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C2020-615 exam Dumps Source : IBM Cognos Real-time Monitoring Developer
Test Code : C2020-615
Test name : IBM Cognos Real-time Monitoring Developer
Vendor name : IBM
: 60 existent Questions
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IBM IBM Cognos Real-time Monitoring
IBM Works with Garmin, Guardhat, Mitsufuji and SmartCone to identify talents risks within the workplace
SAN FRANCISCO, Feb. 13, 2019 /PRNewswire/ -- IBM suppose -- IBM (NYSE: IBM) these days announced most faultfinding collaborations with Garmin fitness, Guardhat, Mitsufuji and SmartCone to monitor worker security in hazardous environments, including these working in construction, mining and factories, the usage of IoT technologies, built-in into wearables. IBM's Maximo worker Insights will pomp screen biometric and environmental information to succor determine whether personnel are experiencing hazards or chance. facts will live gathered in nigh true-time from wearables, judicious devices and environmental sensors to succor groups quickly reply to problems or react to changing environmental circumstances.
today IBM announced collaborations with Garmin, Guardhat, Mitsufuji and SmartCone to succor organizations pomp screen their employees’ security with Watson IoT. supply: IBM
personnel working in unexpectedly changing environments face shifting circumstances, even if on the factory ground, on the forklift, atop a phone tower or drilling into the earth. using IoT to understand what worker's are doing in the context of the dynamic ambiance round them – including warmth, peak, weather and gasoline stages – permits businesses to invoke near actual-time and prescriptive defense practices to aid protect the wellbeing of employees and which should succor them preserve lower coverage costs.
For personnel, this novel providing displays capabilities environmental threats to their security and safety as they labor on the entrance traces. For employers, the concede is designed to back them establish and reply to skills hazards with the intention to hold their workforce secure. Nonfatal site of labor injuries account for near $60 billion in employees' compensation fees within the U.S. although security controls and personal defensive device are obligatory in most hazardous jobs, this concede is designed to back agencies to determine and respond to issues or react to changing environmental situations. in fact, based on the Bureau of Labor records, just about three million nonfatal occupational injuries were recorded in 2017.
"worker safety is a faultfinding priority for All businesses and this collaboration is an faultfinding milestone in dramatically enhancing the manner enterprises identify and collect rid of hazards in the site of work," said Kareem Yusuf Ph.D., time-honored manager, IBM Watson IoT. "we're extremely joyful to labor with Garmin, Guardhat, Mitsufuji and SmartCone, and leverage their respective management and commitment to assist help protection within the office," continued Dr. Yusuf.
"Garmin fitness is worked up to labor with IBM Watson to modernize employee safeguard," talked about Travis Johnson, international Product Lead, Garmin fitness. "Combining the potent analytic capabilities of the IBM Watson IoT concede with the superb sensor statistics and lengthy battery life of Garmin devices creates an excellent solution for remotely monitoring worker's with minimal user burden."
"The implementation of sensible defensive equipment permits us to more suitable anatomize site of labor records and provide essential safeguard insights in nigh actual-time," said Saikat Dey, Guardhat Co-Founder and CEO. "by pass of working with IBM, they are capable of leverage Maximo employee Insights to deliver sensible defense to scale within the development, manufacturing and refining industries."
"IBM Maximo worker Insights offers the near precise-time perception that their customers need to tackle the security of their workers," talked about Ayumu Mitera, CEO, Mitsufuji. "we are excited to labor with each IBM and their valued clientele to augment the hamon solution additional. They discern IBM as a useful member of their crew, now not handiest offering effective internet of issues applied sciences, however too assisting us establish novel market alternatives All over."
"we are extremely joyful to labor with a global chief similar to IBM and combine IBM Maximo employee insight technology into their platform," pointed out Tenille Houston, VP Communications and advertising, SmartCone. "With the ever-evolving office, SmartCones' finished end-to-conclusion concede combined with IBM's IoT know-how and superior analytics offers the optimal pairing to gold benchmark meet trade needs."
Garmin health companion SDKGarmin, a world leader in wearable know-how, is teaming up with IBM to tender organizations who installation the IBM Maximo employee Insights platform to collect hold of indicators according to nigh actual-time sensor data from workers donning Garmin undertaking trackers. by using embedding the Garmin health accomplice SDK within the IBM Maximo employee Insights platform, supervisors and safeguard officers can receive nigh true-time notifications for top coronary heart expense and man down situations, as well as assessment ancient analytics based on the biometric alerts from Garmin wearables.
Guardhat and its smart difficult hatsGuardhat's KYRA IoT platform integrates and complements the IBM employee Insights solution to provide nigh precise-time situational attention to laborers and company operations through the exercise of smart PPE wearables. corporations can gain deeper knowing of the container condition and elevate recognition within the organization, to examine surest practices and strategies for desultory mitigation thereby managing or keeping lower assurance charges.
Mitsufuji and its hamon® wearable shirtMitsufuji, a wearable platformer in Japan, has launched a novel wearable "shirt" referred to as hamon® to music IoT sensor facts from employee's biometrics to succor live sure protection and productivity in vehement environments. The hamon® shirt, crafted from silver conductive fibers, collects a wearer's biometric records, together with heart fee, cadaver temperature and location, as well as environmental records equivalent to humidity, temperature, noise and toxic gasoline levels, along with using IBM Maximo employee Insights. with the aid of connecting to the IBM Maximo employee Insights solution on the IBM Cloud, this information can too live analyzed in nigh precise-time, with alerts and alarms signaled on cellular instruments to buy a break, exchange areas, and so forth., before overexertion or damage occur.
SmartCone and its incredibly transportable systemSmartCone, a issuer of sensible, IoT-based security and monitoring solutions for securing supine and hazardous zones, gigantic and small, is working with IBM and integrating Maximo worker Insights into its particularly transportable device to video pomp employee protection within the utilities industry, community site visitors, development, mining and industrial environments with stirring or inferior no-go zones. applying multi-sensors, audio/video, communication capabilities, computing and zone gateway capabilities, TheSmartCone™ gadget combines with IBM Maximo employee Insights to deliver supervisors and safety officers with near precise-time notification and customary analytics on risks related to falls, "man-downs," no-go zones, extreme temperatures and more.
About IBM suppose At consider 2019, IBM will define novel choices, client engagements, partnerships, know-how breakthroughs and developer tools that underscore how IBM and partners are altering the pass the zone works. For greater counsel, visit the IBM believe 2019 Newsroom: https://newsroom.ibm.com/think. comply with the convention on Twitter at #think2019 and @ibmlive, and fade to https://www.ibm.com/pursuits/suppose/ for the total schedule and are living streaming agenda.
Guardhat, this is no common tough hat
hamon®-the incredibly connective AGposs fiber collects biometric information from the wearer.
CEO, Jason Lee, shows simply how moveable theSmartCone™ can too be. (photo through result Holleron)
IBM enterprise brand. (PRNewsfoto/IBM)
View original content material to down load multimedia:http://www.prnewswire.com/news-releases/ibm-helps-organizations-display screen-their-people-defense-with-watson-iot-300794986.html
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IBM announced major collaborations with Garmin health, Guardhat, Mitsufuji and SmartCone to pomp screen worker security in hazardous environments, including these working in development, mining and factories, the exercise of IoT technologies, integrated into wearables. IBM's Maximo employee Insights will video pomp biometric and environmental facts to aid establish even if employees are experiencing risks or possibility. facts will live gathered in near real-time from wearables, judicious instruments and environmental sensors to back organizations right away respond to complications or react to altering environmental circumstances.
people donning Garmin recreation trackers will exercise IBM Maximo employee Insights platform sending nigh actual-time notifications for prime heart rate and man down eventualities.IBMEmployees working in unexpectedly changing environments face stirring circumstances, even if on the manufacturing facility floor, on the forklift, atop a phone tower or drilling into the earth. using IoT to consider what people are doing in the context of the dynamic atmosphere round them — including heat, top, climate and fuel tiers — allows companies to reserve in accommodate nigh precise-time and prescriptive security practices to aid give protection to the smartly-being of worker's and which should assist them preserve reduce coverage costs.
For employees, this novel providing monitors expertise environmental threats to their safety and protection as they labor on the entrance lines. For employers, the solution is designed to assist them identify and reply to abilities hazards with the intention to maintain their workforce safe. however protection controls and private protecting gadget are obligatory in most hazardous jobs, this solution is designed to back organizations to determine and respond to issues or react to altering environmental situations.
"worker defense is a vital priority for All organisations and this collaboration is a ample milestone in dramatically improving the manner corporations establish and collect rid of dangers within the office," mentioned Kareem Yusuf Ph.D., established supervisor, IBM Watson IoT. "we are overjoyed to labor with Garmin, Guardhat, Mitsufuji and SmartCone, and leverage their respective management and dedication to assist enhance safety in the site of work," continued Dr. Yusuf.
Guardhat's KYRA IoT platform and IBM employee Insights will supply nigh actual-time situational focus to employees.IBM
"Garmin health is worked up to labor with IBM Watson to modernize worker security," observed Travis Johnson, global Product Lead, Garmin fitness. "Combining the powerful analytic capabilities of the IBM Watson IoT concede with the extremely helpful sensor facts and lengthy battery lifetime of Garmin contraptions creates an excellent solution for remotely monitoring workers with minimal person burden."
"The implementation of judicious protective gadget allows for us to enhanced anatomize office facts and supply faultfinding safety insights in nigh true-time," pointed out Saikat Dey, Guardhat Co-Founder and CEO. "by using working with IBM, they are in a position to leverage Maximo worker Insights to convey judicious security to scale in the construction, manufacturing and refining industries."
"IBM Maximo employee Insights can provide the nigh true-time perception that their customers deserve to handle the safeguard of their laborers," spoke of Ayumu Mitera, CEO, Mitsufuji. "we are excited to labor with both IBM and their purchasers to enhance the hamon concede additional. They discern IBM as a valuable member of their group, no longer best featuring effective internet of issues technologies, however too helping us establish novel market opportunities All over."
Mitsufuji hamon wearable shirt tracks IoT sensor facts from employee's biometrics.IBM"we're overjoyed to labor with a global chief similar to IBM and combine IBM Maximo worker perception expertise into their platform," referred to Tenille Houston, VP Communications and marketing, SmartCone. "With the ever-evolving site of work, SmartCones' comprehensive end-to-end concede combined with IBM's IoT expertise and advanced analytics offers the top of the line pairing to greatest meet trade wants."
Garmin fitness companion SDK Garmin, a worldwide chief in wearable know-how, is teaming up with IBM to present organizations who install the IBM Maximo worker Insights platform to acquire signals according to near real-time sensor data from workers donning Garmin activity trackers. by means of embedding the Garmin health associate SDK in the IBM Maximo employee Insights platform, supervisors and safety officers can receive near true-time notifications for towering coronary heart rate and man down eventualities, as well as assessment ancient analytics in accordance with the biometric signals from Garmin wearables.
Guardhat and its sensible arduous hats Guardhat's KYRA IoT platform integrates and enhances the IBM employee Insights solution to provide near real-time situational awareness to employees and company operations through the exercise of judicious PPE wearables. corporations can profit deeper knowing of the container situation and elevate awareness in the firm, to verify most effective practices and techniques for risk mitigation thereby managing or keeping reduce coverage charges.
Mitsufuji and its hamon wearable shirt Mitsufuji, a wearable platformer in Japan, has launched a brand novel wearable "shirt" referred to as hamon to tune IoT sensor statistics from employee's biometrics to aid ensure protection and productiveness in vehement environments. The hamon shirt, made from silver conductive fibers, collects a wearer's biometric data, including coronary heart expense, cadaver temperature and placement, in addition to environmental records comparable to humidity, temperature, noise and mephitic gasoline degrees, at the side of the exercise of IBM Maximo worker Insights. with the aid of connecting to the IBM Maximo worker Insights solution on the IBM Cloud, this facts will too live analyzed in near actual-time, with alerts and alarms signaled on mobile contraptions to buy a break, alternate areas, and many others., earlier than overexertion or harm occur.
SmartCone is integrating IBM Maximo employee Insights into its portable device to monitor employee protection in building, mining, utilities, industrial and group traffic environments.IBM
SmartCone and its tremendously transportable gadget SmartCone, a issuer of sensible, IoT-based defense and monitoring solutions for securing susceptible and hazardous zones, great and small, is working with IBM and integrating Maximo employee Insights into its enormously portable equipment to computer screen employee security in the utilities industry, group traffic, construction, mining and industrial environments with stirring or hazardous no-go zones. employing multi-sensors, audio/video, conversation capabilities, computing and side gateway capabilities, TheSmartCone™ equipment combines with IBM Maximo worker Insights to give supervisors and protection officers with near actual-time notification and customary analytics on risks concerning falls, "man-downs," no-go zones, extreme temperatures and extra.
Visoot Uthairam | second | Getty photos
IBM has announced "important collaborations" with SmartCone, Guardhat, Garmin health and Mitsufuji so that it will back to video pomp the security of employees in hazardous environments.
The collaborations will exercise cyber web of issues (IOT) technologies that beget been built-in into wearables, the tech tremendous referred to in an announcement Wednesday. workers in sectors together with factories, structure and mining will exercise the expertise, IBM delivered.
The business's know-how should live used to investigate environmental and biometric records to assist verify if worker's are exposed to hazard or possibility. judicious contraptions, wearables and environmental sensors may live used to compile the information in near real-time. "employee safety is a faultfinding priority for All corporations and this collaboration is a major milestone in dramatically improving the pass firms identify and liquidate dangers in the site of work," Kareem Yusuf, universal manager at IBM Watson IoT, mentioned in a statement. As know-how develops, a few industries and agencies are the usage of it to try and boost the safeguard of employees in the office.
Mining great BHP, for example, is the exercise of every slight thing from self reliant drills at iron ore mines to trialing "sensible caps" that anatomize brain waves and computer screen worker fatigue.
Of the novel collaboration with IBM, Garmin health's international Product Lead, Travis Johnson, spoke of that the aggregate of "the potent analytic capabilities of the IBM Watson IoT concede with the top notch sensor data and long battery lifetime of Garmin gadgets creates a very helpful concede for remotely monitoring laborers with minimal consumer burden."
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IBM Works with Garmin, Guardhat, Mitsufuji and SmartCone to Identify Potential Hazards in the Workplace
SAN FRANCISCO, Feb. 13, 2019 /PRNewswire/ -- IBM Think -- IBM (NYSE: IBM) today announced major collaborations with Garmin Health, Guardhat, Mitsufuji and SmartCone to monitor worker safety in hazardous environments, including those working in construction, mining and factories, using IoT technologies, integrated into wearables. IBM's Maximo Worker Insights will monitor biometric and environmental data to succor identify whether employees are experiencing dangers or risk. Data will live gathered in near real-time from wearables, smart devices and environmental sensors to succor organizations quickly respond to problems or react to changing environmental conditions.
Today IBM announced collaborations with Garmin, Guardhat, Mitsufuji and SmartCone to succor organizations monitor their workers’ safety with Watson IoT. Source: IBM
Employees working in rapidly changing environments face shifting conditions, whether on the factory floor, on the forklift, atop a cell tower or drilling into the earth. Utilizing IoT to understand what workers are doing in the context of the dynamic environment around them – including heat, height, weather and gas levels – allows organizations to implement near real-time and prescriptive safety practices to succor protect the wellbeing of workers and which should succor them maintain lower insurance costs.
For employees, this novel offering monitors potential environmental threats to their safety and security as they labor on the front lines. For employers, the solution is designed to succor them identify and respond to potential hazards in an pains to withhold their workforce safe. Nonfatal workplace injuries account for nigh to $60 billion in workers' compensation costs in the U.S. Although safety controls and personal protective equipment are mandatory in most hazardous jobs, this solution is designed to succor companies to identify and respond to problems or react to changing environmental conditions. In fact, according to the Bureau of Labor Statistics, nearly 3 million nonfatal occupational injuries were recorded in 2017.
"Worker safety is a faultfinding priority for All enterprises and this collaboration is a major milestone in dramatically improving the pass enterprises identify and liquidate hazards in the workplace," said Kareem Yusuf Ph.D., general manager, IBM Watson IoT. "We are thrilled to labor with Garmin, Guardhat, Mitsufuji and SmartCone, and leverage their respective leadership and commitment to succor help safety in the workplace," continued Dr. Yusuf.
"Garmin Health is excited to labor with IBM Watson to modernize worker safety," said Travis Johnson, Global Product Lead, Garmin Health. "Combining the powerful analytic capabilities of the IBM Watson IoT solution with the high-quality sensor data and long battery life of Garmin devices creates a much solution for remotely monitoring workers with minimal user burden."
"The implementation of smart protective equipment allows us to better anatomize workplace data and provide faultfinding safety insights in near real-time," said Saikat Dey, Guardhat Co-Founder and CEO. "By working with IBM, they are able to leverage Maximo Worker Insights to bring smart safety to scale in the construction, manufacturing and refining industries."
"IBM Maximo Worker Insights delivers the near real-time insight that their clients need to address the safety of their workers," said Ayumu Mitera, CEO, Mitsufuji. "We are excited to labor with both IBM and their clients to develop the hamon solution further. They discern IBM as a valuable member of their team, not only providing powerful Internet of Things technologies, but too helping us identify novel market opportunities around the world."
"We are thrilled to labor with a global leader such as IBM and integrate IBM Maximo Worker Insight technology into their platform," said Tenille Houston, VP Communications and Marketing, SmartCone. "With the ever-evolving workplace, SmartCones' comprehensive end-to-end solution combined with IBM's IoT technology and advanced analytics provides the optimal pairing to best meet industry needs."
Garmin Health Companion SDKGarmin, a global leader in wearable technology, is teaming up with IBM to tender organizations who deploy the IBM Maximo Worker Insights platform to receive alerts based on near real-time sensor data from workers wearing Garmin activity trackers. By embedding the Garmin Health Companion SDK in the IBM Maximo Worker Insights platform, supervisors and safety officers can receive near real-time notifications for towering heart rate and man down scenarios, as well as review historical analytics based on the biometric signals from Garmin wearables.
Guardhat and its smart arduous hatsGuardhat's KYRA IoT platform integrates and complements the IBM Worker Insights solution to provide near real-time situational awareness to workers and company operations through the exercise of Smart PPE wearables. Companies can gain deeper understanding of the province situation and raise awareness in the organization, to determine best practices and methods for risk mitigation thereby managing or maintaining lower insurance costs.
Mitsufuji and its hamon® wearable shirtMitsufuji, a wearable platformer in Japan, has launched a novel wearable "shirt" called hamon® to track IoT sensor data from worker's biometrics to succor ensure safety and productivity in extreme environments. The hamon® shirt, made from silver conductive fibers, collects a wearer's biometric data, including heart rate, cadaver temperature and location, as well as environmental data such as humidity, temperature, noise and toxic gas levels, together with the exercise of IBM Maximo Worker Insights. By connecting to the IBM Maximo Worker Insights solution on the IBM Cloud, this data can live analyzed in near real-time, with alerts and alarms signaled on mobile devices to buy a break, change locations, etc., before overexertion or injury occur.
SmartCone and its highly portable systemSmartCone, a provider of smart, IoT-based safety and monitoring solutions for securing vulnerable and hazardous zones, great and small, is working with IBM and integrating Maximo Worker Insights into its highly portable system to monitor worker safety in the utilities industry, community traffic, construction, mining and industrial environments with stirring or hazardous no-go zones. Utilizing multi-sensors, audio/video, communication capabilities, computing and edge gateway capabilities, TheSmartCone™ system combines with IBM Maximo Worker Insights to provide supervisors and safety officers with near real-time notification and historical analytics on hazards related to falls, "man-downs," no-go zones, unreasonable temperatures and more.
About IBM Think At consider 2019, IBM will profile novel offerings, client engagements, partnerships, technology breakthroughs and developer tools that underscore how IBM and partners are changing the pass the world works. For more information, visit the IBM consider 2019 Newsroom: https://newsroom.ibm.com/think. succeed the conference on Twitter at #think2019 and @ibmlive, and fade to https://www.ibm.com/events/think/ for the complete schedule and live streaming agenda.
Guardhat, this is no ordinary arduous hat
hamon®-the highly connective AGposs fiber collects biometric data from the wearer.
CEO, Jason Lee, shows just how portable theSmartCone™ can be. (Photo by result Holleron)
IBM Corporation logo. (PRNewsfoto/IBM)
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In 2010, a mine in northern Chile collapsed, trapping 33 workers underground for more than two months. IBM is working to provide AI solutions that can help response to mine disasters. (Image: Miner Alex Vega. Hugo Infante, Chilean Gov’t via Wikipedia.)
Much has been said lately about how IBM’s cognitive exploration and content analysis platform, known as Watson, is helping major miners, such as Goldcorp and Newcrest, in a number of ways, from mine planning and operational performance optimization to sharpening takeover strategies.
A less touted, but equally helpful advantage of this and other artificial intelligence (AI) applications is the role they are playing — or expected to play— in the health and safety zone of mining companies.
For result Fawcett, a partner with IBM Global industry Services, the concede is clear. Available technologies, he tells MINING.com, fade beyond helping mining companies foretell when their equipment is going to fail, they can too monitor biometric and environmental data to identify whether employees are at risk of danger.
Data can live gathered in near existent time from wearables, smart devices, and environmental sensors to succor firms respond to problems or react to changing environmental conditions.
The problem is that many organizations finish not beget an automated safety system in place, Fawcett says. Often, they are paper-based or reckon on systems where the data is unstructured. Even when there are systems in place, they usually vary from mine to mine. Ultimately, safety departments are left with an incomplete view of incidents across their organization.
“AI has the talent to quickly consume the data regardless of source and easily provide insights on the top issues, major trends that are occurring, and partake insights on data that may beget been missed. In addition, historical data can live consumed to trend historically over time,” Fawcett notes.
IBM believes that in the “very near” future, AI will provide a complete analysis on working conditions before an employee even takes a labor order.
Fawcett believes that in the “very near” future, AI will provide a complete analysis on working conditions before an employee even takes a labor order. This will embrace a complete summary on where the assignment is going to live performed spatially, forecasted weather data and pertinent safety notices for the worker in that specific location.
“The freeze-thaw cycle is a common specimen of where they can apply spatial analytics to safety. When an employee receives a labor order where the ground may live frozen, that labor order would live accompanied by the pertinent safety notices and other events that beget happened giving the employee a pertinent picture of the work, the forecast and potential risk,” he says.
“Using this data, they can avert a lot of falls that would beget otherwise happened without that notice, ultimately resulting in smarter and safer working conditions.”
That’s why IBM is developing what it calls “Watson safe”, currently in its second angle and is expected to live ready on a platform scale in the second half of the year.
IBM is too working on extending the compass of the so-called internet of things (IoT), a system of interrelated computing devices, mechanical and digital machines, objects, people and even animals embedded with sensors, software, electronics and connectivity. These allow the system to perform better by exchanging information with other connected devices without requiring human-to-human or human-to-computer interaction.
The company has recently joined wearable technology developer Garmin to tender organizations who deploy IBM’s Maximo Worker Insights platform to receive alerts based on near real-time sensor data from workers wearing Garmin activity trackers.
By embedding the Garmin Health Companion SDK in the IBM Maximo Worker Insights platform, supervisors and safety officers can receive notifications for towering heart rate and man-down scenarios, as well as review historical analytics based on the biometric signals from Garmin wearables.
The IT giant is too partnering with Guardhat, Mitsufuji and SmartCone to succor monitor worker safety in hazardous environments.
Guardhat's KYRA IoT platform can complement the IBM Worker Insights solution to provide situational awareness to workers and company operations through the exercise of Smart PPE wearables.
Mitsufuji, in turn, has launched a novel wearable “shirt” made from silver conductive fibres that tracks data from workers' biometrics to succor ensure safety in extreme environments.
SmartCone, a provider of smart, IoT-based safety and monitoring solutions for securing vulnerable and hazardous zones, will live integrating Maximo Worker Insights into its highly portable system to monitor worker safety in the utilities industry, community traffic, construction, mining and industrial environments with stirring or hazardous no-go zones.
Response to mine disasters
IBM envisions AI being used too to help response to mine disasters. When something enjoy the recent deadly dam disaster in the Brazilian town of Brumadinho happens, everyone from national government leaders and the military to the small-town mayor and scores of volunteers forward together to respond to the event. All those people, at every level, need to communicate, partake information and coordinate their activities so that they’re doing things efficiently and not duplicating their efforts.
Many times, that doesn’t happen effectively because people can’t find or partake the information they need, when they need it.
IBM is already supporting Lightship, a company that offers an bright fields operations appliance to succor organizations navigate their data to find the necessary information to succor them figure better, safer decisions. It pulls together All of an organization’s information, such as Geographic Information System (GIS) mapping, drone photos, satellite photos and the real-time locations of people and vehicles.
In September 2018, IBM announced a novel product, IBM Db2 AI for z/OS. This artificial intelligence engine monitors data access patterns from executing SQL statements, uses machine learning algorithms to determine on optimal patterns and passes this information to the Db2 query optimizer for exercise by subsequent statements.
Machine Learning on the IBM z Platform
In May of 2018, IBM announced version 1.2 of its Machine Learning for z/OS (MLz) product. This is a hybrid zServer and cloud software suite that ingests performance data, analyzes and builds models that portray the health status of various indicators, monitors them over time and provides real-time scoring capabilities.
Several features of this product offering are aimed at supporting a community of model developers and managers. For example:
It supports multiple programming languages such as Python, Scala and R. This allows data modelers and scientists to exercise a language with which they are familiar;
A graphical user interface called the Visual Model Builder guides model developers without requiring highly-technical programming skills;
It includes multiple dashboards for monitoring model results and scoring services, as well as controlling the system configuration.
This machine learning suite was initially aimed at zServer-based analytics applications. One of the first obvious choices was zSystem performance monitoring and tuning. System Management Facility (SMF) records that are automatically generated by the operating system provide the raw data for system resource consumption such as central processor usage, I/O processing, recollection paging and the like. IBM MLz can collect and store these data over time, and build and train models of system behavior, score those behaviors, identify patterns not readily foreseen by humans, develop key performance indicators (KPIs) and then feed the model results back into the system to influence system configuration changes that can help performance.
The next step was to implement this suite to anatomize Db2 performance data. One solution, called the IBM Db2 IT Operational Analytics (Db2 ITOA) solution template, applies the machine learning technology to Db2 operational data to gain an understanding of Db2 subsystem health. It can dynamically build baselines for key performance indicators, provide a dashboard of these KPIs and give operational staff real-time insight into Db2 operations.
While general Db2 subsystem performance is an faultfinding factor in overall application health and performance, IBM estimates that the DBA back staff spends 25% or more of its time, " ... fighting access path problems which occasions performance degradation and service impact.". (See Reference 1).
AI Comes to Db2
Consider the plight of modern DBAs in a Db2 environment. In today's IT world they must back one or more ample data applications, cloud application and database services, software installation and configuration, Db2 subsystem and application performance tuning, database definition and management, disaster recovery planning, and more. Query tuning has been in actuality since the origins of the database, and DBAs are usually tasked with this as well.
The heart of query path analysis in Db2 is the Optimizer. It accepts SQL statements from applications, verifies authority to access the data, reviews the locations of the objects to live accessed and develops a list of candidate data access paths. These access paths can embrace indexes, table scans, various table unite methods and others. In the data warehouse and ample data environments there are usually additional choices available. One of these is the actuality of summary tables (sometimes called materialized query tables) that accommodate pre-summarized or aggregated data, thus allowing Db2 to avoid re-aggregation processing. Another option is the starjoin access path, common in the data warehouse, where the order of table joins is changed for performance reasons.
The Optimizer then reviews the candidate access paths and chooses the access path, "with the lowest cost." Cost in this context means a weighted summation of resource usage including CPU, I/O, recollection and other resources. Finally, the Optimizer takes the lowest cost access path, stores it in recollection (and, optionally, in the Db2 Directory) and begins access path execution.
Big data and data warehouse operations now embrace software suites that allow the industry analyst to exercise a graphical interface to build and maneuver a miniature data model of the data they wish to analyze. The packages then generate SQL statements based on the users’ requests.
The Problem for the DBA
In order to finish helpful analytics on your multiple data stores you need a helpful understanding of the data requirements, an understanding of the analytical functions and algorithms available and a high-performance data infrastructure. Regrettably, the number and location of data sources is expanding (both in size and in geography), data sizes are growing, and applications continue to proliferate in number and complexity. How should IT managers back this environment, especially with the most experienced and ripen staff nearing retirement?
Understand too that a great Part of reducing the total cost of ownership of these systems is to collect Db2 applications to flee faster and more efficiently. This usually translates into using fewer CPU cycles, doing fewer I/Os and transporting less data across the network. Since it is often difficult to even identify which applications could profit from performance tuning, one approach is to automate the detection and correction of tuning issues. This is where machine learning and artificial intelligence can live used to much effect.
Db2 12 for z/OS and artificial Intelligence
Db2 version 12 on z/OS uses the machine learning facilities mentioned above to gather and store SQL query text and access path details, as well as actual performance-related historical information such as CPU time used, elapsed times and result set sizes. This offering, described as Db2 AI for z/OS, analyzes and stores the data in machine learning models, with the model analysis results then being scored and made available to the Db2 Optimizer. The next time a scored SQL statement is encountered, the Optimizer can then exercise the model scoring data as input to its access path preference algorithm.
The result should live a reduction in CPU consumption as the Optimizer uses model scoring input to choose better access paths. This then lowers CPU costs and speeds application response times. A significant advantage is that using AI software does not require the DBA to beget data science skills or profound insights into query tuning methodologies. The Optimizer now chooses the best access paths based not only on SQL query syntax and data distribution statistics but on modelled and scored historical performance.
This can live particularly faultfinding if you store data in multiple places. For example, many analytical queries against ample data require concurrent access to sure data warehouse tables. These tables are commonly called dimension tables, and they accommodate the data elements usually used to control subsetting and aggregation. For example, in a retail environment consider a table called StoreLocation that enumerates every store and its location code. Queries against store sales data may wish to aggregate or summarize sales by Location; hence, the StoreLocation table will live used by some ample data queries. In this environment it is common to buy the dimension tables and copy them regularly to the ample data application. In the IBM world this location is the IBM Db2 Analytics Accelerator (IDAA).
Now consider about SQL queries from both operational applications, data warehouse users and ample data industry analysts. From Db2's perspective, All these queries are equal, and are forwarded to the Optimizer. However, in the case of operational queries and warehouse queries they should most likely live directed to access the StoreLocation table in the warehouse. On the other hand, the query from the industry analyst against ample data tables should probably access the copy of the table there. This results in a proliferations of potential access paths, and more labor for the Optimizer. Luckily, Db2 AI for z/OS can provide the Optimizer the information it needs to figure smart access path selections.
How It Works
The sequence of events in Db2 AI for z/OS (See Reference 2) is generally the following:
During a bind, rebind, prepare or account for operation, an SQL statement is passed to the Optimizer;
The Optimizer chooses the data access path; as the preference is made, Db2 AI captures the SQL syntax, access path preference and query performance statistics (CPU used, etc.) and passes it to a "learning task";
The learning task, which can live executed on a zIIP processor (a non-general-purpose CPU core that does not factor into software licensing charges), interfaces with the machine learning software (MLz Model Services) to store this information in a model;
As the amount of data in each model grows, the MLz Scoring Service (which too can live executed on a zIIP processor) analyzes the model data and scores the behavior;
During the next bind, rebind, prepare or explain, the Optimizer now has access to the scoring for SQL models, and makes arrogate changes to access path choices.
There are too various user interfaces that give the administrator visibility to the status of the accumulated SQL statement performance data and model scoring.
IBM's machine learning for zOS (MLz) offering is being used to much result in Db2 version 12 to help the performance of analytical queries as well as operational queries and their associated applications. This requires management attention, as you must verify that your industry is prepared to consume these ML and AI conclusions. How will you measure the costs and benefits of using machine learning? Which IT back staff must live tasked to reviewing the result of model scoring, and perhaps approving (or overriding) the results? How will you review and warrant the assumptions that the software makes about access path choices?
In other words, how well finish you know your data, its distribution, its integrity and your current and proposed access paths? This will determine where the DBAs expend their time in supporting analytics and operational application performance.
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John Campbell, IBM Db2 Distinguished EngineerFrom "IBM Db2 AI for z/OS: Boost IBM Db2 application performance with machine learning"https://www.worldofdb2.com/events/ibm-db2-ai-for-z-os-boost-ibm-db2-application-performance-with-ma
Db2 AI for z/OShttps://www.ibm.com/support/knowledgecenter/en/SSGKMA_1.1.0/src/ai/ai_home.html
See All articles by Lockwood Lyon