Tibco streaming analytics overview and roadmapLou Bajuk
This document discusses TIBCO's streaming analytics products and services. It provides an overview of TIBCO Streaming Analytics, BusinessEvents, and StreamBase, highlighting their developer and business user features. It also discusses TIBCO Live Datamart and various accelerators and integrations with predictive analytics and other TIBCO products. The document is confidential and its contents are subject to change.
Embracing data science for smarter analytics appsLou Bajuk
This document discusses TIBCO's plans to embrace data science and make advanced analytics more accessible. It highlights TIBCO Enterprise Runtime for R (TERR), which allows embedding predictive analytics and the R programming language into TIBCO products like Spotfire for easier use by analysts, engineers and business users. TIBCO aims to help more users leverage data science through guided applications, visual tools, and integration of TERR and other analytics tools into a unified ecosystem.
Making Data Science accessible to a wider audienceLou Bajuk
TIBCO's Lou Bajuk talks about the challenges to making Data Science accessible to a wider audience, and how the TIBCO Analytics platform helps our customers tackle those challenges.
Yield Improvement Through Data Analysis using TIBCO SpotfireTIBCO Spotfire
Presented by: Andrew Choo, Sr. Yield Engineer, TriQuint Semiconductor
TIBCO Spotfire and Teradata: First to Insight, First to Action; Warehousing, Analytics and Visualizations for the High Tech Industry Conference
July 22, 2013 The Four Seasons Hotel Palo Alto, CA
TIBCO provides an analytics platform that delivers business value across the analytics spectrum from descriptive to predictive to prescriptive analytics. The platform includes Spotfire for visual analytics, predictive analytics using R scripting, and real-time event processing capabilities. It can consume and analyze various data sources including big data. The platform enables different types of users from data scientists to analysts to business users.
Data Science Case Studies: The Internet of Things: Implications for the Enter...VMware Tanzu
The Internet of Things: Implications for the Enterprise
The Internet Of Things (IoT) is already a reality but getting value out of that is still in its infancy. This session analyzes the implications of IoT for the enterprise with examples from the work we have done.
Rashmi Raghu is a Principal Data Scientist at Pivotal with a focus on the Internet-of-Things and applications in the Energy sector. Her work has spanned diverse industry problems including uncovering patterns & anomalies in massive datasets to predictive maintenance. She holds a Ph.D. in Mechanical Engineering with a minor in Management Science & Engineering from Stanford University. Her doctoral work focused on the development of novel computational models of the cardiovascular system to aid disease research. Prior to that she obtained Master’s and Bachelor’s degrees in Engineering Science from the University of Auckland, New Zealand.
The Hive Think Tank: Talk by Mohandas Pai - India at 2030, How Tech Entrepren...The Hive
This document discusses how India can become a $10 trillion economy by 2030 through technology entrepreneurship and the growth of its startup ecosystem. It notes that India currently has the 3rd largest startup ecosystem in the world with 19,400 startups. If the ecosystem continues growing at 270% over 6 years, it could create $500 billion in market value and employ over 3.5 million people by 2030. This growth will be accelerated by initiatives like Digital India that are building digital infrastructure and opening government data through APIs, fueling innovation and problem solving across sectors to help propel India to its economic goals.
Tibco streaming analytics overview and roadmapLou Bajuk
This document discusses TIBCO's streaming analytics products and services. It provides an overview of TIBCO Streaming Analytics, BusinessEvents, and StreamBase, highlighting their developer and business user features. It also discusses TIBCO Live Datamart and various accelerators and integrations with predictive analytics and other TIBCO products. The document is confidential and its contents are subject to change.
Embracing data science for smarter analytics appsLou Bajuk
This document discusses TIBCO's plans to embrace data science and make advanced analytics more accessible. It highlights TIBCO Enterprise Runtime for R (TERR), which allows embedding predictive analytics and the R programming language into TIBCO products like Spotfire for easier use by analysts, engineers and business users. TIBCO aims to help more users leverage data science through guided applications, visual tools, and integration of TERR and other analytics tools into a unified ecosystem.
Making Data Science accessible to a wider audienceLou Bajuk
TIBCO's Lou Bajuk talks about the challenges to making Data Science accessible to a wider audience, and how the TIBCO Analytics platform helps our customers tackle those challenges.
Yield Improvement Through Data Analysis using TIBCO SpotfireTIBCO Spotfire
Presented by: Andrew Choo, Sr. Yield Engineer, TriQuint Semiconductor
TIBCO Spotfire and Teradata: First to Insight, First to Action; Warehousing, Analytics and Visualizations for the High Tech Industry Conference
July 22, 2013 The Four Seasons Hotel Palo Alto, CA
TIBCO provides an analytics platform that delivers business value across the analytics spectrum from descriptive to predictive to prescriptive analytics. The platform includes Spotfire for visual analytics, predictive analytics using R scripting, and real-time event processing capabilities. It can consume and analyze various data sources including big data. The platform enables different types of users from data scientists to analysts to business users.
Data Science Case Studies: The Internet of Things: Implications for the Enter...VMware Tanzu
The Internet of Things: Implications for the Enterprise
The Internet Of Things (IoT) is already a reality but getting value out of that is still in its infancy. This session analyzes the implications of IoT for the enterprise with examples from the work we have done.
Rashmi Raghu is a Principal Data Scientist at Pivotal with a focus on the Internet-of-Things and applications in the Energy sector. Her work has spanned diverse industry problems including uncovering patterns & anomalies in massive datasets to predictive maintenance. She holds a Ph.D. in Mechanical Engineering with a minor in Management Science & Engineering from Stanford University. Her doctoral work focused on the development of novel computational models of the cardiovascular system to aid disease research. Prior to that she obtained Master’s and Bachelor’s degrees in Engineering Science from the University of Auckland, New Zealand.
The Hive Think Tank: Talk by Mohandas Pai - India at 2030, How Tech Entrepren...The Hive
This document discusses how India can become a $10 trillion economy by 2030 through technology entrepreneurship and the growth of its startup ecosystem. It notes that India currently has the 3rd largest startup ecosystem in the world with 19,400 startups. If the ecosystem continues growing at 270% over 6 years, it could create $500 billion in market value and employ over 3.5 million people by 2030. This growth will be accelerated by initiatives like Digital India that are building digital infrastructure and opening government data through APIs, fueling innovation and problem solving across sectors to help propel India to its economic goals.
The document discusses how telecom companies are increasingly using Hadoop to manage and analyze large amounts of diverse data. It notes that 80% of telecom data will be stored on Hadoop platforms going forward. Hadoop provides more cost-effective storage and processing of data compared to traditional data warehouses. It allows telecom companies to gain more value from all their data by performing more flexible analyses and asking bigger questions of their data. The document outlines some of the key benefits of Hadoop architectures for telecom companies dealing with big data, including being able to retain more types of data for longer periods at a lower cost.
Data as the New Oil: Producing Value in the Oil and Gas IndustryVMware Tanzu
Oil and gas exploration and production activities generate large amounts of data from sensors, logistics, business operations and more. Given the data volume, variety and velocity, gaining actionable and relevant insights from the data is challenging. Learn about these challenges and how to address them by leveraging big data technologies in this webinar.
During the webinar we will dive deep into approaches for predicting drilling equipment function and failure, a key step towards zero unplanned downtime. In the process of drilling wells, non-productive time due to drilling equipment failure can be expensive. We will highlight how the Pivotal Data Labs team uses big data technologies to build models for predicting drilling equipment function and failure. Models such as these can be used to build essential early warning systems to reduce costs and minimize unplanned downtime.
Panelist:
Rashmi Raghu, Senior Data Scientist, Pivotal
Hosted by:
Tim Matteson, Co-Founder -- Data Science Central
Video replay is available to watch here: http://youtu.be/dhT-tjHCr9E
Continuously improving factory operations is of critical importance to manufacturers. Consider the facts: the total cost of poor quality amounts to a staggering 20% of sales (American Society of Quality), and unplanned downtime costs plants approximately $50 billion per year (Deloitte).
The most pressing questions are: which process variables effect quality and yield and which process variables predict equipment failure? Getting to those answers is providing forward thinking manufacturers a leg up over competitors.
The speakers address the data management challenges facing today's manufacturers, including proprietary systems and siloed data sources, as well as an inability to make sensor-based data usable.
Integrating enterprise data from ERP, MES, maintenance systems, and other sources with real-time operations data from sensors, PLCs, SCADA systems, and historians represents a major first step. But how to get started? What is the value of a data lake? How are AI/ML being applied to enable real time action?
Join us for this educational session, which includes a view into a roadmap for an open source industrial IoT data management platform.
Key Takeaways:
• Understand key use cases commonly undertaken by manufacturing enterprises
• Understand the value of using multivariate manufacturing data sources, as opposed to a single sensor on a piece of equipment
• Understand advances in big data management and streaming analytics that are paving the way to next-generation factory performance
Hadoop is regarded as a key capability for implementing Big Data initiatives in the enterprise, but organizations have yet to realize its full business benefits. In this webinar, Pivotal and guest Forrester Research, Inc. Identify the use cases driving Hadoop adoption, and explore what is needed to transform initial investments into results.
Learn about:
Challenges Hadoop introduces, and how the right tools and platforms can help address them
Shifts in the industry with regards to SQL and NoSQL systems and their implications to Big Data analytics
Applying in-memory technologies for data management systems, data analytics, transactional processing and operational databases
Watch the on-demand webinar here:
http://www.pivotal.io/big-data/pivotal-forrester-operationalizing-data-analytics-webinar
Learn how to maximize business value from all of your data here: http://www.pivotal.io/big-data/pivotal-hd
Check out this presentation from Pentaho and ESRG to learn why product managers should understand Big Data and hear about real-life products that have been elevated with these innovative technologies.
Learn more in the brief that inspired the presentation, Product Innovation with Big Data: http://www.pentaho.com/resources/whitepaper/product-innovation-big-data
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014Pentaho
Bo Borland presentation at MongoDB World in NYC, June 24, 2014. Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyze Disparate Data in a Single MongoDB View
What's in store for Big Data in 2015? Will the 'Internet of Things' fuel the Industrial Internet? Will Big Data get Cloudy? Check out the top five Big Data predictions for 2015 according to Quentin Gallivan, CEO, Pentah0
Transforming GE Healthcare with Data Platform StrategyDatabricks
Data and Analytics is foundational to the success of GE Healthcare’s digital transformation and market competitiveness. This use case focuses on a heavy platform transformation that GE Healthcare drove in the last year to move from an On prem legacy data platforming strategy to a cloud native and completely services oriented strategy. This was a huge effort for an 18Bn company and executed in the middle of the pandemic. It enables GE Healthcare to leap frog in the enterprise data analytics strategy.
Risk listening: monitoring for profitable growthDataWorks Summit
Historically, insurers used 50-, 100-, and 500-year flood models for risk evaluation and pricing. The extreme weather events we have experienced in 2017 alone prove how dated these methods really are.
To better understand their customers and potential current/future liability claims, forward thinking insurers are monitoring, analyzing, and integrating external data sources in real time (weather feeds from USGS.gov, news and stock feeds, and satellite imagery, to name just a few). By integrating and injecting these new data sources into their risk models and underwriting, insurers are better able to identify their risk appetites and effectively price.
The session will include real-world case studies, including how a global P&C insurer is now quickly analyzing and monitoring 50,000 customers and targets, gaining new insights into the market. Another example is a global reinsurance and specialty company that now leverages digital news channels to monitor its risk portfolio for early warning claims indicators to help drive down loss costs.
Speaker
Cindy Maike, VP Industry Solutions, GM of Insurance, Hortonworks
Big data analytics platform ParStream enables enterprises to exploit big data opportunities and beat competitors through fast implementation and operation. ParStream overcomes limitations of traditional databases through its unique high performance compressed index, parallel architecture, and continuous data import to deliver answers from billions of records in milliseconds. ParStream provides a competitive advantage through its real-time analytics capabilities on large, dynamic datasets.
Big Data Integration Webinar: Getting Started With Hadoop Big DataPentaho
This document discusses getting started with big data analytics using Hadoop and Pentaho. It provides an overview of installing and configuring Hadoop and Pentaho on a single machine or cluster. Dell's Crowbar tool is presented as a way to quickly deploy Hadoop clusters on Dell hardware in about two hours. The document also covers best practices like leveraging different technologies, starting with small datasets, and not overloading networks. A demo is given and contact information provided.
Explore how data integration (or “mashups”) can maximize analytic value and help business teams create streamlined data pipelines that enables ad-hoc analytic inquiries. You’ll learn why businesses increasingly focused on blending data on demand and at the source, the concrete analytic advantages that this approach delivers, and the type of architectures required for delivering trusted, blended data. We provide a checklist to assess your data integration needs and capabilities, and review some real-world examples of how blending various data types has created significant analytic value and concrete business impact.
This document describes a customer success story involving Cloudera and Xpand IT. It discusses how Xpand IT developed a solution to provide near real-time monitoring and management of Hadoop clusters. The solution involves collecting telemetry data from Hadoop jobs, storing it in Kafka for real-time access, and using Spark to parse the logs and load data into Impala and HBase. This allows for real-time monitoring and control of ETL jobs across multiple Hadoop components in a fault-tolerant manner. The architecture is designed according to lambda architecture principles to handle both real-time and batch data processing.
ICIC 2013 Conference Proceedings Tony Trippe PatinformaticsDr. Haxel Consult
The document discusses how big data and data science techniques are bringing a "sea change" to patent analytics. These new techniques, like Hadoop and R, allow for analyzing the huge amounts of patent data in ways that were not possible before. Examples discussed include next-generation citation analysis using network diagrams, word trees to analyze patent claims, and tag clouds for discovering hedge words and synonyms. The advent of these big data analytics tools is creating new opportunities for growth in the patent analysis field.
Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyz...MongoDB
The document discusses blending disparate data sources like stock quotes, news, and Twitter sentiment data into a single MongoDB view for analytics using Pentaho tools. It provides an example of blending intraday Tesla stock quote data from a web service with real-time Twitter data from the Twitter API about Tesla to inform investment decisions. Pentaho data integration is used to extract, transform, and load the data into MongoDB, and Pentaho analytics tools like the new Analyzer for MongoDB allow visualizing and analyzing the blended data.
TIME SERIES: APPLYING ADVANCED ANALYTICS TO INDUSTRIAL PROCESS DATAHortonworks
Thanks to sensors and the Internet of Things, industrial processes now generate a sea of data. But are you plumbing its depths to find the insight it contains, or are you just drowning in it? Now, Hortonworks and Seeq team to bring advanced analytics and machine learning to time-series data from manufacturing and industrial processes.
The document outlines an agenda for a presentation on big data. It discusses key topics like the state of big data adoption, a holistic approach to big data, five high value use cases, technical components, and the future of big data and cloud. The presentation aims to provide an overview of big data and how organizations can take a comprehensive approach to leveraging their data assets.
Reusing and Managing R models in an EnterpriseLou Bajuk
1) The document discusses deploying, managing, and reusing R models in an enterprise environment to make data science more accessible.
2) It describes how TIBCO products like Spotfire, Statistica, and Streambase can be used to deploy R models, embed them in applications and visualizations, and score models in real-time.
3) The goal is to allow both data scientists and general users to leverage R models through these tools to drive insights, automate processes, and take real-time actions.
SL Corporation was pleased to be both a Platinum Sponsor and speaker at TIBCO’S annual user conference, TUCON 2013. TUCON brought together thousands of the world's most influential technologists and decision-makers that form the future of industry. RTView for TIBCO, a lightweight yet comprehensive performance monitoring platform that is tightly integrated with TIBCO middleware was shown at the booth. The solution dramatically increases visibility into TIBCO infrastructure.
TIBCO expert and TIBCO Architect for Asurion, Craig Shelley, and SL’s CTO, Tom Lubinski, presented the following session:
Asurion and SL Present | Tell Me When My Critical Apps Are Sick, Not Dead!
Craig and Tom offered an in-depth look at the latest advances in end-to-end application monitoring and control of TIBCO-centric environments. Learn how you can achieve a significant positive business impact through increased productivity, proactive monitoring, and the agility of being able to quickly change what you’re monitoring and how you view it.
The document discusses how telecom companies are increasingly using Hadoop to manage and analyze large amounts of diverse data. It notes that 80% of telecom data will be stored on Hadoop platforms going forward. Hadoop provides more cost-effective storage and processing of data compared to traditional data warehouses. It allows telecom companies to gain more value from all their data by performing more flexible analyses and asking bigger questions of their data. The document outlines some of the key benefits of Hadoop architectures for telecom companies dealing with big data, including being able to retain more types of data for longer periods at a lower cost.
Data as the New Oil: Producing Value in the Oil and Gas IndustryVMware Tanzu
Oil and gas exploration and production activities generate large amounts of data from sensors, logistics, business operations and more. Given the data volume, variety and velocity, gaining actionable and relevant insights from the data is challenging. Learn about these challenges and how to address them by leveraging big data technologies in this webinar.
During the webinar we will dive deep into approaches for predicting drilling equipment function and failure, a key step towards zero unplanned downtime. In the process of drilling wells, non-productive time due to drilling equipment failure can be expensive. We will highlight how the Pivotal Data Labs team uses big data technologies to build models for predicting drilling equipment function and failure. Models such as these can be used to build essential early warning systems to reduce costs and minimize unplanned downtime.
Panelist:
Rashmi Raghu, Senior Data Scientist, Pivotal
Hosted by:
Tim Matteson, Co-Founder -- Data Science Central
Video replay is available to watch here: http://youtu.be/dhT-tjHCr9E
Continuously improving factory operations is of critical importance to manufacturers. Consider the facts: the total cost of poor quality amounts to a staggering 20% of sales (American Society of Quality), and unplanned downtime costs plants approximately $50 billion per year (Deloitte).
The most pressing questions are: which process variables effect quality and yield and which process variables predict equipment failure? Getting to those answers is providing forward thinking manufacturers a leg up over competitors.
The speakers address the data management challenges facing today's manufacturers, including proprietary systems and siloed data sources, as well as an inability to make sensor-based data usable.
Integrating enterprise data from ERP, MES, maintenance systems, and other sources with real-time operations data from sensors, PLCs, SCADA systems, and historians represents a major first step. But how to get started? What is the value of a data lake? How are AI/ML being applied to enable real time action?
Join us for this educational session, which includes a view into a roadmap for an open source industrial IoT data management platform.
Key Takeaways:
• Understand key use cases commonly undertaken by manufacturing enterprises
• Understand the value of using multivariate manufacturing data sources, as opposed to a single sensor on a piece of equipment
• Understand advances in big data management and streaming analytics that are paving the way to next-generation factory performance
Hadoop is regarded as a key capability for implementing Big Data initiatives in the enterprise, but organizations have yet to realize its full business benefits. In this webinar, Pivotal and guest Forrester Research, Inc. Identify the use cases driving Hadoop adoption, and explore what is needed to transform initial investments into results.
Learn about:
Challenges Hadoop introduces, and how the right tools and platforms can help address them
Shifts in the industry with regards to SQL and NoSQL systems and their implications to Big Data analytics
Applying in-memory technologies for data management systems, data analytics, transactional processing and operational databases
Watch the on-demand webinar here:
http://www.pivotal.io/big-data/pivotal-forrester-operationalizing-data-analytics-webinar
Learn how to maximize business value from all of your data here: http://www.pivotal.io/big-data/pivotal-hd
Check out this presentation from Pentaho and ESRG to learn why product managers should understand Big Data and hear about real-life products that have been elevated with these innovative technologies.
Learn more in the brief that inspired the presentation, Product Innovation with Big Data: http://www.pentaho.com/resources/whitepaper/product-innovation-big-data
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014Pentaho
Bo Borland presentation at MongoDB World in NYC, June 24, 2014. Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyze Disparate Data in a Single MongoDB View
What's in store for Big Data in 2015? Will the 'Internet of Things' fuel the Industrial Internet? Will Big Data get Cloudy? Check out the top five Big Data predictions for 2015 according to Quentin Gallivan, CEO, Pentah0
Transforming GE Healthcare with Data Platform StrategyDatabricks
Data and Analytics is foundational to the success of GE Healthcare’s digital transformation and market competitiveness. This use case focuses on a heavy platform transformation that GE Healthcare drove in the last year to move from an On prem legacy data platforming strategy to a cloud native and completely services oriented strategy. This was a huge effort for an 18Bn company and executed in the middle of the pandemic. It enables GE Healthcare to leap frog in the enterprise data analytics strategy.
Risk listening: monitoring for profitable growthDataWorks Summit
Historically, insurers used 50-, 100-, and 500-year flood models for risk evaluation and pricing. The extreme weather events we have experienced in 2017 alone prove how dated these methods really are.
To better understand their customers and potential current/future liability claims, forward thinking insurers are monitoring, analyzing, and integrating external data sources in real time (weather feeds from USGS.gov, news and stock feeds, and satellite imagery, to name just a few). By integrating and injecting these new data sources into their risk models and underwriting, insurers are better able to identify their risk appetites and effectively price.
The session will include real-world case studies, including how a global P&C insurer is now quickly analyzing and monitoring 50,000 customers and targets, gaining new insights into the market. Another example is a global reinsurance and specialty company that now leverages digital news channels to monitor its risk portfolio for early warning claims indicators to help drive down loss costs.
Speaker
Cindy Maike, VP Industry Solutions, GM of Insurance, Hortonworks
Big data analytics platform ParStream enables enterprises to exploit big data opportunities and beat competitors through fast implementation and operation. ParStream overcomes limitations of traditional databases through its unique high performance compressed index, parallel architecture, and continuous data import to deliver answers from billions of records in milliseconds. ParStream provides a competitive advantage through its real-time analytics capabilities on large, dynamic datasets.
Big Data Integration Webinar: Getting Started With Hadoop Big DataPentaho
This document discusses getting started with big data analytics using Hadoop and Pentaho. It provides an overview of installing and configuring Hadoop and Pentaho on a single machine or cluster. Dell's Crowbar tool is presented as a way to quickly deploy Hadoop clusters on Dell hardware in about two hours. The document also covers best practices like leveraging different technologies, starting with small datasets, and not overloading networks. A demo is given and contact information provided.
Explore how data integration (or “mashups”) can maximize analytic value and help business teams create streamlined data pipelines that enables ad-hoc analytic inquiries. You’ll learn why businesses increasingly focused on blending data on demand and at the source, the concrete analytic advantages that this approach delivers, and the type of architectures required for delivering trusted, blended data. We provide a checklist to assess your data integration needs and capabilities, and review some real-world examples of how blending various data types has created significant analytic value and concrete business impact.
This document describes a customer success story involving Cloudera and Xpand IT. It discusses how Xpand IT developed a solution to provide near real-time monitoring and management of Hadoop clusters. The solution involves collecting telemetry data from Hadoop jobs, storing it in Kafka for real-time access, and using Spark to parse the logs and load data into Impala and HBase. This allows for real-time monitoring and control of ETL jobs across multiple Hadoop components in a fault-tolerant manner. The architecture is designed according to lambda architecture principles to handle both real-time and batch data processing.
ICIC 2013 Conference Proceedings Tony Trippe PatinformaticsDr. Haxel Consult
The document discusses how big data and data science techniques are bringing a "sea change" to patent analytics. These new techniques, like Hadoop and R, allow for analyzing the huge amounts of patent data in ways that were not possible before. Examples discussed include next-generation citation analysis using network diagrams, word trees to analyze patent claims, and tag clouds for discovering hedge words and synonyms. The advent of these big data analytics tools is creating new opportunities for growth in the patent analysis field.
Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyz...MongoDB
The document discusses blending disparate data sources like stock quotes, news, and Twitter sentiment data into a single MongoDB view for analytics using Pentaho tools. It provides an example of blending intraday Tesla stock quote data from a web service with real-time Twitter data from the Twitter API about Tesla to inform investment decisions. Pentaho data integration is used to extract, transform, and load the data into MongoDB, and Pentaho analytics tools like the new Analyzer for MongoDB allow visualizing and analyzing the blended data.
TIME SERIES: APPLYING ADVANCED ANALYTICS TO INDUSTRIAL PROCESS DATAHortonworks
Thanks to sensors and the Internet of Things, industrial processes now generate a sea of data. But are you plumbing its depths to find the insight it contains, or are you just drowning in it? Now, Hortonworks and Seeq team to bring advanced analytics and machine learning to time-series data from manufacturing and industrial processes.
The document outlines an agenda for a presentation on big data. It discusses key topics like the state of big data adoption, a holistic approach to big data, five high value use cases, technical components, and the future of big data and cloud. The presentation aims to provide an overview of big data and how organizations can take a comprehensive approach to leveraging their data assets.
Reusing and Managing R models in an EnterpriseLou Bajuk
1) The document discusses deploying, managing, and reusing R models in an enterprise environment to make data science more accessible.
2) It describes how TIBCO products like Spotfire, Statistica, and Streambase can be used to deploy R models, embed them in applications and visualizations, and score models in real-time.
3) The goal is to allow both data scientists and general users to leverage R models through these tools to drive insights, automate processes, and take real-time actions.
SL Corporation was pleased to be both a Platinum Sponsor and speaker at TIBCO’S annual user conference, TUCON 2013. TUCON brought together thousands of the world's most influential technologists and decision-makers that form the future of industry. RTView for TIBCO, a lightweight yet comprehensive performance monitoring platform that is tightly integrated with TIBCO middleware was shown at the booth. The solution dramatically increases visibility into TIBCO infrastructure.
TIBCO expert and TIBCO Architect for Asurion, Craig Shelley, and SL’s CTO, Tom Lubinski, presented the following session:
Asurion and SL Present | Tell Me When My Critical Apps Are Sick, Not Dead!
Craig and Tom offered an in-depth look at the latest advances in end-to-end application monitoring and control of TIBCO-centric environments. Learn how you can achieve a significant positive business impact through increased productivity, proactive monitoring, and the agility of being able to quickly change what you’re monitoring and how you view it.
Set Your Course for Change with Real-Time Analytics and InsightsTIBCO Software Inc.
The days where analytics could be an afterthought are over. In this era of unprecedented business change, one needs contextual, real-time insights and the ability to immediately act on them. In these slides, we will take an in-depth look at the power of combining real-time analytics and BPM, the different audiences, the difference between reporting and business intelligence (BI), and how they all come together to bring big benefits to business users and enable change.
Give'em What They Want! Self-Service Monitoring in a Shared Services EnvironmentDavid Hickman
The document discusses implementing self-service monitoring in a shared services environment. It describes how providing developers, support teams, and operations staff with access to monitoring dashboards and historical performance data reduces emergency calls to operations and frees up their time. Specific benefits are outlined for application developers, support teams, and the middleware platform team in quickly identifying issues and making scaling decisions.
Tibco NOW San Diego 2017 RTView Breakout sessionSL Corporation
What’s New With TIBCO Middleware Monitoring was a session given at TIBCO Now San Diego 2017 By Ted Wilson, SL COO and Rahul Kamdar from TIBCO. In this session, they discussed the proactive performance monitoring of TIBCO integration platforms is the most effective way to avoid problems. Learn about how TIBCO® RTView® is constantly evolving to meet demand for consolidated visibility across the latest TIBCO technologies deployed in modern multi-cloud, PaaS, and hybrid environments.
This document discusses TIBCO's OEM partnerships and provides an overview of TIBCO's analytics and data integration products. It highlights challenges faced by various industries and how TIBCO technologies like Spotfire and Insight Platform can help address those challenges. Customer case studies are presented on how Equifax and eClinicalWorks have benefited from using TIBCO Spotfire to gain insights from their data. The document also introduces TIBCO Accelerators which provide pre-built solutions to common use cases to help customers develop applications more quickly.
GeoAnalytics: Maximize the Value of Location Based DataNicola Sandoli
We have quickly come to rely on digital maps for everyday living. Map applications are now gaining traction in the enterprise, with users expecting the same simple and intuitive experiences as in their personal apps.
GeoAnalytics can help organize resources to reduce costs, visualize opportunities, and provide a more accurate way to manage the flow of goods.
PART 1: Intro To JasperReports IO And How To Build Your First ReportTIBCO Jaspersoft
The document provides an agenda for introducing JasperReports IO, which is a data visualization and reporting service that allows for interactive data visualizations using a JavaScript API and report production via REST services. The agenda includes introductions, an overview of what JasperReports IO is and why it was created, a demonstration of it in use, building a first visualization, and polling questions. Key points about JasperReports IO are that it is based on the JasperReports platform and allows for embedded interactive visualizations in web applications and report generation via a REST API.
INTRODUCING JASPERSOFT ADVANCED DATA SERVICES: DATA VIRTUALIZATION AT SCALETIBCO Jaspersoft
TIBCO has a new, best-in-class data virtualization tool, TIBCO Jaspersoft® Advanced Data Services. This new service can have a big impact on performance—particularly in scenarios that involve combining three or more data sources or accessing high volumes of data. It is also capable of performing complex joins and data transformations that aren’t possible in Jaspersoft® Domains.
Join our customer-exclusive webinar for an introduction to Jaspersoft Advanced Data Services, its use cases, and how it compares to existing Jaspersoft data integration options.
Specifically, you’ll learn:
How Jaspersoft Advanced Data Services compares to other Jaspersoft data integration options: Jaspersoft ETL and Jaspersoft Virtual Data Sources (Domains)
What use case scenarios are particularly well-suited for Jaspersoft Advanced Data Services
Through product demonstrations, how Jaspersoft Advanced Data Services works
How to try Jaspersoft Advanced Data Services for free
Information processing and analytics cannot be focused only on “store-first” or batch-based approaches. To provide maximum business value, information must also be analyzed closer to the source, and at the speed in which it is being created. Streaming analytics utilizes various techniques for intelligently processing data as it arrives at the edge or within the data center, with the purpose of proactively identifying threats or opportunities for your business.
Democratizing Analytics and Data Science for Continuous IntelligenceBipin Singh
TIBCO provides analytics and data science solutions to help Mercedes F1 team optimize car performance. Their solutions help Mercedes analyze vast amounts of test, simulation and real-time racing data to find optimal car setups and strategies. This has helped Mercedes win several recent F1 driver's and constructor's championships. TIBCO solutions also help other companies like Hemlock Semiconductor optimize manufacturing processes and Hunt Oil better monitor oil drilling operations.
Applying R in BI and Real Time applications EARL London 2015Lou Bajuk
Overview of the challenges of applying R in enterprise analytic applications, and TIBCO's approach to these challenges with Spotfire, TERR and Streambase.
Companies must find a way to join both paths and view the transition to digital as a unified journey, with the end goal clearly defined, then utilize APIs to help them get there faster. The question then becomes, how can companies and developers leverage ESBs, APIs, and a Fast Data platform to cultivate innovation?
In my session at 19th Cloud Expo (Nov 2016), I explored this topic further, highlighting specific use cases and the true value that can be gained from the cloud and APIs in this quest
Big Data LDN 2017: How Big Data Insights Become Easily Accessible With Workfl...Matt Stubbs
This document provides an overview of how workflows can help make big data insights more accessible. It discusses how workflows allow customers to benefit from cost reductions and faster deployment times. Examples are given of customers in healthcare and banking that have reduced surgical infection rates and cut model development time in half using workflows. The document also covers how to pull insights together and deploy predictive models to external systems using tools like Tibco Statistica. It provides a technical overview of building predictive analytics workflows for big data, including examples of workflow templates for Spark, H2O, and deep learning with CNTK.
Wise Men TIBCO ADF Webinar- 16 October 2014Wise Men
TIBCO has a broad range of products which are used for developing various types of enterprise solutions such as, EAI, BPM, CEP and MDM. Most of the enterprises follow agile development methodology and need TIBCO applications to be deployed and promoted as quickly as possible while reducing the develop-test-debug-deploy cycle.
Wise Men has the most comprehensive services on the TIBCO platform. We have an “Automated Deployment Framework” that supports most of the frequently used TIBCO products and we have an implementation service for ADF that guarantees the results..
Please join the experts from Wise Men to understand and discover how we can help you save 75% of lifecycle management cost of your TIBCO applications.
Data Preparation vs. Inline Data Wrangling in Data Science and Machine LearningKai Wähner
Comparison of Data Preparation vs. Data Wrangling Programming Languages, Frameworks and Tools in Machine Learning / Deep Learning Projects.
A key task to create appropriate analytic models in machine learning or deep learning is the integration and preparation of data sets from various sources like files, databases, big data storages, sensors or social networks. This step can take up to 80% of the whole project.
This session compares different alternative techniques to prepare data, including extract-transform-load (ETL) batch processing (like Talend, Pentaho), streaming analytics ingestion (like Apache Storm, Flink, Apex, TIBCO StreamBase, IBM Streams, Software AG Apama), and data wrangling (DataWrangler, Trifacta) within visual analytics. Various options and their trade-offs are shown in live demos using different advanced analytics technologies and open source frameworks such as R, Python, Apache Hadoop, Spark, KNIME or RapidMiner. The session also discusses how this is related to visual analytics tools (like TIBCO Spotfire), and best practices for how the data scientist and business user should work together to build good analytic models.
Key takeaways for the audience:
- Learn various options for preparing data sets to build analytic models
- Understand the pros and cons and the targeted persona for each option
- See different technologies and open source frameworks for data preparation
- Understand the relation to visual analytics and streaming analytics, and how these concepts are actually leveraged to build the analytic model after data preparation
Video Recording / Screencast of this Slide Deck: https://youtu.be/2MR5UynQocs
The document discusses building an analytics-driven security operations center (SOC) using Splunk. It begins with an overview of challenges with traditional SOCs, such as efficacy, staffing, siloization, and costs. It then covers trends in security operations like increased capabilities, automation, use of threat intelligence, and threat hunting. The document outlines components of the security operations toolchain including the log data platform, asset inventory, case management, and common data sources. It presents Splunk as a nerve center for security operations that can provide adaptive security architecture, threat intelligence framework, advanced analytics, automated processes, and proactive hunting and investigation. Finally, it shares examples of how customers have used Splunk to build intelligence-driven SO
Adopting Modern Application Architecture with AWS and Project Flogo (Sponsore...Amazon Web Services
Digital business requires a different breed of applications. Apps that leverage real time event streams, apply machine learning to take immediate action. Flogo is an open source ecosystem designed for just this. Learn how you can leverage Project Flogo to build smart event- driven apps on AWS leveraging services like Amazon EKS, AWS Lambda and Amazon SageMaker.
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R Consortium update for EARL Boston Oct 2017Lou Bajuk
The document provides an overview of the R Consortium, a non-profit organization that supports the R community. It discusses the goals of promoting R's development, funding projects, and fostering collaboration between companies. It outlines the consortium's governance structure and membership levels. Recent projects funded include improving package building, localization, code coverage tools, and database interfaces. TIBCO's participation is driven by contributing to R's success and the compatibility of its products that integrate R.
R consortium update EARL London Sept 2017Lou Bajuk
The document provides an overview of the R Consortium, a non-profit organization that supports the R community. It discusses the goals of promoting R's growth, funding projects, and fostering collaboration between companies. It outlines the consortium's structure, membership options, recently funded projects including improving package building and localization, and encourages involvement through advocacy, proposals, or volunteering.
The document discusses the R Consortium, a non-profit organization that supports the R community. It was founded in 2015 to promote R's growth as a leading data science platform. The R Consortium funds projects and working groups through an Infrastructure Steering Committee to support R and foster collaboration. It is housed at the Linux Foundation to ensure its long-term support of the R community. Membership provides opportunities to influence projects and have a voice in the R community.
The R Consortium is a non-profit organization that supports the R community. Its goals are to create infrastructure and standards to benefit all R users, promote best practices, and support growth and adoption of R. The board of directors and infrastructure steering committee work on collaborative projects. Current projects include improving package development, database interfaces, localization, teaching, and geospatial analysis. Working groups explore new technologies to benefit the R ecosystem.
R in BI and Streaming Applications for useR 2016Lou Bajuk
This document discusses the challenges of applying R in streaming and business intelligence applications and introduces TIBCO's Enterprise Runtime for R (TERR) as a solution. TERR is an enterprise-grade R engine that allows users to develop code in open source R and deploy it on a commercially supported platform without rewriting code. This enables easy integration of R into applications for real-time analytics on streaming data and embedding R functionality in tools like Spotfire for business intelligence. Examples are provided of using TERR for predictive maintenance of oil and gas equipment and transportation logistics optimization.
Extending the R language to BI and Real-time Applications JSM 2015Lou Bajuk
TERR is TIBCO's enterprise-grade R engine that allows companies to leverage R's powerful analytics while overcoming limitations of the open source R engine. TERR enables embedding R functionality tightly within enterprise applications like Spotfire for enhanced analytics. It also allows deploying R models and code in production environments like streaming applications. TERR extends the reach of R across organizations in both interactive and automated analytics.
Using the R Language in BI and Real Time Applications (useR 2015)Lou Bajuk
R provides tremendous value to statisticians and data scientists, however they are often challenged to integrate their work and extend that value to the rest of their organization. This presentation will demonstrate how the R language can be used in Business Intelligence applications (such as Financial Planning and Budgeting, Marketing Analysis, and Sales Forecasting) to put advanced analytics into the hands of a wider pool of decisions makers. We will also show how R can be used in streaming applications (such as TIBCO Streambase) to rapidly build, deploy and iterate predictive models for real-time decisions. TIBCO's enterprise platform for the R language, TIBCO Enterprise Runtime for R (TERR) will be discussed, and examples will include fraud detection, marketing upsell and predictive maintenance.
Real time applications using the R LanguageLou Bajuk
TIBCO Enterprise Runtime for R (TERR) allows for real-time analytics using the R language within TIBCO's Complex Event Processing platforms. TERR provides a faster R engine that can be embedded in TIBCO products like Spotfire and CEP workflows. This enables rapid prototyping and deployment of predictive models to monitor real-time data streams and trigger automated actions. Example use cases discussed include predictive maintenance, customer loyalty analytics, and severe weather alert tracking.
Slides from my 12/10/14 Webinar with the Bloor Group on the importance of an Analytics Platform for delivering value across your organization, and how TIBCO Spotfire meets that need.
Presentation given at the Joint Statistical Meetings in Boston in Aug. 2014, on applications of the R language using TERR, in Business Intelligence and Real Time applications
As the number of packages available for R continues to grow, maintaining and testing these packages becomes more difficult. This difficulty is compounded as independent implementations of the R language, such as TIBCO Enterprise Runtime for R (TERR), are developed. To address this, we have created a test automation framework for testing packages with both TERR and R. We will describe how the framework automatically creates tests from a package's source files. Issues with testing on multiple platforms will be discussed. Suggestions for improving packages with tests will also be presented.
The Compatibility Challenge:Examining R and Developing TERRLou Bajuk
Slides from Michael Sannella, architect for TIBCO Enterprise Runtime for R (TERR), on the the Compatibility Challenge: Examining R and Developing TERR. Presented at useR 2014
Deploying R in BI and Real time ApplicationsLou Bajuk
Overview of how Spotfire and TERR enables the deployment of R language analytics into Business Intelligence and Real time applications, including several examples. Presented at useR 2014 at UCLA on 7/2/14
Extending the Reach of R to the Enterprise with TERR and SpotfireLou Bajuk
An overview of how TIBCO integrates dynamic, interactive visual applications in Spotfire with predictive and advanced analytics in the R language, using TIBCO Enterprise Runtime for R--our R-compatible, enterprise-grade platform for the R language.
Sannella use r2013-terr-memory-managementLou Bajuk
This document discusses memory management in TIBCO's Enterprise Runtime for R (TERR). It summarizes key differences between TERR and R in how they represent data objects, handle reference counting, and perform garbage collection. TERR uses abstract C++ classes to represent data with multiple possible representations. It also implements more precise 16-bit reference counting and leverages reference counts to immediately reclaim temporary objects, reducing the need for garbage collection compared to R.
Extend the Reach of R to the Enterprise (for useR! 2013)Lou Bajuk
An overview of how and why we developed TIBCO Enterprise Runtime for R (TERR), and how it helps organizations leverage the power of the R language more widely.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
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.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.