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
What is the Digital Twin?
Digital twin is the ability to make a virtual representation of the physical elements and the dynamics of how an Internet of Things device operates and works. It's more than a blueprint, it's more than a schematic. It's not just a picture. It's a lot more than a pair of ‘virtual reality’ glasses. It's a virtual representation of both the elements and the dynamics of how an Internet of Things device responds throughout its lifecycle. It can be a jet engine, a building, process on factory floor, and much, much more.
Watch the video introduction of this keynote presentation from Genius of Things Summit in Munich https://youtu.be/RaOejcczPas
This Isn't 'Big Data.' It's Just Bad Data.Peter Orszag
With response rates that have declined to under 10 percent, public opinion polls are increasingly unreliable. Perhaps even more concerning, though, is that the same phenomenon is hindering surveys used for official government statistics, including the Current Population Survey, the Survey of Income and Program Participation and the American Community Survey.
In 2012, The Economist claimed we were entering the third industrial revolution based on the digitization of manufacturing, also referred to as the “smart factory.” The development and adoption of the Internet of Things is a critical element of smart manufacturing as reduced sensor device cost, and increased connectivity and in-memory processing give manufacturers the ability to gather and use data to increase product quality and transform operations. IT organizations are increasingly involved with the management, security and governance of this data as equipment and products are connected to the internet. This session will provide a practical framework for evaluating ways to improve sensor enablement, transaction processes and analytics based on real-world customer examples.
This presentation was made on June 11, 2020.
Recording from the presentation can be viewed here: https://youtu.be/02Gb062U_M4
The manufacturing industry is adopting artificial intelligence (AI) at a fast rate. This century-old industry is complex but has seen constant transformation across all of its facets.
Led by big data analytics, miniaturization of sensors enabling the Internet of Things (IoT), and, now, AI machine learning (ML), manufacturers everywhere have embarked on an AI transformation that is opening up potential new revenue streams as well taking costs and time out of existing processes.
This talk will walk through a use case for enterprise AI solutions within the manufacturing sector. We will discuss the challenges, motivation, and tool selection process, then cover the solution development in detail.
Speaker Bio:
eRic is armed with the technical know-how of Data Science, Machines Learning, and Big Data Analytics. He. is equipped with skill-sets to value-add businesses exploring into areas of Artificial Intelligence (AI) with an AI consultation approach. Translating BDA, Machine Learning, and AI into Business Values.
eRic CHOO had spent the last 8 years in the IT industry from integration of Infrastructure (Storage and Back-up) solutions to Advance Analytics Software specializing in BDA, Machines Learning, and AI. Before joining the IT industry, he had vast experience in the Semiconductor industry, thus a deep understanding in advance manufacturing processes.
SIONG Jong Hang works as a Solutions Engineer/Data Scientist at H2O.ai based in Singapore where he helps business, government, academia, and non-profit organizations in their transformation into AI. Prior to H2O.ai, he has worked at the Quant Group at Bank of America Merrill Lynch in Hong Kong and Teradata in Singapore as a data scientist. He has completed data science projects for various verticals in Europe and Asia. After hours, he’s an avid learner and has attained 100 MOOC certificates in various fields such as AI, science, engineering, and maths. He has also authored articles to instill interest in science, technology as well as AI.
Technology that is going to create a revolution in every Industry including Health care. What is it, what are the tools and what is the outcome?
NASA started the research on Twins due to space travel and the need to have real time feedback of components. Now it is extending to even Health care to having a Human twin.
Optiflow-Le Manufacturing Execution System is a suite of scalable integrated tools, that synchronize your plant-floor operations with supply chain, materials, inventory & business processes, resulting in greater overall performance.
Includes Factory Intelligence, PDM / PLM, Detailed scheduling & Sequencing, BPM Modeler, Capacity Management, Workforce Management, Integration & Collaboration, Data Acquisition and advanced measurement tools such as OEE & OLE.
What is the Digital Twin?
Digital twin is the ability to make a virtual representation of the physical elements and the dynamics of how an Internet of Things device operates and works. It's more than a blueprint, it's more than a schematic. It's not just a picture. It's a lot more than a pair of ‘virtual reality’ glasses. It's a virtual representation of both the elements and the dynamics of how an Internet of Things device responds throughout its lifecycle. It can be a jet engine, a building, process on factory floor, and much, much more.
Watch the video introduction of this keynote presentation from Genius of Things Summit in Munich https://youtu.be/RaOejcczPas
This Isn't 'Big Data.' It's Just Bad Data.Peter Orszag
With response rates that have declined to under 10 percent, public opinion polls are increasingly unreliable. Perhaps even more concerning, though, is that the same phenomenon is hindering surveys used for official government statistics, including the Current Population Survey, the Survey of Income and Program Participation and the American Community Survey.
In 2012, The Economist claimed we were entering the third industrial revolution based on the digitization of manufacturing, also referred to as the “smart factory.” The development and adoption of the Internet of Things is a critical element of smart manufacturing as reduced sensor device cost, and increased connectivity and in-memory processing give manufacturers the ability to gather and use data to increase product quality and transform operations. IT organizations are increasingly involved with the management, security and governance of this data as equipment and products are connected to the internet. This session will provide a practical framework for evaluating ways to improve sensor enablement, transaction processes and analytics based on real-world customer examples.
This presentation was made on June 11, 2020.
Recording from the presentation can be viewed here: https://youtu.be/02Gb062U_M4
The manufacturing industry is adopting artificial intelligence (AI) at a fast rate. This century-old industry is complex but has seen constant transformation across all of its facets.
Led by big data analytics, miniaturization of sensors enabling the Internet of Things (IoT), and, now, AI machine learning (ML), manufacturers everywhere have embarked on an AI transformation that is opening up potential new revenue streams as well taking costs and time out of existing processes.
This talk will walk through a use case for enterprise AI solutions within the manufacturing sector. We will discuss the challenges, motivation, and tool selection process, then cover the solution development in detail.
Speaker Bio:
eRic is armed with the technical know-how of Data Science, Machines Learning, and Big Data Analytics. He. is equipped with skill-sets to value-add businesses exploring into areas of Artificial Intelligence (AI) with an AI consultation approach. Translating BDA, Machine Learning, and AI into Business Values.
eRic CHOO had spent the last 8 years in the IT industry from integration of Infrastructure (Storage and Back-up) solutions to Advance Analytics Software specializing in BDA, Machines Learning, and AI. Before joining the IT industry, he had vast experience in the Semiconductor industry, thus a deep understanding in advance manufacturing processes.
SIONG Jong Hang works as a Solutions Engineer/Data Scientist at H2O.ai based in Singapore where he helps business, government, academia, and non-profit organizations in their transformation into AI. Prior to H2O.ai, he has worked at the Quant Group at Bank of America Merrill Lynch in Hong Kong and Teradata in Singapore as a data scientist. He has completed data science projects for various verticals in Europe and Asia. After hours, he’s an avid learner and has attained 100 MOOC certificates in various fields such as AI, science, engineering, and maths. He has also authored articles to instill interest in science, technology as well as AI.
Technology that is going to create a revolution in every Industry including Health care. What is it, what are the tools and what is the outcome?
NASA started the research on Twins due to space travel and the need to have real time feedback of components. Now it is extending to even Health care to having a Human twin.
Optiflow-Le Manufacturing Execution System is a suite of scalable integrated tools, that synchronize your plant-floor operations with supply chain, materials, inventory & business processes, resulting in greater overall performance.
Includes Factory Intelligence, PDM / PLM, Detailed scheduling & Sequencing, BPM Modeler, Capacity Management, Workforce Management, Integration & Collaboration, Data Acquisition and advanced measurement tools such as OEE & OLE.
Digital Twin refers to a physical and functional description of a component, product or system together with all available operational data. This includes all information which could be useful in current and subsequent lifecycle phases. Benefit of it for mechatronic and cyber-physical systems is to provide the information created during design and engineering also at the operation of the system. The comprehensive networking of all information, shared between partners and connecting design, production and usage, forms the presented paradigm of next generation Digital Twin.
In these slides, the role of big data in supporting smart manufacturing is discussed: Historical perspective of data lifecycle; Conceptual Framework; and Applications.
Digital Twin - What is it and how can it help us?Shaun West
RQ: What services can be provided (by whom and to who) through (or adopting, or developing) the digital twin concepts?
Our focus is long-life capital equipment
Consider the whole life cycle
Apply Service Dominant Logic in the assessment
Consider technical and business hierarchies
Digital transformation in the manufacturing industryBenji Harrison
Industry 4.0 is here. It is all about the fourth industrial revolution which is all set to transform the manufacturing process using advanced capabilities and IT solutions for manufacturing such as smart sensors and actuators. As a result, manufacturers are gaining benefits from increased visibility into operations, cost minimization, quicker production times and provide excellent customer support. The only way manufacturers can take a leap ahead of competitors and win market share and embrace the latest in growth-driven Industry 4.0 technologies. Right from Enterprise Mobility Solutions to emerging technologies, digital transformation is critical to building and executing growth strategies for manufacturing.
IntelliAura enables organizations to digitally connect the right people to the right technologies at the right time. From our own operations to what we offer clients, we are focused on one thing: Business Value. It’s more than how much you paid for something or what a new solution saved.
Everything we do is based on an effective simple idea by bridging the gap between existing and emerging technologies—so you can innovate faster, with less risk, in the race to digital transformation.
Our comprehensive solutions are designed to provide cost-effective and timely advice and support to assist customers with business compliance, improvement and growth, to strengthen your productivity, profitability and competitiveness.
We believe in being open, always. We build trust through transparency, support genuine partnerships, and welcome new ideas. From strengthening relationships with suppliers to integrating with leading technologies, IntelliAura opens the door to a world of opportunities.
Principles of Artificial Intelligence & Machine LearningJerry Lu
Artificial intelligence has captivated me since I worked on projects at Google that ranged from detecting fraud on Google Cloud to predicting subscriber retention on YouTube Red. Looking to broaden my professional experience, I then entered the world of venture capital by joining Baidu Ventures as its first summer investment associate where I got to work with amazingly talented founders building AI-focused startups.
Now at the Wharton School at the University of Pennsylvania, I am looking for opportunities to meet people with interesting AI-related ideas and learn about the newest innovations within the AI ecosystem. Within the first two months of business school, I connected with Nicholas Lind, a second-year Wharton MBA student who interned at IBM Watson as a data scientist. Immediately recognizing our common passion for AI, we produced a lunch-and-learn about AI and machine learning (ML) for our fellow classmates.
Using the following deck, we sought to:
- define artificial intelligence and describe its applications in business
- decode buzzwords such as “deep learning” and “cognitive computing”
- highlight analytical techniques and best practices used in AI / ML
- ultimately, educate future AI leaders
The lunch-and-learn was well received. When it became apparent that it was the topic at hand and not so much the free pizzas that attracted the overflowing audience, I was amazed at the level of interest. It was reassuring to hear that classmates were interested in learning more about the technology and its practical applications in solving everyday business challenges. Nick and I are now laying a foundation to make these workshops an ongoing effort so that more people across the various schools of engineering, design, and Penn at large can benefit.
With its focus on quantitative rigor, Wharton already feels like a perfect fit for me. In the next two years, I look forward to engaging with like-minded people, both in and out of the classroom, sharing my knowledge about AI with my peers, and learning from them in turn. By working together to expand Penn’s reach and reputation with respect to this new frontier, I’m confident that we can all grow into next-generation leaders who help drive companies forward in an era of artificial intelligence.
I’d love to hear what you think. If you found this post or the deck useful, please recommend them to your friends and colleagues!
TEDx Manchester: AI & The Future of WorkVolker Hirsch
TEDx Manchester talk on artificial intelligence (AI) and how the ascent of AI and robotics impacts our future work environments.
The video of the talk is now also available here: https://youtu.be/dRw4d2Si8LA
Digital Transformation is the buzz word of the latest year: What it really means? Which trends and technologies should manufacturers follow? What's next? What to focus on? IoT, Chatbot, Artificial Intelligence, Digical, Big Data
Artificial intelligence (AI) all in one presentation consists of almost all concepts of Artificial intelligence. i.e.
Artificial intelligence, Robotics, ANN, NLP, NLU, History of AI, History, Pakistan, basharat jehan, agriculture university peshawar, Forward and Backward Chaining, Grammers in AI, Morphology, Examples of Expert system, Laws of Robotics,Expert system languages, Syntactic Analysis in NLP, Lecture Notes
Intelligent Manufacturing is a Smart Choice to gain on competitiveness and sustainability. Innovation technologies to boost productivity and visibility of manufacturing opearations.
AI in Healthcare | Future of Smart Hospitals Renee Yao
In this talk, I specifically talk about how NVIDIA healthcare AI software and hardware were used to support healthcare AI startups' innovation. Three startups featured: Caption Health, Artisight, and Hyperfine. Audience: healthcare systems CXOs.
Big Data & Analytics in the Manufacturing Industry: The Vaasan GroupIBM Analytics
The Vassan Group struggled to accurately forecast fluctuating sales orders across the Nordic region. As a result, they couldn't effectively plan their resource and production schedule. With IBM Big Data & Analytics, Vaasan gained the ability to predict production requirements and prepare for fluctuating orders ultimately fulfilling 30% more orders. http://bit.ly/1bt5yGt
Digital Twin refers to a physical and functional description of a component, product or system together with all available operational data. This includes all information which could be useful in current and subsequent lifecycle phases. Benefit of it for mechatronic and cyber-physical systems is to provide the information created during design and engineering also at the operation of the system. The comprehensive networking of all information, shared between partners and connecting design, production and usage, forms the presented paradigm of next generation Digital Twin.
In these slides, the role of big data in supporting smart manufacturing is discussed: Historical perspective of data lifecycle; Conceptual Framework; and Applications.
Digital Twin - What is it and how can it help us?Shaun West
RQ: What services can be provided (by whom and to who) through (or adopting, or developing) the digital twin concepts?
Our focus is long-life capital equipment
Consider the whole life cycle
Apply Service Dominant Logic in the assessment
Consider technical and business hierarchies
Digital transformation in the manufacturing industryBenji Harrison
Industry 4.0 is here. It is all about the fourth industrial revolution which is all set to transform the manufacturing process using advanced capabilities and IT solutions for manufacturing such as smart sensors and actuators. As a result, manufacturers are gaining benefits from increased visibility into operations, cost minimization, quicker production times and provide excellent customer support. The only way manufacturers can take a leap ahead of competitors and win market share and embrace the latest in growth-driven Industry 4.0 technologies. Right from Enterprise Mobility Solutions to emerging technologies, digital transformation is critical to building and executing growth strategies for manufacturing.
IntelliAura enables organizations to digitally connect the right people to the right technologies at the right time. From our own operations to what we offer clients, we are focused on one thing: Business Value. It’s more than how much you paid for something or what a new solution saved.
Everything we do is based on an effective simple idea by bridging the gap between existing and emerging technologies—so you can innovate faster, with less risk, in the race to digital transformation.
Our comprehensive solutions are designed to provide cost-effective and timely advice and support to assist customers with business compliance, improvement and growth, to strengthen your productivity, profitability and competitiveness.
We believe in being open, always. We build trust through transparency, support genuine partnerships, and welcome new ideas. From strengthening relationships with suppliers to integrating with leading technologies, IntelliAura opens the door to a world of opportunities.
Principles of Artificial Intelligence & Machine LearningJerry Lu
Artificial intelligence has captivated me since I worked on projects at Google that ranged from detecting fraud on Google Cloud to predicting subscriber retention on YouTube Red. Looking to broaden my professional experience, I then entered the world of venture capital by joining Baidu Ventures as its first summer investment associate where I got to work with amazingly talented founders building AI-focused startups.
Now at the Wharton School at the University of Pennsylvania, I am looking for opportunities to meet people with interesting AI-related ideas and learn about the newest innovations within the AI ecosystem. Within the first two months of business school, I connected with Nicholas Lind, a second-year Wharton MBA student who interned at IBM Watson as a data scientist. Immediately recognizing our common passion for AI, we produced a lunch-and-learn about AI and machine learning (ML) for our fellow classmates.
Using the following deck, we sought to:
- define artificial intelligence and describe its applications in business
- decode buzzwords such as “deep learning” and “cognitive computing”
- highlight analytical techniques and best practices used in AI / ML
- ultimately, educate future AI leaders
The lunch-and-learn was well received. When it became apparent that it was the topic at hand and not so much the free pizzas that attracted the overflowing audience, I was amazed at the level of interest. It was reassuring to hear that classmates were interested in learning more about the technology and its practical applications in solving everyday business challenges. Nick and I are now laying a foundation to make these workshops an ongoing effort so that more people across the various schools of engineering, design, and Penn at large can benefit.
With its focus on quantitative rigor, Wharton already feels like a perfect fit for me. In the next two years, I look forward to engaging with like-minded people, both in and out of the classroom, sharing my knowledge about AI with my peers, and learning from them in turn. By working together to expand Penn’s reach and reputation with respect to this new frontier, I’m confident that we can all grow into next-generation leaders who help drive companies forward in an era of artificial intelligence.
I’d love to hear what you think. If you found this post or the deck useful, please recommend them to your friends and colleagues!
TEDx Manchester: AI & The Future of WorkVolker Hirsch
TEDx Manchester talk on artificial intelligence (AI) and how the ascent of AI and robotics impacts our future work environments.
The video of the talk is now also available here: https://youtu.be/dRw4d2Si8LA
Digital Transformation is the buzz word of the latest year: What it really means? Which trends and technologies should manufacturers follow? What's next? What to focus on? IoT, Chatbot, Artificial Intelligence, Digical, Big Data
Artificial intelligence (AI) all in one presentation consists of almost all concepts of Artificial intelligence. i.e.
Artificial intelligence, Robotics, ANN, NLP, NLU, History of AI, History, Pakistan, basharat jehan, agriculture university peshawar, Forward and Backward Chaining, Grammers in AI, Morphology, Examples of Expert system, Laws of Robotics,Expert system languages, Syntactic Analysis in NLP, Lecture Notes
Intelligent Manufacturing is a Smart Choice to gain on competitiveness and sustainability. Innovation technologies to boost productivity and visibility of manufacturing opearations.
AI in Healthcare | Future of Smart Hospitals Renee Yao
In this talk, I specifically talk about how NVIDIA healthcare AI software and hardware were used to support healthcare AI startups' innovation. Three startups featured: Caption Health, Artisight, and Hyperfine. Audience: healthcare systems CXOs.
Big Data & Analytics in the Manufacturing Industry: The Vaasan GroupIBM Analytics
The Vassan Group struggled to accurately forecast fluctuating sales orders across the Nordic region. As a result, they couldn't effectively plan their resource and production schedule. With IBM Big Data & Analytics, Vaasan gained the ability to predict production requirements and prepare for fluctuating orders ultimately fulfilling 30% more orders. http://bit.ly/1bt5yGt
Apache Storm vs. Spark Streaming - two stream processing platforms comparedGuido Schmutz
Storm as well as Spark Streaming are Open-Source Frameworks supporting distributed stream processing. Storm has been developed by Twitter and is a free and open source distributed real-time computation system that can be used with any programming language. It is written primarily in Clojure and supports Java by default. Spark is fast and general engine for large-scale data processing and has been designed to provide a more efficient alternative to Hadoop MapReduce. Spark Streaming brings Spark's language-integrated API to stream processing, letting you write streaming applications the same way you write batch jobs. It supports both Java and Scala. This presentation shows how you can implement stream processing solutions with the two frameworks, discusses how they compare and highlights the differences and similarities.
Bobby Evans and Tom Graves, the engineering leads for Spark and Storm development at Yahoo will talk about how these technologies are used on Yahoo's grids and reasons why to use one or the other.
Bobby Evans is the low latency data processing architect at Yahoo. He is a PMC member on many Apache projects including Storm, Hadoop, Spark, and Tez. His team is responsible for delivering Storm as a service to all of Yahoo and maintaining Spark on Yarn for Yahoo (Although Tom really does most of that work).
Tom Graves a Senior Software Engineer on the Platform team at Yahoo. He is an Apache PMC member on Hadoop, Spark, and Tez. His team is responsible for delivering and maintaining Spark on Yarn for Yahoo.
Apache Storm 0.9 basic training - VerisignMichael Noll
Apache Storm 0.9 basic training (130 slides) covering:
1. Introducing Storm: history, Storm adoption in the industry, why Storm
2. Storm core concepts: topology, data model, spouts and bolts, groupings, parallelism
3. Operating Storm: architecture, hardware specs, deploying, monitoring
4. Developing Storm apps: Hello World, creating a bolt, creating a topology, running a topology, integrating Storm and Kafka, testing, data serialization in Storm, example apps, performance and scalability tuning
5. Playing with Storm using Wirbelsturm
Audience: developers, operations, architects
Created by Michael G. Noll, Data Architect, Verisign, https://www.verisigninc.com/
Verisign is a global leader in domain names and internet security.
Tools mentioned:
- Wirbelsturm (https://github.com/miguno/wirbelsturm)
- kafka-storm-starter (https://github.com/miguno/kafka-storm-starter)
Blog post at:
http://www.michael-noll.com/blog/2014/09/15/apache-storm-training-deck-and-tutorial/
Many thanks to the Twitter Engineering team (the creators of Storm) and the Apache Storm open source community!
VoltDB and Flytxt Present: Building a Single Technology Platform for Real-Tim...VoltDB
Webinar presented by Prateek Kapadia, CTO, Flytxt and Ryan Betts, CTO, VoltDB.
Prateek and Ryan highlight the technology stack for Fast + Big data and iterative analytics using Hadoop and VoltDB. In addition, they will outline use cases for Big Data analytics with Hadoop, iterative analytics and machine learning using Spark and real-time analytics using VoltDB supplemented by Big Data + iterative analytics.
The six phase comprehensive project life cycle model-2013Russell Archibald
This holistic project life cycle includes the Incubation/Feasibility Phase prior to the Project Start Phase, and the Project/Product Evaluation Phase after the Project Close-Out Phase.
The Science of Predictive Maintenance: IBM's Predictive Analytics SolutionSenturus
Overview of IBM’s Predictive Maintenance and Quality (PMQ) solution. View the webinar video recording and download this deck: http://www.senturus.com/resources/science-predictive-maintenance/.
We show you the PMQ solution can keep manufacturing processes, infrastructure and field equipment running to maximize use and performance, while minimizing costs.
We show how you can use powerful analytics and data integration to help: Anticipate asset maintenance and product quality problems, Reduce unscheduled asset downtime, Spend less time solving production machinery and field asset problems, Improve asset productivity and process quality, Monitor how assets are performing in real-time and predict what will happen next.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
International competition, shorter product life cycles and faster technological leaps forward – these are only a few of the challenges the production of a company is facing in the 21st century. In order to survive in an environment like this, resource-efficient and secure planning of production processes are necessary to guarantee a consistent and high quality output. Unforeseeable machine failures as well as performance drops or deterioration in quality because of defective system components can lead to shortness of supplies which will eventually weaken the market position of the entire organization.
To meet these requirements organizations are increasingly focusing on the improvement of maintenance, repair and operations of their machinery. In the previous years, the industry shifted their focus away from only reactive repair mechanisms towards the predictive coordination of machine maintenance.
Predictive Maintenance falls under the category of the future of maintenance developments. Originally developed in the course of the “Industrie 4.0” high-tech strategy of the German government, today Predictive Maintenance represents the informatization of production processes - intelligent IT-based production systems on the path towards a Smart Factory. Through the generation and analysis of different machine data, the predictive power of the state of industrial plants is not only enhanced, but also provides the basis for an improved planning certainty as well as the efficient planning of repair and maintenance work.
When Downtime Isn’t an Option: Performance Optimization Analytics in the Era ...CA Technologies
In the era of the customer, preventing system downtime and fixing performance issues before they occur is more critical than ever. Discover how the power of IT analytics can help you deliver improved customer experience through root cause analysis and actionable insight to prevent problems before they occur and resolve them faster if they do. See how you can correlate data from multiple sources for real-time prediction and increased insights into the behavior of your mainframe systems and databases. Whether you are currently doing IT analytics manually, using a variety of tools, an expert or a novice, you won’t want to miss this informative session and learn about new analytics innovations that can help you reduce costs, increase operational efficiency and delight your customers.
For more information, please visit http://cainc.to/Nv2VOe
Topics including: The transformative value of real-time data and analytics, and current barriers to adoption. The importance of an end-to-end solution for data-in-motion that includes ingestion, processing, and serving. Apache Kudu’s role in simplifying real-time architectures.
Streaming analytics webinar | 9.13.16 | Guest: Mike Gualtieri from ForresterCubic Corporation
Business success relies heavily on taking the right action, at the right time, all the time. And actions are dictated by data. But the batch-oriented, collect-store-contemplate model employed by Big Data Analytics technologies is incomplete because it does not make use of live data in real time. Without live, real-time data insights gathered are not up-to-date, and cannot accurately inform applications and services that would benefit from continuous, real-time context for time-sensitive decisions.
To thrive, businesses need to be able to use both live and historical data in their applications and services, continuously, concurrently, and correctly and the only technology currently capable of handling it is streaming analytics. Streaming analytics computes data right now, when it can be analyzed and put to good use to make applications of all kinds contextual and smarter.
This webinar held in collaboration with Forrester, Inc., showcased how streaming analytics applications can be built in minutes, to:
- Aggregate, enrich, and analyze a high throughput of data from multiple, disparate live data sources and in any format to identify patterns, detect opportunities, automate actions, and dynamically adapt
- Easily ingest streaming data from multiple disparate sources to multiple sources, within and between cloud and on-premises environments
- Analyze and act on data as it arrives, without needing to store, eliminating unnecessary security risks and storage costs
- Enable real-time analytics with existing business intelligence and data assets.
Artificial Intelligence, Predictive Analysis, Blockchain, and Machine Learning platforms can be easily
Ingested to our Analytics to provide you with the best solution according to your business needs
Intro of Key Features of Soft CAAT Ent Softwarerafeq
This presentation provides a brief overview of SoftCAAT Ent with use cases. SoftCAAT Ent is a data analytics/BI software used by CAs and CXOs for Assurance, Compliance and Fraud Investigations.
How and Why: Embedded Analytics Interfaces For Your SaaS ProductAggregage
Sam and Jessica faced a problem that many product managers face: their customers wanted better analytics and reporting, but analytics wasn’t the core function of the SaaS product Sam and Jessica manage. To make things tougher, they needed something flexible, scalable and capable of serving different user types.
Modern Product Data Workflows: How and Why: Embedded Analytics Interfaces For...Hannah Flynn
Sam and Jessica faced a problem that many product managers face: their customers wanted better analytics and reporting, but analytics wasn’t the core function of the SaaS product Sam and Jessica manage. To make things tougher, they needed something flexible, scalable and capable of serving different user types.
Data Con LA 2022 - Why Data Quality vigilance requires an End-to-End, Automat...Data Con LA
Curtis ODell, Global Director Data Integrity at Tricentis
Join me to learn about a new end-to-end data testing approach designed for modern data pipelines that fills dangerous gaps left by traditional data management tools—one designed to handle structured and unstructured data from any source. You'll hear how you can use unique automation technology to reach up to 90 percent test coverage rates and deliver trustworthy analytical and operational data at scale. Several real world use cases from major banks/finance, insurance, health analytics, and Snowflake examples will be presented.
Key Learning Objective
1. Data journeys are complex and you have to ensure integrity of the data end to end across this journey from source to end reporting for compliance
2. Data Management tools do not test data, they profile and monitor at best, and leave serious gaps in your data testing coverage
3. Automation with integration to DevOps and DataOps' CI/CD processes are key to solving this.
4. How this approach has impact in your vertical
As part of the re-affirmed commitment to our customers, Ivanti formed an Independent Business Unit (IBU) consisting of proven and loved Ivanti products that will receive increased attention. One of these products is Ivanti Service Desk (ISD).
EMA research places AI and automation initiatives at the top of C-level technology priorities. But resistance to change, lack of experience, and the complexity of training models all hold back progress.
These slides, based on the webinar, address 5 common misconceptions about AI-powered ITSM automation and present a practical way to revolutionize IT support without changing platforms, processes, or user habits.
The Power of 3 - IBM PureApplications, SoftLayer and General Operational Eff...Prolifics
Speakers:
Mike Hastie, Prolifics
Bradley Hertenstein, Prolifics
Join Prolifics as we explore how combining PureApps (Infrastructure Automations), Softlayer (Cloud), and general operational effectiveness (DevOps) to reduce time to delivery, reduce complexity, and reduce cost. This is a birds of a feather interactive discussion but a recorded demo will be used to help level set and get the discussion started.
http://www.prolifics.com
This presentation provides an overview of Inflectra, our mission to foster harmony between developers, testers, and managers, streamline the software development and testing process, and in general make the world a better place for building new products and realizing ideas.
Data, Interconnectedness & The Internet of Things Software AG
Innovation World 2013 presentation.
The key to deriving value from fast data is being able to access, analyze and respond to it in real-time. Robin Gilthorpe explores the deep capabilities and synergies of Real-Time Analytics (Apama) and In-Memory (Terracotta) Platforms, sharing a breadth of insights around use cases and customer successes.
Speaker:
Robin Gilthorpe
CEO, Terracotta
Webinar: Business Intelligence From The Inside OutCorSourceTechPDX
There are a lot of terms thrown around in the world of business intelligence and analytics. Presented as a webinar, this deck is an introduction to the terminology and power of business intelligence to transform companies.
Similar to Real-time Predictive Analytics in Manufacturing - Impetus Webinar (20)
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
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
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
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.
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!
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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.
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
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.
How world-class product teams are winning in the AI era by CEO and Founder, P...
Real-time Predictive Analytics in Manufacturing - Impetus Webinar
1. Real-Time Predictive Analytics
in Manufacturing
Vivek A. Ganesan, Principal Architect
Yue Cathy Chang, Sr. Director, Business Development
Impetus Technologies, Inc.