Leveraging NoSQL Database Technology to Implement Real-time Data Architecture...Impetus Technologies
Impetus webcast "Leveraging NoSQL Database Technology to Implement Real-time Data Architectures” available at http://bit.ly/1g6Eaj4
This webcast:
• Presents trade-offs of using different approaches to achieve a real-time architecture
• Closely examines an implementation of a NoSQL based real-time architecture
• Shares specific capabilities offered by NoSQL Databases that enable cost and reliability advantages over other techniques
Oracle Cloud : Big Data Use Cases and ArchitectureRiccardo Romani
Oracle Itay Systems Presales Team presents : Big Data in any flavor, on-prem, public cloud and cloud at customer.
Presentation done at Digital Transformation event - February 2017
Presentación sobre el lifecycle management, y cómo desde la consola de Enterprise Cloud Control podemos ser capaces de gestionar una base de datos de principio a fin.
Leveraging NoSQL Database Technology to Implement Real-time Data Architecture...Impetus Technologies
Impetus webcast "Leveraging NoSQL Database Technology to Implement Real-time Data Architectures” available at http://bit.ly/1g6Eaj4
This webcast:
• Presents trade-offs of using different approaches to achieve a real-time architecture
• Closely examines an implementation of a NoSQL based real-time architecture
• Shares specific capabilities offered by NoSQL Databases that enable cost and reliability advantages over other techniques
Oracle Cloud : Big Data Use Cases and ArchitectureRiccardo Romani
Oracle Itay Systems Presales Team presents : Big Data in any flavor, on-prem, public cloud and cloud at customer.
Presentation done at Digital Transformation event - February 2017
Presentación sobre el lifecycle management, y cómo desde la consola de Enterprise Cloud Control podemos ser capaces de gestionar una base de datos de principio a fin.
Hadoop World 2011: Unlocking the Value of Big Data with Oracle - Jean-Pierre ...Cloudera, Inc.
Analyzing new and diverse digital data streams can reveal new sources of economic value, provide fresh insights into customer behavior and identify market trends early on. But this influx of new data can create challenges for IT departments. To derive real business value from Big Data, you need the right tools to capture and organize a wide variety of data types from different sources, and to be able to easily analyze it within the context of all your enterprise data. Attend this session to learn how Oracle’s end-to-end value chain for Big Data can help you unlock the value of Big Data.
Integrating and Analyzing Data from Multiple Manufacturing Sites using Apache...DataWorks Summit
In this talk Mark Baker (CSL) will show how CSL Behring is Integrating and Analyzing Data from Multiple Manufacturing Sites using Apache NIFI to a central Hadoop data lake at CSL Behring
The challenge of merging data from disparate systems has been a leading driver behind investments in data warehousing systems, as well as, in Hadoop. While data warehousing solutions are ready-built for RDBMS integration, Hadoop adds the benefits of infinite and economical scale – not to mention the variety of structured and non-structured formats that it can handle. Whether using a data warehouse or Hadoop or both, physical data movement and consolidation is the primary method of integration.
There may also be challenges with synchronizing rapidly changing data from a system of record to a consolidated Hadoop platform .
This introduces the need for “data federation” , where data is integrated without copying data between systems.
For historical/batch data use cases there is a replication of data across remote data hubs into a central data lake using Apache NIFI.
We will demo using Apache Zeppelin for analyzing data using Apache Spark and Apache HIVE.
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...MSAdvAnalytics
Lance Olson. Cortana Analytics is a fully managed big data and advanced analytics suite that helps you transform your data into intelligent action. Come to this two-part session to learn how you can do "big data" processing and storage in Cortana Analytics. In the first part, we will provide an overview of the processing and storage services. We will then talk about the patterns and use cases which make up most big data solutions. In the second part, we will go hands-on, showing you how to get started today with writing batch/interactive queries, real-time stream processing, or NoSQL transactions all over the same repository of data. Crunch petabytes of data by scaling out your computation power to any sized cluster. Store any amount of unstructured data in its native format with no limits to file or account size. All of this can be done with no hardware to acquire or maintain and minimal time to setup giving you the value of "big data" within minutes. Go to https://channel9.msdn.com/ to find the recording of this session.
According to Gartner, organizations can reduce their database spend by up to 80% by deploying EDB Postgres in place of traditional database solutions like Oracle. Nevertheless, the perceived risks associated with migrating from Oracle to an open source-based alternative prevents many organizations from trying.
Review this presentation to learn some of EDB Postgres Enterprise’s more important features and techniques employed to reduce migration risk.
This presentation will be valuable to organizations researching Postgres, as well as current Oracle customers considering migrating to an open source-based database management system such as EDB Postgres. It highlights key points for both business and technical decision-makers and influencers.
Exploring microservices in a Microsoft landscapeAlex Thissen
Presentation for Dutch Microsoft TechDays 2015 with Marcel de Vries:
During this session we will take a look at how to realize a Microservices architecture (MSA) using the latest Microsoft technologies available. We will discuss some fundamental theories behind MSA and show you how this can actually be realized with Microsoft technologies such as Azure Service Fabric. This session is a real must-see for any developer that wants to stay ahead of the curve in modern architectures.
Accelerating Business Intelligence Solutions with Microsoft Azure passJason Strate
Business Intelligence (BI) solutions need to move at the speed of business. Unfortunately, roadblocks related to availability of resources and deployment often present an issue. What if you could accelerate the deployment of an entire BI infrastructure to just a couple hours and start loading data into it by the end of the day. In this session, we'll demonstrate how to leverage Microsoft tools and the Azure cloud environment to build out a BI solution and begin providing analytics to your team with tools such as Power BI. By end of the session, you'll gain an understanding of the capabilities of Azure and how you can start building an end to end BI proof-of-concept today.
MOUG17 Keynote: Oracle OpenWorld Major AnnouncementsMonica Li
Midwest Oracle Users Group Training Day 2017 Presentation by Rich Niemiec, Chief Innovation Officer at Viscosity North America.
Catch up on OOW17's top announcements in this 1 hour presentation.
This talk provides an architecture overview of data-centric microservices illustrated with an example application. The following Microservices concepts are illustrated - domain driven design, event-driven services, Saga transactions, Application tracing and Health monitoring with different microservices using a variety of data types supported in the database - business data, documents, spatial, graph, and events. A running example of a mobile food delivery application (called GrubDash) is used, with a hands-on-lab that is available for attendees to work through on the Oracle Cloud after these sessions. The rest of the talks will build upon this Microservices architecture framework.
Oracle Data Integration overview, vision and roadmap. Covers GoldenGate, Data Integrator (ODI), Data Quality (EDQ), Metadata Management (MM) and Big Data Preparation (BDP)
Securing Data in Hybrid on-premise and Cloud Environments Using Apache RangerDataWorks Summit
Companies are increasingly moving to the cloud to store and process data. One of the challenges companies have is in securing data across hybrid environments with easy way to centrally manage policies. In this session, we will talk through how companies can use Apache Ranger to protect access to data both in on-premise as well as in cloud environments. We will go into details into the challenges of hybrid environment and how Ranger can solve it. We will also talk through how companies can further enhance the security by leveraging Ranger to anonymize or tokenize data while moving into the cloud and de-anonymize dynamically using Apache Hive, Apache Spark or when accessing data from cloud storage systems. We will also deep dive into the Ranger’s integration with AWS S3, AWS Redshift and other cloud native systems. We will wrap it up with an end to end demo showing how policies can be created in Ranger and used to manage access to data in different systems, anonymize or de-anonymize data and track where data is flowing.
Things Every Oracle DBA Needs to Know About the Hadoop Ecosystem 20170527Zohar Elkayam
Big data is one of the biggest buzzwords in today's market. Terms such as Hadoop, HDFS, YARN, Sqoop, and non-structured data have been scaring DBAs since 2010, but where does the DBA team really fit in?
In this session, we will discuss everything database administrators and database developers need to know about big data. We will demystify the Hadoop ecosystem and explore the different components. We will learn how HDFS and MapReduce are changing the data world and where traditional databases fit into the grand scheme of things. We will also talk about why DBAs are the perfect candidates to transition into big data and Hadoop professionals and experts.
This is the presentation I gave in Kscope17, on June 27, 2017.
Oracle Solaris Build and Run Applications Better on 11.3OTN Systems Hub
Build and Run Applications Better on Oracle Solaris 11.3
Tech Day, NYC
Liane Praza, Senior Principal Software Engineer
Ikroop Dhillon, Principal Product Manager
June, 2016
For decades developers and DBAs have battled over who controls the world. With each new development paradigm the battle flares again as developers push DBAs to adopt and support new data structures (JSON), new APIs (REST services), new technologies (In-Memory) and new platforms (Cloud). In this session, Gerald Venzl takes on the role of lead developer on a project to deploy a RESTful web-based application for a new coffeeshop chain, while Maria Colgan takes on the role of the DBA. Through the use of live demos, they learn to work together to find a solution that will allow them to embrace a more agile development approach, as well as the latest technology trends without exposing the business to painful availability or security vulnerabilities.
Hadoop World 2011: Unlocking the Value of Big Data with Oracle - Jean-Pierre ...Cloudera, Inc.
Analyzing new and diverse digital data streams can reveal new sources of economic value, provide fresh insights into customer behavior and identify market trends early on. But this influx of new data can create challenges for IT departments. To derive real business value from Big Data, you need the right tools to capture and organize a wide variety of data types from different sources, and to be able to easily analyze it within the context of all your enterprise data. Attend this session to learn how Oracle’s end-to-end value chain for Big Data can help you unlock the value of Big Data.
Integrating and Analyzing Data from Multiple Manufacturing Sites using Apache...DataWorks Summit
In this talk Mark Baker (CSL) will show how CSL Behring is Integrating and Analyzing Data from Multiple Manufacturing Sites using Apache NIFI to a central Hadoop data lake at CSL Behring
The challenge of merging data from disparate systems has been a leading driver behind investments in data warehousing systems, as well as, in Hadoop. While data warehousing solutions are ready-built for RDBMS integration, Hadoop adds the benefits of infinite and economical scale – not to mention the variety of structured and non-structured formats that it can handle. Whether using a data warehouse or Hadoop or both, physical data movement and consolidation is the primary method of integration.
There may also be challenges with synchronizing rapidly changing data from a system of record to a consolidated Hadoop platform .
This introduces the need for “data federation” , where data is integrated without copying data between systems.
For historical/batch data use cases there is a replication of data across remote data hubs into a central data lake using Apache NIFI.
We will demo using Apache Zeppelin for analyzing data using Apache Spark and Apache HIVE.
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...MSAdvAnalytics
Lance Olson. Cortana Analytics is a fully managed big data and advanced analytics suite that helps you transform your data into intelligent action. Come to this two-part session to learn how you can do "big data" processing and storage in Cortana Analytics. In the first part, we will provide an overview of the processing and storage services. We will then talk about the patterns and use cases which make up most big data solutions. In the second part, we will go hands-on, showing you how to get started today with writing batch/interactive queries, real-time stream processing, or NoSQL transactions all over the same repository of data. Crunch petabytes of data by scaling out your computation power to any sized cluster. Store any amount of unstructured data in its native format with no limits to file or account size. All of this can be done with no hardware to acquire or maintain and minimal time to setup giving you the value of "big data" within minutes. Go to https://channel9.msdn.com/ to find the recording of this session.
According to Gartner, organizations can reduce their database spend by up to 80% by deploying EDB Postgres in place of traditional database solutions like Oracle. Nevertheless, the perceived risks associated with migrating from Oracle to an open source-based alternative prevents many organizations from trying.
Review this presentation to learn some of EDB Postgres Enterprise’s more important features and techniques employed to reduce migration risk.
This presentation will be valuable to organizations researching Postgres, as well as current Oracle customers considering migrating to an open source-based database management system such as EDB Postgres. It highlights key points for both business and technical decision-makers and influencers.
Exploring microservices in a Microsoft landscapeAlex Thissen
Presentation for Dutch Microsoft TechDays 2015 with Marcel de Vries:
During this session we will take a look at how to realize a Microservices architecture (MSA) using the latest Microsoft technologies available. We will discuss some fundamental theories behind MSA and show you how this can actually be realized with Microsoft technologies such as Azure Service Fabric. This session is a real must-see for any developer that wants to stay ahead of the curve in modern architectures.
Accelerating Business Intelligence Solutions with Microsoft Azure passJason Strate
Business Intelligence (BI) solutions need to move at the speed of business. Unfortunately, roadblocks related to availability of resources and deployment often present an issue. What if you could accelerate the deployment of an entire BI infrastructure to just a couple hours and start loading data into it by the end of the day. In this session, we'll demonstrate how to leverage Microsoft tools and the Azure cloud environment to build out a BI solution and begin providing analytics to your team with tools such as Power BI. By end of the session, you'll gain an understanding of the capabilities of Azure and how you can start building an end to end BI proof-of-concept today.
MOUG17 Keynote: Oracle OpenWorld Major AnnouncementsMonica Li
Midwest Oracle Users Group Training Day 2017 Presentation by Rich Niemiec, Chief Innovation Officer at Viscosity North America.
Catch up on OOW17's top announcements in this 1 hour presentation.
This talk provides an architecture overview of data-centric microservices illustrated with an example application. The following Microservices concepts are illustrated - domain driven design, event-driven services, Saga transactions, Application tracing and Health monitoring with different microservices using a variety of data types supported in the database - business data, documents, spatial, graph, and events. A running example of a mobile food delivery application (called GrubDash) is used, with a hands-on-lab that is available for attendees to work through on the Oracle Cloud after these sessions. The rest of the talks will build upon this Microservices architecture framework.
Oracle Data Integration overview, vision and roadmap. Covers GoldenGate, Data Integrator (ODI), Data Quality (EDQ), Metadata Management (MM) and Big Data Preparation (BDP)
Securing Data in Hybrid on-premise and Cloud Environments Using Apache RangerDataWorks Summit
Companies are increasingly moving to the cloud to store and process data. One of the challenges companies have is in securing data across hybrid environments with easy way to centrally manage policies. In this session, we will talk through how companies can use Apache Ranger to protect access to data both in on-premise as well as in cloud environments. We will go into details into the challenges of hybrid environment and how Ranger can solve it. We will also talk through how companies can further enhance the security by leveraging Ranger to anonymize or tokenize data while moving into the cloud and de-anonymize dynamically using Apache Hive, Apache Spark or when accessing data from cloud storage systems. We will also deep dive into the Ranger’s integration with AWS S3, AWS Redshift and other cloud native systems. We will wrap it up with an end to end demo showing how policies can be created in Ranger and used to manage access to data in different systems, anonymize or de-anonymize data and track where data is flowing.
Things Every Oracle DBA Needs to Know About the Hadoop Ecosystem 20170527Zohar Elkayam
Big data is one of the biggest buzzwords in today's market. Terms such as Hadoop, HDFS, YARN, Sqoop, and non-structured data have been scaring DBAs since 2010, but where does the DBA team really fit in?
In this session, we will discuss everything database administrators and database developers need to know about big data. We will demystify the Hadoop ecosystem and explore the different components. We will learn how HDFS and MapReduce are changing the data world and where traditional databases fit into the grand scheme of things. We will also talk about why DBAs are the perfect candidates to transition into big data and Hadoop professionals and experts.
This is the presentation I gave in Kscope17, on June 27, 2017.
Oracle Solaris Build and Run Applications Better on 11.3OTN Systems Hub
Build and Run Applications Better on Oracle Solaris 11.3
Tech Day, NYC
Liane Praza, Senior Principal Software Engineer
Ikroop Dhillon, Principal Product Manager
June, 2016
For decades developers and DBAs have battled over who controls the world. With each new development paradigm the battle flares again as developers push DBAs to adopt and support new data structures (JSON), new APIs (REST services), new technologies (In-Memory) and new platforms (Cloud). In this session, Gerald Venzl takes on the role of lead developer on a project to deploy a RESTful web-based application for a new coffeeshop chain, while Maria Colgan takes on the role of the DBA. Through the use of live demos, they learn to work together to find a solution that will allow them to embrace a more agile development approach, as well as the latest technology trends without exposing the business to painful availability or security vulnerabilities.
Engagiert gegen Rechts - Report über wirkungsvolles zivilgesellschaftliches E...PHINEO gemeinnützige AG
Zahlreiche Initiativen in Deutschland engagieren sich auf vielfältigste Weise gegen Rechtsextremismus. Wir stellen 17 Musterbeispiele guter Praxis vor, die hier herausragende Arbeit leisten und nachhaltige Veränderungen bewirken können.
Rapport om seksuell trakassering i online dataspillkristineask
"Bug or feature?" Seksuell trakassering i online dataspill. En forskningsrapport skrevet av Kristine Ask og Stine H. Bang Svendsen. Prosjekt finansiert av Rådet for Anvendt Medieforskning og utført ved NTNU.
Catalog thiết bị đóng cắt Fuji Electric - Air Circuit Breakers DW Series
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CTY TNHH HẠO PHƯƠNG - Nhà phân phối chính thức các thiết bị điện công nghiệp và tự động hóa của hãng FUJI ELECTRIC JAPAN tại Việt Nam
Xem chi tiết các sản phẩm Fuji Electric tại
http://haophuong.com/b1033533/fuji-electric
Cloudera Altus: Big Data in the Cloud Made EasyCloudera, Inc.
Cloudera Altus makes it easier for data engineers, ETL developers, and anyone who regularly works with raw data to process that data in the cloud efficiently and cost effectively. In this webinar we introduce our new platform-as-a-service offering and explore challenges associated with data processing in the cloud today, how Altus abstracts cluster overhead to deliver easy, efficient data processing, and unique features and benefits of Cloudera Altus.
Turning Data into Business Value with a Modern Data PlatformCloudera, Inc.
3 Things to Learn About:
-Real-time analytics and data in motion
-Self-service access for SQL analysts and data scientists alike
-Public cloud and hybrid infrastructure
NoSQL Databases for Enterprises - NoSQL Now Conference 2013Dave Segleau
Talk delivered at Dataversity NoSQL Now! Conference in San Jose, August 2013. Describes primary NoSQL functionality and the key features and concerns that Enterprises should consider when choosing a NoSQL technology provider.
Oracle Openworld Presentation with Paul Kent (SAS) on Big Data Appliance and ...jdijcks
Learn about the benefits of Oracle Big Data Appliance and how it can drive business value underneath applications and tools. This includes a section by Paul Kent, VP Big Data SAS describing how SAS runs well on Oracle Engineered Systems and on Oracle Big Data Appliance specifically.
Best Practices for Monitoring Cloud NetworksThousandEyes
Slides from webinar of Wednesday March 7th 2018 presented by Ian Waters and Tim Hale from ThousandEyes on how to adopt a Cloud Readiness Lifecycle methodology to monitoring cloud networks.
Data Driven With the Cloudera Modern Data Warehouse 3.19.19Cloudera, Inc.
In this session, we will cover how to move beyond structured, curated reports based on known questions on known data, to an ad-hoc exploration of all data to optimize business processes and into the unknown questions on unknown data, where machine learning and statistically motivated predictive analytics are shaping business strategy.
Oracle Big Data Appliance and Big Data SQL for advanced analyticsjdijcks
Overview presentation showing Oracle Big Data Appliance and Oracle Big Data SQL in combination with why this really matters. Big Data SQL brings you the unique ability to analyze data across the entire spectrum of system, NoSQL, Hadoop and Oracle Database.
Intel and Cloudera: Accelerating Enterprise Big Data SuccessCloudera, Inc.
The data center has gone through several inflection points in the past decades: adoption of Linux, migration from physical infrastructure to virtualization and Cloud, and now large-scale data analytics with Big Data and Hadoop.
Please join us to learn about how Cloudera and Intel are jointly innovating through open source software to enable Hadoop to run best on IA (Intel Architecture) and to foster the evolution of a vibrant Big Data ecosystem.
Manufacturers have an abundance of data, whether from connected sensors, plant systems, manufacturing systems, claims systems and external data from industry and government. Manufacturers face increased challenges from continually improving product quality, reducing warranty and recall costs to efficiently leveraging their supply chain. For example, giving the manufacturer a complete view of the product and customer information integrating manufacturing and plant floor data, with as built product configurations with sensor data from customer use to efficiently analyze warranty claim information to reduce detection to correction time, detect fraud and even become proactive around issues requires a capable enterprise data hub that integrates large volumes of both structured and unstructured information. Learn how an enterprise data hub built on Hadoop provides the tools to support analysis at every level in the manufacturing organization.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Cassandra Summit 2014: Internet of Complex Things Analytics with Apache Cassa...DataStax Academy
Speaker: Mohammed Guller, Application Architect & Lead Developer at Glassbeam.
Learn how Cassandra can be used to build a multi-tenant solution for analyzing operational data from Internet of Complex Things (IoCT). IoCT includes complex systems such as computing, storage, networking and medical devices. In this session, we will discuss why Glassbeam migrated from a traditional RDBMS-based architecture to a Cassandra-based architecture. We will discuss the challenges with our first-generation architecture and how Cassandra helped us overcome those challenges. In addition, we will share our next-gen architecture and lessons learned.
Watch a replay of the webinar: https://www.youtube.com/watch?v=BtzPgLBy56w
451 Research and NuoDB outline the key database criteria for cloud applications. Explore how applications deployed in the cloud require a combination of standard functionality, such as ANSI SQL, and new capabilities specifically required to take full advantage of cloud economics, such as elastic scalability and continuous availability.
MongoDB IoT City Tour STUTTGART: Hadoop and future data management. By, ClouderaMongoDB
Bernard Doering, Senior Slaes Director DACH, Cloudera.
Hadoop and the Future of Data Management. As Hadoop takes the data management market by storm, organisations are evolving the role it plays in the modern data centre. Explore how this disruptive technology is quickly transforming an industry and how you can leverage it today, in combination with MongoDB, to drive meaningful change in your business.
3 Things to Learn:
-How data is driving digital transformation to help businesses innovate rapidly
-How Choice Hotels (one of largest hoteliers) is using Cloudera Enterprise to gain meaningful insights that drive their business
-How Choice Hotels has transformed business through innovative use of Apache Hadoop, Cloudera Enterprise, and deployment in the cloud — from developing customer experiences to meeting IT compliance requirements
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaCloudera, Inc.
Transitioning to a Big Data architecture is a big step; and the complexity of moving existing analytical services onto modern platforms like Cloudera, can seem overwhelming.
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.
The coming years will be full of big changes in enterprise analytics and Data Architecture. William will kick off the fourth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
Maximizing Oil and Gas (Data) Asset Utilization with a Logical Data Fabric (A...Denodo
Watch full webinar here: https://bit.ly/3g9PlQP
It is no news that Oil and Gas companies are constantly faced with immense pressure to stay competitive, especially in the current climate while striving towards becoming data-driven at the heart of the process to scale and gain greater operational efficiencies across the organization.
Hence, the need for a logical data layer to help Oil and Gas businesses move towards a unified secure and governed environment to optimize the potential of data assets across the enterprise efficiently and deliver real-time insights.
Tune in to this on-demand webinar where you will:
- Discover the role of data fabrics and Industry 4.0 in enabling smart fields
- Understand how to connect data assets and the associated value chain to high impact domain areas
- See examples of organizations accelerating time-to-value and reducing NPT
- Learn best practices for handling real-time/streaming/IoT data for analytical and operational use cases
Future-Proof Your Streaming Analytics Architecture- StreamAnalytix WebinarImpetus Technologies
Future-Proof Your Streaming Analytics Architecture- StreamAnalytix Webinar
View the webcast on http://bit.ly/1HFD8YR
The speakers from Forrester and Impetus talk about the options and optimal architecture to incorporate real-time insights into your apps that provisions benefitting from future innovation also.
Impetus White Paper- Handling Data Corruption in ElasticsearchImpetus Technologies
This white paper focuses on handling data corruption in Elasticsearch. It describes how to recover data from corrupted indices of Elasticsearch and re-index that data in a new index. The paper also guides you about Lucene’s index terminology
Deep Learning: Evolution of ML from Statistical to Brain-like Computing- Data...Impetus Technologies
Presentation on 'Deep Learning: Evolution of ML from Statistical to Brain-like Computing'
Speaker- Dr. Vijay Srinivas Agneeswaran,Director, Big Data Labs, Impetus
The main objective of the presentation is to give an overview of our cutting edge work on realizing distributed deep learning networks over GraphLab. The objectives can be summarized as below:
- First-hand experience and insights into implementation of distributed deep learning networks.
- Thorough view of GraphLab (including descriptions of code) and the extensions required to implement these networks.
- Details of how the extensions were realized/implemented in GraphLab source – they have been submitted to the community for evaluation.
- Arrhythmia detection use case as an application of the large scale distributed deep learning network.
SPARK USE CASE- Distributed Reinforcement Learning for Electricity Market Bi...Impetus Technologies
SPARK SUMMIT SESSION -
A majority of the electricity in the U.S. is traded in independent system operator (ISO) based wholesale markets. ISO-based markets typically function in a two-step settlement process with day-ahead (DA) financial settlements followed by physical real-time (spot) market settlements for electricity. In this work, we focus on obtaining equilibrium bidding strategies for electricity generators in DA markets. Electricity prices in DA markets are determined by the ISO, which matches competing supply offers from power generators with demand bids from load serving entities. Since there are multiple generators competing with one another to supply power, this can be modeled as a competitive Markov decision problem, which we solve using a reinforcement learning approach. For power networks of realistic sizes, the state-action space could explode, making the RL procedure computationally intensive. This has motivated us to solve the above problem over Spark. The talk provides the following takeaways:
1. Modeling the day-ahead market as a Markov decision process
2. Code sketches to show the markov decision process solution over Spark and Mahout over Apache Tez
3. Performance results comparing Mahout over Apache Tez and Spark.
Real-time Streaming Analytics: Business Value, Use Cases and Architectural Co...Impetus Technologies
Impetus webcast ‘Real-time Streaming Analytics: Business Value, Use Cases and Architectural Considerations’ available at http://bit.ly/1i6OrwR
The webinar talks about-
• How business value is preserved and enhanced using Real-time Streaming Analytics with numerous use-cases in different industry verticals
• Technical considerations for IT leaders and implementation teams looking to integrate Real-time Streaming Analytics into enterprise architecture roadmap
• Recommendations for making Real-time Streaming Analytics – real – in your enterprise
• Impetus StreamAnalytix – an enterprise ready platform for Real-time Streaming Analytics
Maturity of Mobile Test Automation: Approaches and Future Trends- Impetus Web...Impetus Technologies
Impetus webcast " Maturity of Mobile Test Automation: Approaches and Future Trends " available at http://lf1.me/Pxb/
This Impetus webcast talks about:
• Mobile test automation challenges
• Evolution of test automation challenges from Unit tests to image based and object comparison methods
• What next?
• Impetus solution approach for comprehensive mobile testing automation
The Shared Elephant - Hadoop as a Shared Service for Multiple Departments – I...Impetus Technologies
For Impetus’ White Papers archive, visit- http://lf1.me/drb/
This white paper talks about the design considerations for enterprises to run Hadoop as a shared service for multiple departments.
As Hadoop becomes more mainstream and indispensable to enterprises, it is imperative that they build, operate and scale shared Hadoop clusters. The design considerations discussed in this paper will help enterprises accomplish the essential mission of running multi-tenant, multi-use Hadoop clusters at scale.
The white paper talks about Identity, Security, Resource Sharing, Monitoring and Operations on the Central Service.
For Impetus’ White Papers archive, visit- http://lf1.me/drb/
Performance Testing of Big Data Applications - Impetus WebcastImpetus Technologies
Impetus webcast "Performance Testing of Big Data Applications" available at http://lf1.me/cqb/
This Impetus webcast talks about:
• A solution approach to measure performance and throughput of Big Data applications
• Insights into areas to focus for increasing the effectiveness of Big Data performance testing
• Tools available to address Big Data specific performance related challenges
Real-time Predictive Analytics in Manufacturing - Impetus WebinarImpetus Technologies
Impetus webcast "Real-time Predictive Analytics in Manufacturing" available at http://lf1.me/hqb/
This Impetus webcast talks about:
• The business value of predictive analytics
• How real-time analytics is enabling ‘intelligent-data’ driven manufacturing
• A Reference Architecture and real world examples based on the experiences of Impetus Big Data architects
• A step-by-step guide for successfully implementing a predictive analytics solution
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
So if we take our examples from the previous slide….Healthcare & Retail is mostly a batch oriented process.Location based is mostly a real time service.Each has specific requirements around how they use and process the data. Depending on how you want to use and process the data, you need to choose the proper technology to store/acquire that data…
Given those scenarios, here's how they might be storage/managed. HDFS is a great distributed file system. Parallel, highly scalable. However, it’s tuned primarily for bulk sequential read/write of file blocks. There are no indices for fast access to specific data records, it’s not well suited for lots of small files or updating files that have already been written. Primarily a batch system, write lots of data, then read it all in parallel over and over. NoSQL DB is a distributed key-value database. It has indices. It’s designed for high volume reads and writes of simple data. It’s not tuned for reading/writing huge files – use a file system for that.
Bottom line: NoSQL is about “data management scalability at cost” first and foremost. There are some technical features that are also important, but they come secondary. With enough effort (HW and SW) you can solve most of the technical problems with RDBMS systems. However, the whole reason that NoSQL was invented was to deal with the fact that it’s too expensive to manage Big Data using general purpose RDBMS systems. Regarding CAP: http://en.wikipedia.org/wiki/CAP_theoremThe CAP theorem, also known as Brewer's theorem, states that it is impossible for a distributed computer system to simultaneously provide all three of the following guarantees:Consistency (all nodes see the same data at the same time)Availability (a guarantee that every request receives a response about whether it was successful or failed)Partition tolerance (the system continues to operate despite arbitrary message loss)According to the theorem, a distributed system can satisfy any two of these guarantees at the same time, but not all three. RDBMS products focus on CA, where as NoSQL products focus on AP.
Cox Communications. 128-node Hadoop cluster. Home-grown distributed key-value storage using Berkeley DB. Would have used NoSQL DB if it had been available 2-3 yrs ago.
Cox Communications. 128-node Hadoop cluster. Home-grown distributed key-value storage using Berkeley DB. Would have used NoSQL DB if it had been available 2-3 yrs ago.
This slide shows the master-slave architecture of Oracle NoSQL DB. Master receives the write and it asynchronously replicate the data to the other replica-nodes.
Oracle NoSQL DB uses simple, understandable k-v pairs, simple get/insert/update/delete operations and ACID transactions. Different than SQL in an RDBMS, but the model and behavior is very familiar to application developers.Think of keys as a directory structure: multiple parts, allowing you to traverse the hierarchy. Major Key determines where the data is stored (which shard). Keys (M+m) are unique, only one value per unique Key. Minor Key allows you to have multiple records for a given Major Key. Keys are simple strings. Value is a byte string. It’s anything that you want it to be. The application knows what the structure and content of the value is. Support for a flexible data serialization format will be available in future releases (Apache Avro http://en.wikipedia.org/wiki/Apache_Avro).
This is basically a summary slide, highlighting the features of Oracle NoSQL Database, especially the that we think set us apart from some of the other products that are out on the market. General Purpose: What we mean here is that Oracle NoSQL DB is built as a general purpose scalable, highly reliable NoSQL database. Several of the open source NoSQL databases on the market were built specifically to solve the technical problems at a given company – Voldemort was built by LinkedIn, Dynamo was built by Amazon, Big Table was built by Google – which can trend to affect the technical direction and design decisions for those products. That is not the case with Oracle NoSQL Database. Reliable: Unlike most of the NoSQL databases out there, which are inventing both storage and distributed data management, Oracle NoSQL Database uses Berkeley DB Java Edition for key-value storage and replication on the storage nodes. BDB has been running large production applications for many years and is a proven, reliable, scalable storage system.
Keep the cluster investment at workMost bang for your buckTraining NeededMultiple Management ToolsRapidly, automatically or rule based single click provisioning of Big Data ClustersMeasure the boost provided by Clusters/Grids to your business data processing capabilities. Need to change your choice of cluster software at any point of time when you feel that it is not sufficiently delivering to your needsManage big data solution from a single cluster management software umbrellaIT & System Administrators wantConsistent and easy to use provisioning, management & monitoring toolsCreate less disruption in the stack, reuse technology investmentsExtensibility, keep the same tooling when adding new big data technologies to the stackReduced outage timesReduced time to scale & production
Cluster Analytics – Cross Cluster AnalyticsOptimizationsSelf healing capabilitiesFail Safe for false negatives/positivesAdvanced ProfilingCapability to “certify” cluster performanceJob Profiling – weeds out bad written codeValue Added FeaturesTesting Framework for Map – Reduce jobs : certify build to production
This slide shows the master-slave architecture of Oracle NoSQL DB. Master receives the write and it asynchronously replicate the data to the other replica-nodes.
This slide shows the master-slave architecture of Oracle NoSQL DB. Master receives the write and it asynchronously replicate the data to the other replica-nodes.
This slide shows the master-slave architecture of Oracle NoSQL DB. Master receives the write and it asynchronously replicate the data to the other replica-nodes.
Experienced Advisors Accelerated Consulting & Services Leader for Big Data. Headquartered in San Jose, offices in India.Expertise through Architects Pioneers in distributed software engineering with both vertical and functional expertise. Dedicated Innovation Labs.Excellence delivered through technology Advances Open source and Innovation Product Portfolio.Founded 1991 – 1300 StrongLeading Big Data since 2008Chicago, NYC, Atlanta, Indore, Noida, BangaloreImpetus provides Big Data thought leadership and services, creating new ways of analyzing data to gain key business insights across enterprises. Impetus’ experience extends across the big data ecosystem including Hadoop, NoSQL, newsql, MPP databases, machine learning, and visualization. Impetus offers a Quick Start program, Architecture Advisory Services, Proof of Concept, and Implementation.
Oracle NoSQL Database allows you to relax/configure the Consistencyand Durability policies for a given operation. Durability is controlled by defining the Write Policy and the HA Acknowledgement Policy. You can increase write transactions performance by relaxing the Durability constraints. The default is Write-to-memory, Majority Ack. Consistency is controlled by defining the Read Guarantees that you require from the system. You can increase read transaction performance by relaxing the Consistency constraints. The default is None.
We heard you – we have ACID transactions in Oracle NoSQL Database. You can think of a transaction as a single auto-commit API call. That API call can be for a single record, multiple records or multiple operations AS LONG AS all of the records are for the same Major Key. However many records/operations are in that API call, they are all committed atomically (all or nothing). Because they all share the same Major Key, all of the data being affected resides on a single storage node, so we can guarantee the transactional semantics of the transaction commit. We will replicate that transaction to the replicas (copies of the data) as part of the transaction. Of course, not all operations are created equal. In some cases you may want operations that are not completely ACID. One of the benefits of NoSQL is that it relaxes transactional guarantees in order to provide faster throughput. The Oracle NoSQL Database allows you to override the default and relax the ACID properties on a per-operation basis, allowing the application to specify the transactional behavior that is most appropriate.
Elasticity refers to dynamic/online expansion changes in a deployed store configuration. New storage nodes are added to a store to increase performance, reliability, or both.Increase Data Capacity - A Company’s Oracle NoSQL Database application is now obtaining it’s data from several unplanned new sources. The utilization of the existing configuration as more than adequate to meet requirements, with one exception, they anticipate running out of disk space later this year. The company would like to add the needed disks to the existing servers in existing slots, establish mount points, ask NoSQL Database to fully utilize the new disks along with the disks already in place while the system is up and running Oracle NoSQL Database. The Administrator after installing the new disks, defines a new topology using the Administrator with the new mount points and capacity value such that new replication nodes can be created on the existing storage nodes. The administrator can review the plan for errors and then when ready the new topology is deployed while the Oracle NoSQL Database is online and continues to serve the running application with CRUD operations.Increase Throughput- As a result of an unplanned corporate merger, the live Oracle NoSQL Database will see a substantial increase in write operations. The read write mix of transactions will go from 50/50 to 85/15. The need workload will exceeds the I/O capacity available of the available storage nodes. The company would like to add new hardware and have it be utilized by the existing Oracle NoSQL Database (kvstore) currently in place. Oh, and of course the Application needs to continue to be available while this upgrade is occurring.With the new elasticity capabilities and topology planning, the administrator can add the new hardware and define a new topology with the new Storage Nodes. The administrator can then look at the resulting topology (storage nodes, replication nodes, shards, etc) to confirm it meets their requirements. Once they are satisfied with the new topolgy they can also determine when they want to deploy the new topology in the background and while the existing application continues to operate. As partitions/chunks of data are moved they are made available to the live system. Increase Replication Factor- A new requirement has been placed on an existing Oracle NoSQL Database to increase the overall availability of the Oracle NoSQL Database by increasing the replication factor by utilizing new storage nodes added in a second geographic location. This is accomplished by adding at least 1 replication node for every existing shard. The current configuration has a replication factor of 3.While the system is live, the administrator changes the topology to define the new storage nodes and define the replication factor. Again the administrator can validate the topology and review it before deploying. As a side point, the administrator could validate several changes to evaluate alternatives and then decide which topology to deploy. Just like the other scenarios described the data is automatically moved and partitions are made available as they are moved as part of a background activity. Meanwhile the KVStore continues to service the existing workload starting to use the new replicas as they become available. Once the topology is deployed a new replication node has been created and populated for each shard. We have increased availability by increasing the replication factor where the new storage nodes are in another geographic location. We have increased read throughput capability with the new Replication nodes for each shard and the Replication Factor is now 4.
Rebalance a configuration :A storage node has failed and must be replaced (KVStore continues to run). The new hardware is a much more powerful machine (9 Cores, 64 GB of real (compared to 8 GB), multiple 400 GB Solid State Drives). The hardware is a heterogenous hardware mix. The new hardware replaces the failed storage node and the System administrator add the new Storage node to the pool of available storage modes and then migrates the old (failed) Storage node to the new one. After successful migration (KVStore continues to run) the failed storage node is deleted and all Storage nodes are active again. Continuing to monitor the performance of the system and the existing topology, the administrator notices that some of the older storage nodes have 2 replication nodes on them and the CPU/IO utilization is high and latency is high as well, while the new much faster storage node is under utilized. By using the new physical topology planning support available in this release, Oracle NoSQL Database will rebalance the configuration and redistribute the data . In other words, Oracle NoSQL Database will make optimal use of heterogeneous storage nodes. The new Storage nodes will likely have multiple replication nodes running on them while many of the older systems may go from 2 to 1. The replication nodes will automatically be moved. Again this can all happen while the system is online and at the convenience of the company.By using the new physical topology planning support available in this release, Oracle NoSQL Database will rebalance the configuration and redistribute the data . In other words, Oracle NoSQL Database will make optimal use of heterogeneous storage nodes. The new Storage nodes will likely have multiple replication nodes running on them while many of the older systems may go from 2 to 1. The replication nodes will automatically be moved. Again this can all happen while the system is online and at the convenience of the company.Data Movement:• Idempotent: Can be run multiple times with the same result• Interruptible: You can interrupt at any time and the KVStore will continue running. The company may have a peak workload period daily and may want to interrupt the data movement (as part of the new topology) and restart it after the peak period. • Restartable:
Why Avro?Avro is used in multiple products such as Hadoop and other programming languages. Having a schema and serialization framework is advantageous when working with multiple programmers and other products such as Hadoop. Schema With Avro, each value is associated with an AVRO schema (created in JSON format) typically created by the application programmer. An advantage of using Avro is that the serialized values can be stored in a space efficient manner. Avro has a number of primitive data types, including. boolean, int, long, float and stringBindingsOracle NoSQL Database supports multiple binding types. Generic – Schemas are treated dynamically (not fixed at build time).Using Specific bindings (named SpecificAvroBinding) has the advantage of creating a POJO (Plain Old Java Object) class with getter and setter methods for each field in the schema. JSON Bindings: . The JSON binding JsonAvroBinding is easy to read or create and also can interoperate with other programs that use JSON objects. Raw – Low level serialization not performedSchema Evolution is important with large databases where you can’t simply update every key/value pair in the store. Different schemas (with defined constraints in the avro specification) can be used when data is read or written. With well defined constraints in the avro specification, the schema used to read data does not need to be exactly the same as for writing data. For example, let’s imagine we have a key/value record representing profile information for a user. We have a new requirement to add an alternate email address. The field is added and a default value is established. In the future if a new key/value pair is added, the alternate email address is added. If the profile information is updated, the alternate email address is added. On reads (for example displaying the profile information) the alternate email address may not have been updated yet and that is fine, a default value can be displayed. This allows complete flexibility in terms of providing the updated field over time.
New streaming API for Large Objects (recommended size greater than 1M to 100’s of GB). Examples would be audio files, video files, Medical Imaging. New methods were created of the kvstore handle (getLob, putLOB, deleteLOB, putLOBIfAbsent, putLOBIfPresent)The major difference is the Input stream utilized to chunk the Large Object. The result is that the smaller chunks can be stored across the KVStore (multiple shards) depending on size. In addition, the chunks are stored in parallel so the write/read operations are much faster.
External Table support. Allows you to access data in external sources as it is a table in the Oracle Relational Database. Through Oracle’s external table support, you can access Oracle NoSQL Database key/value paris as if they are rows in Oracle Database. This allows you to issue SQL read statements such as Select, Select Count(*) where the results are obtained from Oracle NoSQL Database. Since Select statements can refer to multiple tables, the query can be looking at both Oracle NoSQL Database information AND data that resides directly in the Oracle Database. It also means that the data can be accessed via JDBC.Sample Programs and javadoc are available. Event Processing.The cartridge will work with Oracle EP.
From http://www.slideshare.net/jmusser/j-musser-apishotnotgluecon2012, slide 23
There’s a web-based Admin GUI which is a great way to get started. Most production sites with lots of nodes will probably use the CLI (command line interface) to start/stop the system, and use the GUI to check on status. The system keeps track of both the status of the system and the various storage nodes, as well as the performance statistics and throughput for each node. In a future of NoSQL Database, the administration functionality will also be available via Oracle Enterprise Manager.