Business Service Management (BSM) is of growing importance in the IT world. By managing IT systems according to the business services they support - like order entry, online sales, shipping, or customer service - IT is able to deliver on real business goals like providing competitive advantage, improving customer satisfaction, driving revenue growth, and increasing shareholder value.
Configuration Management is at the heart of the IT Infrastructure Library (ITIL®) and forms the foundation for Business Service Management (BSM). In fact, it is safe to say that neither the ITIL IT Service Management (ITSM) processes nor the BSM functions that leverage ITSM can be efficiently carried out without accurate configuration and dependency information.
Effective workload automation that provides complete management level visibility into real-time events impacting the delivery of IT services is needed by the data center more than ever before. The traditional job scheduling approach, with an uncoordinated set of tools that often requires reactive manual intervention to minimize service disruptions, is failing more than ever due to todays complex world of IT with its multiple platforms, applications and virtualized resources.
Virtualization continues to grow at 20 percent or more per year, but it is not expected to overtake existing physical architectures at least through 2010. This white paper examines the unique challenges of virtualization and offers tips for its successful management alongside IT's physical deployments.
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.
There are success stories of businesses that have implemented Business Service Management (BSM) with well-documented, bottom-line results. What do these organizations know that their discouraged counterparts don't?
Configuration Management is at the heart of the IT Infrastructure Library (ITIL) and forms the foundation for Business Service Management (BSM). In fact, it is safe to say that neither the ITIL IT Service Management (ITSM) processes nor the BSM functions that leverage ITSM can be efficiently
carried out without accurate configuration and dependency information.
Welcome to the future of 24/7, any-time, anywhere access to digital content - where dynamic publishing solutions are the mantra. Is your organization ready for this brave new world of digital content distribution? This whitepaper explores how to prime your organization to leverage rapid digital content consumption as a key to business intelligence.
Giving employees the right tools to do their best work can be challenging in today’s world of multiple devices and diverse work styles. This e-book reveals how to choose technology that helps your workforce:
Protect company data
Get more done
Collaborate with colleagues
Stay in control of their schedules
Spend more time on value-added tasks
Published By: LogRhythm
Published Date: Feb 22, 2018
The traditional approach to cybersecurity has been to use
a prevention-centric strategy focused on blocking attacks.
While prevention-centric approaches do stop many threats,
many of today’s advanced and motivated threat actors are
circumventing these defenses with creative, stealthy,
targeted, and persistent attacks that often go undetected
for significant periods of time.
Do you know what happens during the first 60 minutes of a phishing attack? In this paper, security industry analyst Derek Brink, a Research Fellow at Aberdeen Group, crunches real-world data and measures the business risks of phishing attacks, including calculating the costs of phishing to businesses, the probability of small and large losses, and the ROI on incremental investments in advanced security to prevent phishing.
Published By: StrongMail
Published Date: Jun 08, 2008
The growing trend towards insourcing marketing and transactional email is being driven by businesses that are looking for ways to improve their email programs, increase data security and lower costs. When evaluating whether it makes more sense to leverage an on-premise or outsourced solution, it's important to understand how the traditional arguments have changed.
For financial business leaders and other c-level executives, moving away from unclear or ambiguous “improvements” to quantifiable measurements is crucial to the overall organization. Hard, meaningful data substantiates the execution of strategic, long-term business decisions. As technology is rapidly changing, executives can be challenged to find the right systems that drive business performance, provide competitive advantages, and increase the bottom line.
The average computer room today has cooling capacity that is nearly four times the IT heat load. Using data from 45 sites reviewed by Upsite Technologies, this white paper will show how you can calculate, benchmark, interpret, and benefit from a simple and practical metric called the Cooling Capacity Factor (CCF).
Calculating the CCF is the quickest and easiest way
to determine cooling infrastructure utilization and
potential gains to be realized by AFM improvements.
Despite the business-transforming upsides of data from the Internet of things (IoT), there’s a downside: security. Porous networks and lax users offer tantalizing access for hackers. Although most security spending is at the enterprise level, a shift is needed to secure IoT applications and provide improved governance and accountability. Electronics companies must create secure environments that safely collect, consume, share and store data on their networks. But they also must go beyond devices and consumers to close holes to factory, ecosystem and partner networks.
Hyper-complex production meets cognitive computing. Electronics manufacturing is surrounded by continuous complexity. Executives face rising resource costs in traditionally low-cost production markets. They must address increasing customization, shorter lead times, frequently changing requirements and shrinking order sizes – all while managing a sophisticated supply network. They need to examine automation potential and maintain critical institutional knowledge. Thinner margins and increased competition threaten consistent quality, risk greater downtime and reduce desired flexibility. Investments in new equipment and automation systems are increasing the amount of data available from the shop floor, but most is not used to its full potential. Now, cognitive manufacturing is transforming production to address such complexity.
This white paper will provide a road map to the most effective strategies and technologies to protect data and provide fast recovery should data be lost or corrupted due to accident or malicious action.
Journaling is a powerful feature, one that IBM has continued to develop and improve over the years. Yet, depending upon your business requirements, you probably still need more protection against downtime than journaling alone can provide. This white paper will cover what you need to know about journaling, what it can do and how it supports and cooperates with high availability software.
This white paper provides a road map to the most effective strategies and technologies to protect data in AIX environments and provide fast recovery should data be lost or corrupted due to accident or malicious action. The paper also outlines the benefits of continuous data protection (CDP) technologies for AIX.
Continuous member service is an important deliverable for credit unions, and. the continued growth in assets and members means that the impact of downtime is affecting a larger base and is therefore potentially much more costly. Learn how new data protection and recovery technologies are making a huge impact on downtime for credit unions that depend on AIX-hosted applications.
Imagine getting into your car and saying, “Take me to work,” and then enjoying an automated
drive as you read the morning news. We are getting very close to that kind of
scenario, and companies like Ford expect to have production vehicles in the latter part
Driverless cars are just one popular example of machine learning. It’s also used in
countless applications such as predicting fraud, identifying terrorists, recommending
the right products to customers at the right time, and correctly identifying medical
symptoms to prescribe appropriate treatments.
The concept of machine learning has been around for decades. What’s new is that
it can now be applied to huge quantities of data. Cheaper data storage, distributed
processing, more powerful computers and new analytical opportunities have dramatically
increased interest in machine learning systems. Other reasons for the increased
momentum include: maturing capabilities with methods and algorithms refactored to
run in memory; the
Machines learn by studying data to detect patterns or by applying known rules to:
• Categorize or catalog like people or things
• Predict likely outcomes or actions based on identified patterns
• Identify hitherto unknown patterns and relationships
• Detect anomalous or unexpected behaviors
The processes machines use to learn are known as algorithms. Different algorithms learn in different ways. As new data regarding observed responses or changes to the environment are provided to the “machine” the algorithm’s performance improves. Thereby resulting in increasing “intelligence” over time.
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.