1) O documento discute o Oracle Event Processing (OEP) para o Oracle Java Embedded e como ele pode facilitar a captura e análise de dados em tempo real de dispositivos inteligentes.
2) O OEP para Java Embedded permite monitorar processos locais em tempo real para detectar problemas e tomar ações rápidas, além de reduzir ruídos de dados.
3) O documento fornece exemplos de como o OEP pode ser usado para análise de eventos em tempo real e tomada de decisão mais rápida.
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All kinds of data Large volumes Valuable insight, but difficult to extract (structured and unstructured data) Often extremely time sensitive Most of the vast data types portrayed here is consumer data and while the business will want to leverage Oracle Event Processing for business and application data, they are also impacted by this consumer data and information from the vast array or sensors where stream events showing temperatures in a container mid-pacific may destroy high cost food goods unless immediate action is taken or ….. For Starbucks immediately analyzing tweats after launching a new coffee, seeing spikes of negative comments, and very quickly figuring out that the negative reactions came from stores that were serving a particular warmed cheese sandwich, whose aroma did not go with the new coffee smell….. Huge ROI due to quick analysis and specific targeted response. And as you can see from the Spanish (La Caxia) bank solution, a customers Tweets are also being analzed by Oracle Event Processing and stored in Big Data to augment his preferences and influence his/her real time targetted campaigns
Everyone is talking about the Internet-of-Things, or Machine-to-Machine, or Industrial Internet these days. The very fact that we’re meeting today, is an evidence of how important it is for your business, your customers, and customers of your customers. There’ll be way more connected devices and these devices will be generating an unprecedented amount of data. Let us share with you why we strongly believe that Java is a platform perfectly suited for powering virtually any connected device, of any size and in any market.
The amount of information available to companies today is exploding, a trend frequently called big data. Information generated inside the company is increasing due to automated data collection, technologies such as RFID and GPS, web click streams, email, wikis, and the massive amounts of logs and other machine data created by technologies located inside and outside of the enterprise. For the most part, this is “data exhaust,” and it is spewing everywhere. If captured at all, it is typically filtered and either partially or never used. Organizations typically look to the traditional systems of record and BI technologies to enable decision-making. Yet within this data there is a vast amount of untapped insights that could be leveraged within IT and elsewhere in the business. The challenge has been having the ability to effectively capture, store, correlate, and analyze this data. Adding to this data are other sources of information, like watch lists, asset directories, customer data, shipping and logistics data, and web-based feeds—like real-time stock feeds, travel reservations data, and popular searches. These internal and external sources can provide added context to what’s happening in the business.The good news is that there are now ways to aggregate and understand the vast streams of machine data with methods that can scale as quickly as that data is increasing. It’s practical now to use this real-time and historical data across a broad set of venues and applications. This is the basis of operational intelligence
Key points:A survey of the M2M solutions market was conducted for Oracle in September 2012 and in April/May 2013 by Beecham Research, targeting leading M2M solution providers in North America, Europe and AsiaPac. The aim was to provide an in-depth qualitative assessment of M2M solution requirements today and how these are likely to change in the future. The main findings from the Beecham survey were as follows:1. The primary driver for M2M solutions is now enabling new services, rather than just improving operational efficiency/ cost saving 2. The highest priorities for M2M solutions are now seen as: • Ensuring end-to-end security, from the remote device through to the data center and the end user (true end-to-end)• Integration with legacy IT Systems 3. Although data storage requirements for M2M solutions have often not been huge in the past, this is changing with very large volumes of data expected in the future. Additionally, insight from real-time intelligence “can open up a whole new world of solutions”. This data will need analysing and managing. 4. These trends point towards M2M solutions becoming increasingly mission critical, with the need to minimize downtime and provide high availability solutions 5. It is considered that using the same software development environment (Java platform) for all parts of an M2M solution could be a major advantage, so long as each part of it (edge vs. central) can be optimized for its own particular requirements. 6. Cloud based services are key in M2M, greatly reducing the cost and complexity of delivering M2M solution 7. What also emerged in May 2013 study in greater detail was the need for Security of Devices and Flexibility, and Data Protection. Reinforcing the need for greater harnessing of value through applied intelligence and connected devicesNext slide: D2D gear slideOracle understands the value of data and the challenges of managing this data---this is what we call Oracle’s Internet of Things platform.
Key Points: Key Elements of Connected Intelligence-The explosion in the number of intelligent, connected devices is particularly meaningful as we explore the value of the data generated by these devices. -The data generated by these devices has to be acted upon quickly. -Three aspects of Data: Volume, Variety, Velocity: Fast Data is reacting quickly to the massive volumes of data and taking action immediately.-We want to decrease the time to reaction of the generated data by moving up the analysis of this data as close up to the devices as possible – which is where D2D becomes meaningful-As we leverage embedded OEP in the gateways and the data centers rather than wait to analyze the data from these devices all the way back in enterprise repositories, there is golden opportunity for new services and revenue streams.Next Slide: Builds into the value of data becoming less relevant with time delays
Key Points:-The obstacles to achieving faster data can be outlined in the steps it takes to look at and event and take the correction action.-There’s latencies at each and every step. How long does it take you to capture your data – analyze it and finally take the right action? -Fast data is about shortening the gaps within each step and thereby reducing the amount of time – and consequently producing greater value from it by acting right away. Next slide: Lets look at Oracle Event Processing as a means to analyze data and drive business results
Key PointsIntelligence is most valued from real-time data Tracking and analyzing (processing) streams of information (data) about things that happen (events) and deriving an immediate Business decision from themCombines data from multiple streaming event sources to infer event patterns that suggest more complicated Business circumstances, Opportunities and Threats, and respond to them Immediately (not seconds, or milliseconds but Microseconds)Handle Events happening across the various layers of an organization as sales leads, orders or customer service calls. Or, they may be news items, text messages, social media posts, stock market feeds, traffic reports, weather reports, “Internet of Things” Sensor data or many other kinds of data (Unstructured Fast Data).Give organizations a new way to analyze patterns in real-time, and help the business side communicate better with IT and service departmentsNext slide- Why is OEP for java embedded important?OEP for Oracle Java Embedded has the ability to handle millions of events per second with microseconds of processing latencies. This is achieved through a complete layered solution, not only with a design focus on high performance event processing use cases, but also a tight integration with the industry-leading embedded Java application platform.
Device ConvergenceIn today’s consumer-facing technology sphere, there is virtually limitless appetite for connectivity.Wherever they go, people increasingly expect access to information, entertainment, and each other viaa profusion of devices.Many business and industry environment is not so different. Connected devices exchanging information createleaner, more efficient processes. With the possibilities apparent, a new generation of software isarriving, including development and delivery models, application marketplaces, and services. And moreindustrial devices are equipped with enough processing power and connectivity to make themintelligent “actors” in their environments—for example, by initiating service and maintenance alerts.SecurityDistributed environments pose the challenge of keeping devices connected, oftenwirelessly, while maintaining security to protect sensitive data, proprietary process designs andintellectual property, and transaction information.
The rapid growth in the Internet of Things is driving demand for increased intelligence in embedded devicesMinimal time-to-market is key to market growth for M2M and IoT marketsEffective intelligent management of data and devices is essentialM2M and IoT is being driven partly by IPV6 address availability for a multitude of connected devicesOracle’s 1st Integrated Java Product Suite for Device-to-Data CenterJES is based upon proven and reliable existing Java Products Java SE Embedded, Java DB and Glassfish Java Embedded ProfileJava SE Embedded – provides runtime for Java applicationGlassFish Embedded – provides web server and client capability JavaDB – provides local storage with full SQL DB support
Key Points Benefits of OEP for Embedded for Connected Intelligence (gateway)-High-speed, real-time data capture and analysis helps mitigate the risk of down-time and helps with continuous process improvement-Enables local real-time process monitoring to detect degradation of performance, thus helping with initiation of alerts or requests for operations and maintenance actions-Significantly reduces noise to signal ratio of data reaching the server, enabling savings in bandwidth and scalability costs-Faster time to market for devices and easy over-the-air updates post-deploymentNext slide- Use cases (Home Automation & Gateway)OEP for Oracle Java Embedded targets a wealth of industries and functional areas. Following are some use cases:Industrial Automation: High speed data collection and analysis, local storage and analysis, filtering, correlation, pattern matching.Management appliances (home automation) : Ability to detect events from various sub-systems and determine downstream processTransportation & Telemetry: Location tracking, container content monitoring, intrusion detection, temperature and pressure monitoringHealthcare: Data evaluation, analysis, monitoring, automatic alerts and care-flow processingSmart Retail Vending Machines: Inventory management, demand-based handling and pricingLets look at home automation and see how Java embedded and OEP drive value
Key Points Benefits of OEP for Embedded for Connected Intelligence (gateway)-High-speed, real-time data capture and analysis helps mitigate the risk of down-time and helps with continuous process improvement-Enables local real-time process monitoring to detect degradation of performance, thus helping with initiation of alerts or requests for operations and maintenance actions-Significantly reduces noise to signal ratio of data reaching the server, enabling savings in bandwidth and scalability costs-Faster time to market for devices and easy over-the-air updates post-deploymentNext slide- Use cases (Home Automation & Gateway)OEP for Oracle Java Embedded targets a wealth of industries and functional areas. Following are some use cases:Industrial Automation: High speed data collection and analysis, local storage and analysis, filtering, correlation, pattern matching.Management appliances (home automation) : Ability to detect events from various sub-systems and determine downstream processTransportation & Telemetry: Location tracking, container content monitoring, intrusion detection, temperature and pressure monitoringHealthcare: Data evaluation, analysis, monitoring, automatic alerts and care-flow processingSmart Retail Vending Machines: Inventory management, demand-based handling and pricingLets look at home automation and see how Java embedded and OEP drive value
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