Today Terma Software Labs announced centralized management for job scheduling and workload automation products, also known as “Single Pane of Glass” management. A constant challenge for customers using multiple job scheduling engines and/or multiple vendors’ job scheduling products is the effective management of these environments: the user interfaces between products are very different, the approaches to management are inefficient, and the products themselves are simply not integrated. Terma Software Labs’ JAWS Workload Analytics platform solves these current day challenges by standardizing and modernizing both the user interface as well as the overarching management approach. JAWS can manage the following scenarios from a single and common user interface for CA AutoSys, CA 7, Tidal, and OpsWise:
Multiple instances of the same scheduling product on different platforms
Multiple instances and different release levels of the same scheduling product
Mixed environments (CA, Tidal, OpsWise) with different vendors scheduling products
Mixed platforms (mainframe & distributed) with different scheduling product such as CA 7 on the mainframe and CA AutoSys on distributed
The latest release of JAWS Workload Analytics features an intuitive user interface for managing these heterogeneous environments. It includes richer analytics for managing workload environments by providing resource awareness, agent awareness, advanced reporting, and additional support for legacy and newly released versions of job scheduling platforms. Terma’s platform for workload analytics provides a standard approach to integrating multiple vendors’ workload automation products.
Terma Software Labs, located in Boulder, CO, is the leading provider of advanced workload analytics, monitoring, and reporting solutions for enterprise job scheduling and workload automation products from companies such as Cisco (Tidal), CA Technologies (AutoSys, CA 7), and Stonebranch (OpsWise). Terma’s platform, JAWS, helps companies optimize their workload processing and get more value out of their workload automation products by providing SLA management, forecasting, prediction, and reporting. It helps companies lower their total cost of ownership, and improve the reliability and performance of their mission critical workloads. The platform addresses the long-standing need for a single user interface and management console view (Single Pane of Glass) into heterogeneous job scheduling environments across distributed and mainframe platforms.
For more information got to http://www.TermaLabs.com
To the average enterprise member, IT operations are shrouded in mystery. For the vast majority of business users, these departments largely serve to help keep the lights on. Because so many enterprise leaders are in the dark regarding IT activity, they repeatedly miss opportunities to better utilize these teams and maximize their value to the business.
A recent survey of nonprofit leaders conducted by accounting firm Tate & Tyron found that the managerial structures of these organizations are often inappropriately constructed. Only 13 percent of the respondents stated that their IT departments reported directly to the CEO, according to Nonprofit Quarterly. Meanwhile, 38 percent said their IT leaders were required to report to their CFO or COO, effectively putting IT under the oversight of another department.
Companies often have trouble discerning how to get the most value out of their day-to-day IT operations as well. The Florida Current reported that state lawmakers have recently discussed potential ways to consolidate IT resources and enhance the department's performance. A key point of debate between government officials has been the role that the department would play overseeing IT processes across state agencies. The news source noted that lawmakers have had difficulty in the past coming to an agreement on how to best structure IT in the state of Florida.
What role should IT serve?
Within both the public and private sectors, debates surrounding the use of IT often boil down to maintenance and innovation. Traditionally, these departments have largely been tasked with keeping critical machines and networks online and functioning, leaving little - if any - time or manpower for enterprise-building endeavors. When IT resources are solely utilized for hardware and software upkeep, businesses fail to optimize these departments to their full potential.
IT members can greatly enhance enterprise operations by working more directly with other departments. For instance, MarketingProfs contributor Adele Sweetwood recently outlined how her marketing and IT employees have worked together to improve the customer engagement efforts by taking advantage of digital data streams. Working with IT, the marketing department was able to tear down existing data silos and incorporate sophisticated analytics processes. This has allowed Sweetwood's company to craft more finely honed marketing campaigns that effectively target audiences.
To replicate this successful synchronization of disparate business units, companies will need to free up their existing IT resources. Workload automation analytics solutions offer an opportunity to greatly reduce the amount of manual oversight needed to keep critical systems and assets running. This technology can vastly improve the performance of job scheduling systems and eliminate many of the IT processing errors that can lead to expensive service disruptions. IT operations analytics tools assess past trends and current conditions to help administrators determine how to optimize their jobstreams. By incorporating this technology, IT departments can reduce the amount of personnel needed to maintain complex workflow environments while improving the performance of their processes and tasks. This will leave more resources available for other beneficial and potentially innovative pursuits.
IT Infrastructure Management and Operations news brought to you by Terma Software Labs, leaders in IT Operations Analytics solutions.
Within every corner of the enterprise, department leaders look for new opportunities to reduce risk and inefficiencies. Over the past several years, the advent of advanced analytics processes have provided these business users with new effective tools to achieve these goals. Among the litany of enterprise-grade technologies to emerge recently, predictive analytics has shown some of the greatest potential for direct operational value. Many industries, from marketing to insurance, have already begun leveraging theses tools to dramatically improve their operations, but IT environments may provide the most conducive environment for their deployment.
While retailers and other consumer-facing organizations have utilized predictive analytics to better anticipate market trends and meet customer demands, other areas of industry have put these resources to use improving their risk management practices. In the insurance sector, avoiding risk is critical, as the profitability of a firm could suffer if staff members are not careful about who they offer their services to and how far they extend a given policy's coverage. Customers in this field can be viewed as investments, with some presenting far more risk factors than others. In addition, insurance fraud is a common occurrence, further undercutting the bottom line of organizations throughout the industry.
Predictive analytics tools help these firms better assess the potential for a particular client to file a claim down the road, and if the payout will offset the culmination of policy payments made until then. Furthermore, insurance companies can leverage this technology to more accurately determine whether a claim is completely legitimate or fraudulent. By making more informed decisions regarding what coverage is extended to a client and which claims are approved, insurance firms can generate healthier revenue streams and please stockholders.
According to a recent survey jointly conducted by Earnix and ISO, 82 percent of North American insurance professionals stated that their firms used predictive analytics in some capacity, Insurance Journal reported. Of those, 55 percent cited the ability to reduce operational risks as a benefit of implementing these tools. Meanwhile, 39 percent stated that they had experienced improved operational efficiency since deploying predictive analytics solutions.
Applying predictive capabilities to IT
The ability to better identify risk factors and reduce inefficiencies offers a great deal of value to IT departments, particularly those that experience bottlenecks and disruptions within their job scheduling workflows. Even with sophisticated workload automation tools such as CA 7 or AutoSys in place, it may be difficult for administrators to identify the sources of these performance issues, preventing them from effectively addressing them. By incorporating an IT operations analytics solution, employees can trace jobstream delays back to their root cause in short order and correct them before they lead to more costly and damaging service disruptions.
Over the past eight years, IBM has invested a considerable amount of capital into its analytics processes, including predictive capabilities aimed at improving IT environments, IDG News Service reported. Gathering information from a variety of metrics and key performance indicators, these tools can then determine if current jobstream conditions may prevent critical tasks from receiving the resources needed to complete within their allotted timeframe.
"For instance, a banking application may be performing slowly, but it would be difficult for a network administrator to determine the problem may be with the Java Virtual Machines (JVMs), which are executing garbage collection duties at inopportune times, slowing their output," the source explained.
A sophisticated workload analytics tools can organize jobstream resources and tasks to support mission-critical processes and ensure that they execute as planned. In addition, system administrators will be notified immediately if any developments emerge that may prevent high-priority jobs from completing, giving them ample lead time to make the necessary changes. By laying down this workflow safety net, businesses can ensure they reliably meet the conditions of their SLAs and continue providing high-quality services.
IT Infrastructure Management and Operations news brought to you by Terma Software Labs, leaders in IT Operations Analytics solutions.
Modern organizations are operating in the age of big data, but while some may be aware of the significant benefits that business analytics initiatives can provide, others are only now jumping on board. Appearing in Information Management, Ventana Research provided the results of its recent benchmark study on business technology innovation, in which 39 percent of polled organizations named analytics as their top priority. Furthermore, 11 percent named big data specifically as a top priority for furthering innovation.
"But in this time of global business, nonstop communications and fierce competition, more organizations are finding that big data and analytics together can help them cope with constant change," the research firm stated. "They can help organizations face imperatives such as increasing time-to-value and becoming more agile and adaptive."
The source went on to detail the type of competitive advantages organizations can hope to gain from business analytics, noting that operational analytics in particular can boost efficiency, which can have widespread benefits across a company. Ventana Research also explained how analytics can be leveraged to improve job scheduling and resource allocation, with predictive analytics enabling the prevention of outages that can otherwise have devastating cascading effects down the line.
Midsize Insider also explored the return on investment of business analytics efforts, with contributor Doug Bonderud recommending that companies utilize tools to measure twice and report once. The source cited a recent IBM study that found that most companies were not only leveraging analytics to cut costs, but also to generate revenue. Specifically, the study found that almost 40 percent of businesses that reported using analytics software for purposes such as resource scheduling also saw a return on investment within a six-month period. This demonstrates that while there is the perception that business analytics is primarily useful for managing costs and deter overspending, it can also carry significant advantages in the form of improving the bottom line.
IT Infrastructure Management and Operations news brought to you by Terma Software Labs, leaders in IT Operations Analytics solutions.
Big data and other advanced analytics solutions have exploded in popularity in recent years. Companies have more information at their disposal than ever before and they are rapidly integrating new tools to take advantage of this data for the good of the enterprise. Part of the appeal found in advanced data analytics tools is their versatility. There are nearly endless applications for this technology within any environment. Depending on the individual organization and how it plans to implement data analytics, however, it may find itself coming up against some significant roadblocks. If companies can bypass these challenges, they can achieve new levels of efficiency and success with the insights provided by business analytics solutions.
The two most pressing concerns for organizations considering a data analytics investment are hardware and expertise. Some companies may have the infrastructure in place to handle the gathering, storing and processing of massive volumes of information on a regular basis, but many will need to make a considerable investment to bolster their capabilities. Because big data relies on the "three Vs," volume, velocity and variety, companies need to be able to collect large amounts of complex and disparate forms of data quickly. This could require a significant hardware investment that may undercut the ROI of a data analytics initiative.
"In order to facilitate this information discovery ... next-generation data architectures need to support a foundational data store (either on premise, cloud-based or in hybrid model) that is both fault tolerant and scalable," BeyeNETWORK contributor Timur Mehmedbasic stated. "This new storage model enables data refinery and exploration scenarios that allow companies to gain insights via information production scenarios that were previously not possible in a structured/relational data storage model."
Another concern that businesses will have to address is the current skills gap among analysts. As noted by ITProPortal's Paul Cooper, many organizations have struggled to hire new project members with the requisite experience and knowledge regarding advanced analytics processes. In the United Kingdom alone, the number of big data technicians would need to increase 243 percent to properly fill demand, according to Cooper.
Streamline internal systems with advanced analytics
For organizations that can overcome these challenges, however, the benefits far outweigh any growing pains or cost of investment. ZDNet contributor Dana Gardner recently spoke to Dan Woicke, Director of Enterprise Systems Management at Cerner Corp., to discuss how advanced analytics could be leveraged within the healthcare industry. Woicke explained that an influx of data can help organizational officials identify potential issues in their internal networks and systems before they manifest in more damaging and costly ways.
"We need to make sure that we have the right data in place in order to measure how systems are running and then be able to predict how those systems will run in the future," Woicke said. "If things are happening that might be going negative, how can we take the massive amounts of data that are coming into our new analytical platform, correlate those parameters, predict what's going to happen and then take action before there is a negative?"
IT departments can utilize workload automation analytics to locate bottlenecks in their jobstreams that could present a greater threat to operations if left unattended. For businesses such as financial firms that run critical client-facing services, workflow bottlenecks can lead to catastrophic disruptions. A high-quality IT operations analytics solution will constantly monitor jobstream conditions in real time and accurately identify situations in which an important task may at risk for failure. It can also provide deeper insight into the sources of these bottlenecks, giving administrators a head start on addressing the problem. This way, IT professionals can prevent jobstream delays from culminating in expensive service outages. Because these tools utilize legacy hardware and established job schedulers, little - if any - equipment and personnel upgrades are needed to take full advantage of them.
With the growing complexity of modern IT environments, it has become virtually impossible to maintain successful operations without the use of an effective job management system. However, the tools that exist to help schedule jobs and tasks are wide-ranging, so it is important for decision makers to take a number of considerations into account prior to investing in solutions. In a recent TechTarget article, Senior Technology Editor Stephen Bigelow discussed the increasing complexity and offered a few guidelines as to how to select the best-fitting system management tools for a given organization.
"IT professionals can no longer rely on traditional physical servers and provisioning to manage enterprise computing," Bigelow wrote. "Today, server virtualization and other technologies abstract workloads from underlying systems; mission-critical applications may reside on almost any server at any location, connected through a network that is also virtualized to manage traffic flows and data. IT professionals need powerful tools to manage such systems."
Bigelow outlined five considerations IT professionals must make when selecting the proper scheduling tools, first stressing the importance of identifying the most crucial functionality and features for any given operations. This critical first step will also enable decision makers to narrow their scope as far as available options are concerned by eliminating any scheduling tool that does not contain the desired capabilities. According to Bigelow, this is also essential for goals related to cutting costs as typically, products can be easily upgraded at a later point in time. He listed numerous features that should be considered, including hardware discovery, notification systems, lights-out management, service desk, security and workload automation.
The second point that should be considered is whether an organization is looking for support for heterogeneous or homogeneous systems. Heterogeneous environments often emerge as a side effect of acquisitions, mergers and inadequate planning for growth. Because a schedule program needs to be able to see inside of systems, as Bigelow noted, it is essential that the tools chosen are capable of working across all hardware being used.
"Heterogeneous environments present a serious challenge - a single tool may not be able to gather the same data or impose the same levels of control on every make and model of system hardware," Bigelow wrote. "Heterogeneous tools often sacrifice some granularity to broaden the scope of supported systems."
This consideration relates well to a later point Bigelow addresses - the need to select automation tools that can be integrated with other components and management suites. He explained that many businesses use multiple tools that together make up systems management solutions. In order for this approach to be effective, however, these tools need to be able to integrate with one another.
CA Workload Automation AE (AutoSys Edition) is one solution that could be high on the lists of many decision makers, as the distributed hosted job scheduling engine is geared at reducing complexity through event-driven automation, workflow monitoring and policy-based management. AutoSys is a popular choice because it enables business analytics initiatives across systems. If a corporation is using AutoSys and decides to introduce a workload automation analytics tool to the IT environment, it is essential that they integrate seamlessly to provide the most benefits.
Other considerations that Bigelow addressed included whether it would be more beneficial to leverage open source or proprietary solutions, and what the installation and subsequent learning curve will look like for the selected tool.
"Choosing systems management tools is a challenging exercise for any business," Bigelow wrote. "The best path to success considers management needs and business limitations, then matches those to the best proprietary or open source feature set that interfaces to existing management products."
Today Terma Software Labs announced a significant release of JAWS for Cisco’s Tidal Enterprise Scheduler. Terma has upgraded its current workload analytics, monitoring, and reporting solution to support Tidal Enterprise Scheduler (TES) version 5.3. TES 5.3 was the forerunner to TES 6.x, which was previously released by Cisco. Based on customer demand, Terma has developed and certified this previous release to help customers more efficiently manage their 5.3 instances and provide better insight into their workload environments. This release will aid customers upgrading to the latest release of the TES (6.x) product and is available immediately for download. For more information on Tidal Enterprise Scheduler support click here.
Terma Software Labs is located in Boulder, CO and is the leading provider of advanced workload analytics, monitoring, and reporting solutions for enterprise job scheduling and workload automation products from companies such as Cisco (Tidal), CA Technologies (AutoSys, CA 7), and Stonebranch (OpsWise). Terma’s product, called JAWS, helps companies optimize their workload processing and get more value out of their workload automation products by providing SLA management, forecasting, prediction, and reporting. JAWS helps companies lower the cost of ownership and improve the reliability and performance of their mission critical workloads. JAWS also addresses the need for a single user interface and management console (aka Single Pane of Glass) into heterogeneous job scheduling environments across distributed and mainframe platforms.
For more information, go to www.termalabs.com
One of the major pursuits within the field of advanced analytics is the development of sophisticated tools to process data streams in real time, bringing more immediate insight and performance benefits to businesses everywhere. Traditional analytics tools have exclusively utilized historical information, which have provided a great deal of value in their own right. However, to obtain deeper insights into enterprise operations and identify opportunities to eliminate costly inefficiencies and improve productivity, companies need to broaden the scope of these resources.
Today, businesses are leveraging advanced analytics solutions that incorporate additional sources of information including real-time data streams. By pairing these incoming volumes with records stored in legacy systems, companies can gain a new level of insight into various aspects of the enterprise as they transpire. This ability will allow organizations to remain more agile and quickly respond to emerging trends and developments.
Organizations from numerous disparate sectors have found considerable value in taking a real-time approach to data analytics. For example, Moroch Partners and Polygraph Media recently announced that the two companies had developed a software tool that can process real-time information collected from social media networks. Marketers could then use the information gained from these processes to craft more relevant campaigns that will better engage target audiences.
Officials from the Singapore Management University School of Information Systems have begun to conduct research into the wider applications for this technology, including providing deeper insights into human behavior. However, according to Asian Scientist Magazine, implementing these developments in the real world could present a number of challenges due to unpredictable variables.
Within IT environments, however, users can reliably leverage real-time data streams to bolster enterprise operations. Sophisticated workload automation analytics solutions are able to constantly monitor jobstreams, identifying bottlenecks as they develop. This way, IT administrators can shift resources to ease the workload strain and ensure that job scheduling tools continue to run optimally.
Across the globe, companies have invested in data analytics solutions, enticed by the promise of enhanced enterprise efficiency and productivity. For many business, however, wringing the most value out of these tools proves to be more challenging than anticipated and their immense potential is never fully realized. Bersin by Deloitte recently researched the effectiveness of enterprise analytics programs and found that many organizations have not been able to leverage their data beyond a fundamental level. According to Computer Weekly, 86 percent of participating businesses reported using their human resources data streams solely to generate basic reports.
Many organizations that attempt to implement advanced analytics tools might find that the poor quality of their data prevents them from gaining any real benefits from these efforts. Dirty data, such as erroneous, incomplete or outdated information, will only compromise the integrity of an analytics project and likely return inaccurate insights. When companies cannot trust the validity of their incoming information, they must make an effort to properly scrub that data. This often entails running processes that comb databases, detecting and correcting erroneous value sets. This extra step can delay an analytics program and reduce its overall ROI.
Data silos prevent deep insights
Another issue that analytics adopters frequently encounter is an inability to tap into every enterprise database and system. Getting the most value out of data analytics tools is predicated on having access to the most information possible. But when key sources of information are siloed and beyond the reach of analytics teams, project members will be unable to extract quality insights. Econsultancy contributor Jon Myers noted that this is a common challenge for marketers who try to use analytics technology to better understand customer interactions and behavior.
Many IT operations analytics solutions do not suffer from these same problems, as the data they require is easily available and of a very high quality. When these tools are deployed in a jobstream environment, they can view workflows in real time and identify any process bottlenecks. Once these disruptive resource crunches have been recognized, workload automation utilities can then dive into the data stream and assess what factors have contributed to their development. Knowing the root cause of a jobstream bottleneck will allow IT administrators to quickly devise an effective solution, ensuring that they are allocating resources in the most efficient manner possible.
Predictive analytics has emerged as an exciting subset within the larger umbrella of advanced analytics processes. The ability to leverage incoming data steams to create accurate forecasts of future events offers an enormous amount of value to any organization regardless of its industry. Retailers, restaurant chains and IT operations, among others, have all benefited from the deployment of predictive analytics resources.
Perhaps the most common application of these advanced analytics processes is to determine how market conditions may be poised to change in the near future. Often, this is done by evaluating customer behavior and extrapolating those results to encompass larger demographics. By anticipating fluctuations in consumer trends before they occur, businesses can better position themselves to pass by the competition. According to Consumer Goods Technology, these tools have also been used to identify potential risks that could affect the continued operability of an organization.
Typically, these risks are market factors that could undermine the performance of a particular product or service. Sometimes, however, businesses use predictive analytics to identify more pernicious threats such as the presence of militant forces that could destabilize an entire region. CIO's Lauren Brousell reported that Dunkin' Brands utilizes this technology to discern the likelihood that a violent conflict will break out in areas where its employees may be located. For example, several staff members were recently scheduled to travel to Bogota, Columbia, on business, but the corporation's analytics resources warned that a planned protest in the region had the potential to erupt into violence.
"We have to be ahead of what's about to happen so we can keep employees safe and out of those areas," said John Sullivan, Dunkin's director of corporate security, according to the source.
In the IT world, predictive analytics are often used to identify jobstream conditions that could potentially affect the performance of high-priority tasks. If a critical workload failed to execute as planned, the organization could be in danger of violating one of its important service-level agreements. Workload automation analytics solutions can help IT teams ensure their workflows continue to operate at a high level with little to no disruptions.