-quality and dependable way.

In the broadening data center cost-saving and energy efficiency discussion, data center physical infrastructure preventive maintenance (PM) is sometimes neglected as an important tool for controlling TCO and downtime. PM is performed specifically to prevent faults from occurring. IT and facilities managers can improve systems uptime through a better understanding of PM best practices.

Learn how CIOs can set up a system infrastructure for their business to get the best out of Big Data. Explore what the SAP HANA platform can do, how it integrates with Hadoop and related technologies, and the opportunities it offers to simplify your system landscape and significantly reduce cost of ownership.

Bandwidth. Speed. Throughput. These terms are not interchangeable. They are interrelated concepts in data networking that help measure capacity, the time it takes to get from one point to the next and the actual amount of data you’re receiving, respectively. When you buy an Internet connection from Spectrum Enterprise, you’re buying a pipe between your office and the Internet with a set capacity, whether it is 25 Mbps, 10 Gbps, or any increment in between. However, the bandwidth we provide does not tell the whole story; it is the throughput of the entire system that matters. Throughput is affected by obstacles, overhead and latency, meaning the throughput of the system will never equal the bandwidth of your Internet connection. The good news is that an Internet connection from Spectrum Enterprise is engineered to ensure you receive the capacity you purchase; we proactively monitor your bandwidth to ensure problems are dealt with promptly, and we are your advocates across the Internet w

"Cloud-based predictive analytics platforms are a relatively new phenomenon, and they go far beyond the remote monitoring systems of a prior generation. Three key features differentiate cloud-based predictive analytics — data sharing, scope of monitoring, and use of artificial intelligence/machine learning (AI/ML) to drive autonomous operations. To help familiarize the uninitiated with specifically what types of value these systems can drive, IDC discusses them at some length in this white paper."