data system

Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business.

Many new regulations are spurring banks to rethink how data from across the enterprise flows into the aggregated risk and capital reports required by regulatory agencies. Data must be complete, correct and consistent to maintain confidence in risk reports, capital reports and analytical analyses. At the same time, banks need ways to monetize, grant access to and generate insight from data. To keep pace with regulatory changes, many banks will need to reapportion their budgets to support the development of new systems and processes. Regulators continually indicate that the banks must be able to provide, secure and deliver high-quality information that is consistent and mature.

You can have all the latest features of iOS 8 on your iPhone, but if you’re still using an iPhone 4s, you won’t be able to take advantage of most of them. This should serve as an appropriate metaphor for this audience because when it comes to data storage, many of today’s storage solutions have been around since the 1970s…as in the the world of mobile, today’s data storage needs are revealing just how limited those older solutions are. Even if a company has updated almost everything in its IT ecosystem, it takes only one unchanged layer to prevent them from realizing the benefits of the latest technology. With petabyte scale, reliability, performance, and efficiency the order of the day we are fast approaching that point with storage. There is without question a need to change in the current storage paradigm. In this webinar you will learn about current IT storage challenges and useful insights about next-generation storage solutions.

Finding a better place to store an ever-expanding volume of valuables is a near universal challenge—for individuals and their businesses. From physical holes in the ground to the ethereal cloud and beyond, the range of options for stashing stuff is immense. And, depending on what you’re storing and how easily you want others to find it, some options are better than others. Read this white paper to learn how a Network Attached Storage (NAS) system provides the customization, speed, ease-of-use, security and affordability needed to protect and share digital assets for many small business owners.

This white paper, based on a survey of database professionals, examines the problems facing many large businesses that are attempting to remain agile while dealing with a mountain of data under management.

Sybase's Adaptive Server® Enterprise (ASE) is a high performance relational database management system for mission-critical, data intensive environments that has been meeting these needs for nearly three decades.

Download this white paper for analysis of survey results that compare TCO of Sybase ASE compared to Oracle.

This webcast discusses the technical benefits of Sybase ASE's compression technology. Watch the recording to learn more and to hear about use cases, strategies for data migration and a look at the performance implications.

This paper presents an overview of iSeries high availability to companies that are beginning to explore this powerful business continuity technology. The critical components of high availability solutions are detailed in this paper, including data replication engines, system monitors, role swap capabilities, and the importance of autonomic processes.

Journaling? RAID? Vaulting? Mirroring? High availability? Know your data protection and recovery options! Download this information-packed 29-page report that reviews the spectrum of IBM i (i5/OS) and AIX resilience and recovery technologies and best practices choices, including the latest, next-generation solutions.

For IT departments looking to bring their AIX environments up to the next step in data protection, IBM’s PowerHA (HACMP) connects multiple servers to shared storage via clustering. This offers automatic recovery of applications and system resources if a failure occurs with the primary server.

This paper describes a series of tests run to determine the viability of continuous data protection (CDP) using InMage DR Scout along with Agami Systems AIS 3000 series of unified storage systems.

A powerful signal integrity analysis tool must be flexibility, easy to use and integrated into an existing EDA framework and design flow. In addition, it is important for the tool to be accurate enough. This report reviews a validation study for the Mentor Graphics HyperLynx 8.0 PI tool to establish confidence in using it for power integrity analysis.

For advanced signaling over high-loss channels, designs today are using equalization and several new measurement methods to evaluate the performance of the link. Both simulation and measurement tools support equalization and the new measurement methods, but correlation of results throughout the design flow is unclear. In this paper a high performance equalizing serial data link is measured and the performance is compared to that predicted by simulation. Then, the differences between simulation and measurements are discussed as well as methods to correlate the two.

Virtualization can deliver dramatic benefits for data centers, but it can also stress the underlying support infrastructure.  Power and cooling systems—which may have been quite sufficient for pre-virtualization needs—could easily become inadequate when data center performance patterns are radically altered.  This paper describes some of power challenges related to virtualization—and the readily available technologies to address them.

Learn how IBM's DB2 portfolio can help transform your data center. Download this free white paper from IBM to learn more!

Download this free IBM white paper to learn how to better manage your data center with System z.

Starting data governance initiatives can seem a bit daunting. You’re establishing strategies and policies for data assets. And, you’re committing the organization to treat data as a corporate asset, on par with its buildings, its supply chain, its employees or its intellectual property. However, as Jill Dyché and Evan Levy have noted, data governance is a combination of strategy and execution. It’s an approach that requires one to be both holistic and pragmatic: • Holistic. All aspects of data usage and maintenance are taken into account in establishing the vision. • Pragmatic. Political challenges and cross-departmental struggles are part of the equation. So, the tactical deployment must be delivered in phases to provide quick “wins” and avert organizational fatigue from a larger, more monolithic exercise. To accomplish this, data governance must touch all internal and external IT systems and establish decision-making mechanisms that transcend organizational silos. And, it must provi

How can you open your analytics program to all types of programming languages and all levels of users? And how can you ensure consistency across your models and your resulting actions no matter where they initiate in the company? With today’s analytics technologies, the conversation about open analytics and commerical analytics is no longer an either/or discussion. You can now combine the benefits of SAS and open source analytics technology systems within your organization. As we think about the entire analytics life cycle, it’s important to consider data preparation, deployment, performance, scalability and governance, in addition to algorithms. Within that cycle, there’s a role for open source and commercial analytics. For example, machine learning algorithms can be developed in SAS or Python, then deployed in real-time data streams within SAS Event Stream Processing, while also integrating with open systems through Java and C APIs, RESTful web services, Apache Kafka, HDFS and more.

As the pace of business continues to accelerate, forward-looking organizations are beginning to realize that it is not enough to analyze their data; they must also take action on it. To do this, more businesses are beginning to systematically operationalize their analytics as part of a business process. Operationalizing and embedding analytics is about integrating actionable insights into systems and business processes used to make decisions. These systems might be automated or provide manual, actionable insights. Analytics are currently being embedded into dashboards, applications, devices, systems, and databases. Examples run from simple to complex and organizations are at different stages of operational deployment. Newer examples of operational analytics include support for logistics, customer call centers, fraud detection, and recommendation engines to name just a few. Embedding analytics is certainly not new but has been gaining more attention recently as data volumes and the freq

Business users need a simple but powerful way to navigate through data and find the insights to make timely, critical business decisions. Unfortunately, many users have become frustrated at their inability to quickly access and analyze the information they require. This data typically includes a combination of personal and corporate data locked in various enterprise systems. It exists in different formats and can be hard to analyze, change or share — making it difficult for people to get fast answers to business questions.

IBM PureFlex Systems combine advanced IBM hardware and software with “patterns of expertise” and integrate them into three optimized configurations that are simple to acquire and deploy. Read the data sheet to learn more about configurations optimized for small businesses, application servers, and transactional and database systems.

A Fonality study found that for companies with knowledge workers who average an eight-hour workday, nearly 50 percent of that time-almost four hours a day.

IBM PureFlex Systems combine advanced IBM hardware and software with “patterns of expertise” and integrate them into three optimized configurations that are simple to acquire and deploy. Read the data sheet to learn more about configurations optimized for small businesses, application servers, and transactional and database systems.

Business users need a simple but powerful way to navigate through data and find the insights to make timely, critical business decisions. Unfortunately, many users have become frustrated at their inability to quickly access and analyze the information they require. This data typically includes a combination of personal and corporate data locked in various enterprise systems. It exists in different formats and can be hard to analyze, change or share — making it difficult for people to get fast answers to business questions.