TCP1P.net Meetup Vision, Objectives and RoadmapStefan Ianta
Toronto Code Pile 1 Programming Meetup - the social innovation network - How to build a platform for reactive microservices on a Nobel Prize Reverse Game Algorithm - 2017 Roadmap
Data Science at Netflix - Principles for Speed & Scale [Rev 2019 keynote]Michelle Ufford
Data science powers Netflix. It informs our decisions and challenges our assumptions. It fuels experimentation and innovation at an unprecedented scale. It helps us discover fantastic content and deliver personalized experiences for millions of people around the world. In short, data science has become critical to Netflix, touching nearly every aspect of the business today.
In this talk, Michelle Ufford will discuss the philosophies and innovations that have helped Netflix scale its data science practice. She’ll walk through what the process looks like today and how Netflix is tackling some of the biggest challenges facing data scientists. Through it all, she’ll share core principles that have contributed to their success, which you can put to immediate use at your own company.
MLSEV Virtual. Optimization of Passengers Waiting Time in ElevatorsBigML, Inc
Optimization of Passengers Waiting Time in Elevators using Machine Learning, by Delio Tolivia, Technical Manager of Research, Development and Innovation Projects at Talento Transformación Digital.
*MLSEV 2020: Virtual Conference.
TCP1P.net Meetup Vision, Objectives and RoadmapStefan Ianta
Toronto Code Pile 1 Programming Meetup - the social innovation network - How to build a platform for reactive microservices on a Nobel Prize Reverse Game Algorithm - 2017 Roadmap
Data Science at Netflix - Principles for Speed & Scale [Rev 2019 keynote]Michelle Ufford
Data science powers Netflix. It informs our decisions and challenges our assumptions. It fuels experimentation and innovation at an unprecedented scale. It helps us discover fantastic content and deliver personalized experiences for millions of people around the world. In short, data science has become critical to Netflix, touching nearly every aspect of the business today.
In this talk, Michelle Ufford will discuss the philosophies and innovations that have helped Netflix scale its data science practice. She’ll walk through what the process looks like today and how Netflix is tackling some of the biggest challenges facing data scientists. Through it all, she’ll share core principles that have contributed to their success, which you can put to immediate use at your own company.
MLSEV Virtual. Optimization of Passengers Waiting Time in ElevatorsBigML, Inc
Optimization of Passengers Waiting Time in Elevators using Machine Learning, by Delio Tolivia, Technical Manager of Research, Development and Innovation Projects at Talento Transformación Digital.
*MLSEV 2020: Virtual Conference.
Monitoring with Elastic Machine Learning at SkyElasticsearch
Learn how Sky leveraged the power of Elastic’s machine learning feature to process over seven billion documents and help discover trends, learn from real-time data, and generate alerts when anomalies occur.
See the video: https://www.elastic.co/elasticon/tour/2019/london/monitoring-with-elastic-machine-learning-at-sky
Notebooks @ Netflix: From analytics to engineering with Jupyter notebooksMichelle Ufford
Slides from JupyterCon 2018 in NYC on 8/23/2018.
Notebooks have moved beyond a niche solution at Netflix; they are now the critical path for how everyone runs jobs against the company’s data platform. From creating original content to delivering bufferless streaming, Netflix relies on notebooks to inform decisions and fuel experiments across the company. Netflix also uses notebooks to power its machine learning infrastructure and run over 150,000 jobs against its 100 PB cloud-based data warehouse every day. The goal is to deliver a compelling notebooks experience that simplifies end-to-end workflows for every type of user. To enable this, Netflix is investing deeply in notebook infrastructure and open source projects such as nteract.
In this talk, Michelle Ufford and Kyle Kelley share interesting ways Netflix uses data and some of the big bets the company is making on notebooks. Topics will include architecture, kernels, UIs, and Netflix’s open source collaborations with projects such as Jupyter, nteract, pandas, and Spark.
Digital Transformation Mindset - More Than Just Technologyconfluent
Many enterprises faced with silo’ed, batch-oriented, legacy systems struggle to compete in this new digital-first world. Adhering to the ‘If it’s not broken don’t fix it’ mentality leaves the door wide open for native digital challengers to grow and succeed. To stay competitive, your organization must respond in real time to every customer experience transaction, sale, and market movement. But how do you get there? First, you must change your mindset.
As streaming platforms become central to data strategies, companies both small and large are re-thinking their enterprise architecture with real-time context at the forefront. Monoliths are evolving into microservices. Datacenters are moving to the cloud. What was once a ‘batch’ mindset is quickly being replaced with stream processing as the demands of the business impose real-time requirements on technology leaders.
Join Argyle, in partnership with Confluent, in our 2018 CIO Virtual Event: The Digital Transformation Mindset – More Than Just Technology. During the webinar we’ll learn how leading companies across industries rely on a streaming platform to make event-driven architectures central to:
• How data strategies and IT initiatives are improving the digital customer experiences
• How executives are reducing risk with real time monitoring and anomaly detection
• Increasing operational agility with microservices and IoT architectures within organizations
Predicting Banking Customer Needs with an Agile Approach to Analytics in the ...Databricks
Moneta has repeatedly been recognized as the most innovative bank on the Czech market. This is due in large part to their strategy of completely shifting to the cloud and using data and advanced analytics to innovate the customer experience with use cases ranging from real-time recommendations to fraud detection.
In this talk, we’ll share how we migrated to the cloud to create an agile environment for analytics and AI. From rapid prototyping machine learning use cases to moving models into production, core to this approach was building a unified platform for data and analytics on Apache Spark, Databricks and AWS. Discussion topics include:
Moneta’s strategy and roadmap for moving to the cloud and creation of the data squad
Overview of use cases including ATM/branch location optimization using geo-data, digital channel attribution, identify fraud detection, etc.
Deep dive into the use of digital behavioural data (web, mobile app, internet banking) and offline transactions to understand and predict customer needs in near-real time using Spark MLLib
Approach to building the agile analytics platform and the specific challenges of using the cloud in a financial institution
A New Data Architecture for the App Economy - StampedeCon 2013StampedeCon
At the StampedeCon 2013 Big Data conference in St. Louis, Anant Jhingran, VP of Products at Apigee, discusses A New Data Architecture for the App Economy. It has been clear for quite some time that traditional warehouses do not cut it for unstructured and semistructured data, and therefore new systems such as NoSQL and Hadoop have emerged. But these systems throw the baby out with the bathwater. Traditional warehouses were built on the premise that applications can be simpler because the databases did a lot. Of course, the penalty for this was that the application’s world view had to fit the relational, database world view. In the new Big Data system, the primitives have been lowered so much (simple key value pair, or completely unstructured tuple structure), that the applications now have to do a lot more. We argue that there is a happy medium. We have studied the kinds of data that sits in the app economy, and the data structures that need to be built on top of NoSQL and Hadoop that considerably speed up Insights in the app economy without requiring every problem to be coded from scratch.
Learn how to build advanced GraphQL queries, how to work with filters and patches and how to embed GraphQL in languages like Python and Java. These slides are the second set in our webinar series on GraphQL.
Stephen Cantrell, kdb+ Developer at Kx Systems “Kdb+: How Wall Street Tech c...Dataconomy Media
Stephen Cantrell, kdb+ Developer at Kx Systems
“Kdb+: How Wall Street Tech can Speed up the World"
You can see some additional notes here:
https://github.com/cantrells/berlin_kdb_demo?files=1
The Elastic Stack has been integral to the growth of E*Trade’s real-time operational intelligence pipeline. Hear their journey to adopting Elastic machine learning features and see firsthand how they’re using them to identify anomalies using full-text aggregations and performance data.
Data engineering at the interface of art and analytics: the why, what, and ho...Data Con LA
Abstract:- Netflix has a growing presence in Hollywood, with technical teams working on everything from high-speed video editing pipelines to machine learning methods for categorizing films. Data is foundational across these efforts and in this talk Josh will take a tour through why we invest so much in data about content, what data engineering challenges we tackle, and the style in which we do it.
Using Kafka in Your Organization with Real-Time User Insights for a Customer ...confluent
(Chris Maier + Steven Royster, West Monroe Partners) Kafka Summit SF 2018
The value of real-time data is growing as an increasing number of companies look to provide a comprehensive experience for their customers. Utilizing Kafka in key facets of your organization will yield greater customer satisfaction and promote a better understanding of user interactions. As data streaming is becoming more prevalent in a wide variety of industries, companies are seeking to modernize their tech stacks by employing the extensible, scalable infrastructure afforded by Kafka.
Over the past few months, we have successfully developed a containerized Kafka implementation at a major healthcare provider. In addition, we created producers to publish messages to the Kafka cluster and consumers to receive them on the other end. By capturing a plethora of data around customer activity, we created opportunities for the business to act upon real-time metrics in order to provide an improved customer experience.
In this talk, we will cover the user-related data sources we connected to Kafka, the reasons we chose them, and how the insights gained from each source can be leveraged in your business. You will walk out understanding how capturing a wide variety of customer activity data can create opportunities for the business to act on real-time metrics in order to provide an improved customer experience.
apidays LIVE Paris - The Rise of GraphQL for database APIs by Karthic Raoapidays
apidays LIVE Paris - Responding to the New Normal with APIs for Business, People and Society
December 8, 9 & 10, 2020
The Rise of GraphQL for database APIs
Karthic Rao, Founder of Pixelbytestudio
When breaking your monolith into components, services or even functions you must understand WHERE and HOW you break your existing code base and architecture into smaller units to allow it to SCALE, PERFORM and make it EASY enough to operate!
In this session a Dynatrace Technical AWS Advocate, shows us how companies such as Barbri, Landbay and Citrix redefined their architecture on top of AWS; how Dynatrace was leveraged to re-platform and re-architecture; and how these lessons learned can benefit all of us to transform Fearless from Monolith to Serverless!
Smart Markets of Services / ATG meetup TorontoStefan Ianta
Evolutionary machine intelligence in a smart services market. Presentation at Analytics and Technology Group meetup / Ivey Tangerine Centre of Leadership, Toronto, Aug 18, 2016
Monitoring with Elastic Machine Learning at SkyElasticsearch
Learn how Sky leveraged the power of Elastic’s machine learning feature to process over seven billion documents and help discover trends, learn from real-time data, and generate alerts when anomalies occur.
See the video: https://www.elastic.co/elasticon/tour/2019/london/monitoring-with-elastic-machine-learning-at-sky
Notebooks @ Netflix: From analytics to engineering with Jupyter notebooksMichelle Ufford
Slides from JupyterCon 2018 in NYC on 8/23/2018.
Notebooks have moved beyond a niche solution at Netflix; they are now the critical path for how everyone runs jobs against the company’s data platform. From creating original content to delivering bufferless streaming, Netflix relies on notebooks to inform decisions and fuel experiments across the company. Netflix also uses notebooks to power its machine learning infrastructure and run over 150,000 jobs against its 100 PB cloud-based data warehouse every day. The goal is to deliver a compelling notebooks experience that simplifies end-to-end workflows for every type of user. To enable this, Netflix is investing deeply in notebook infrastructure and open source projects such as nteract.
In this talk, Michelle Ufford and Kyle Kelley share interesting ways Netflix uses data and some of the big bets the company is making on notebooks. Topics will include architecture, kernels, UIs, and Netflix’s open source collaborations with projects such as Jupyter, nteract, pandas, and Spark.
Digital Transformation Mindset - More Than Just Technologyconfluent
Many enterprises faced with silo’ed, batch-oriented, legacy systems struggle to compete in this new digital-first world. Adhering to the ‘If it’s not broken don’t fix it’ mentality leaves the door wide open for native digital challengers to grow and succeed. To stay competitive, your organization must respond in real time to every customer experience transaction, sale, and market movement. But how do you get there? First, you must change your mindset.
As streaming platforms become central to data strategies, companies both small and large are re-thinking their enterprise architecture with real-time context at the forefront. Monoliths are evolving into microservices. Datacenters are moving to the cloud. What was once a ‘batch’ mindset is quickly being replaced with stream processing as the demands of the business impose real-time requirements on technology leaders.
Join Argyle, in partnership with Confluent, in our 2018 CIO Virtual Event: The Digital Transformation Mindset – More Than Just Technology. During the webinar we’ll learn how leading companies across industries rely on a streaming platform to make event-driven architectures central to:
• How data strategies and IT initiatives are improving the digital customer experiences
• How executives are reducing risk with real time monitoring and anomaly detection
• Increasing operational agility with microservices and IoT architectures within organizations
Predicting Banking Customer Needs with an Agile Approach to Analytics in the ...Databricks
Moneta has repeatedly been recognized as the most innovative bank on the Czech market. This is due in large part to their strategy of completely shifting to the cloud and using data and advanced analytics to innovate the customer experience with use cases ranging from real-time recommendations to fraud detection.
In this talk, we’ll share how we migrated to the cloud to create an agile environment for analytics and AI. From rapid prototyping machine learning use cases to moving models into production, core to this approach was building a unified platform for data and analytics on Apache Spark, Databricks and AWS. Discussion topics include:
Moneta’s strategy and roadmap for moving to the cloud and creation of the data squad
Overview of use cases including ATM/branch location optimization using geo-data, digital channel attribution, identify fraud detection, etc.
Deep dive into the use of digital behavioural data (web, mobile app, internet banking) and offline transactions to understand and predict customer needs in near-real time using Spark MLLib
Approach to building the agile analytics platform and the specific challenges of using the cloud in a financial institution
A New Data Architecture for the App Economy - StampedeCon 2013StampedeCon
At the StampedeCon 2013 Big Data conference in St. Louis, Anant Jhingran, VP of Products at Apigee, discusses A New Data Architecture for the App Economy. It has been clear for quite some time that traditional warehouses do not cut it for unstructured and semistructured data, and therefore new systems such as NoSQL and Hadoop have emerged. But these systems throw the baby out with the bathwater. Traditional warehouses were built on the premise that applications can be simpler because the databases did a lot. Of course, the penalty for this was that the application’s world view had to fit the relational, database world view. In the new Big Data system, the primitives have been lowered so much (simple key value pair, or completely unstructured tuple structure), that the applications now have to do a lot more. We argue that there is a happy medium. We have studied the kinds of data that sits in the app economy, and the data structures that need to be built on top of NoSQL and Hadoop that considerably speed up Insights in the app economy without requiring every problem to be coded from scratch.
Learn how to build advanced GraphQL queries, how to work with filters and patches and how to embed GraphQL in languages like Python and Java. These slides are the second set in our webinar series on GraphQL.
Stephen Cantrell, kdb+ Developer at Kx Systems “Kdb+: How Wall Street Tech c...Dataconomy Media
Stephen Cantrell, kdb+ Developer at Kx Systems
“Kdb+: How Wall Street Tech can Speed up the World"
You can see some additional notes here:
https://github.com/cantrells/berlin_kdb_demo?files=1
The Elastic Stack has been integral to the growth of E*Trade’s real-time operational intelligence pipeline. Hear their journey to adopting Elastic machine learning features and see firsthand how they’re using them to identify anomalies using full-text aggregations and performance data.
Data engineering at the interface of art and analytics: the why, what, and ho...Data Con LA
Abstract:- Netflix has a growing presence in Hollywood, with technical teams working on everything from high-speed video editing pipelines to machine learning methods for categorizing films. Data is foundational across these efforts and in this talk Josh will take a tour through why we invest so much in data about content, what data engineering challenges we tackle, and the style in which we do it.
Using Kafka in Your Organization with Real-Time User Insights for a Customer ...confluent
(Chris Maier + Steven Royster, West Monroe Partners) Kafka Summit SF 2018
The value of real-time data is growing as an increasing number of companies look to provide a comprehensive experience for their customers. Utilizing Kafka in key facets of your organization will yield greater customer satisfaction and promote a better understanding of user interactions. As data streaming is becoming more prevalent in a wide variety of industries, companies are seeking to modernize their tech stacks by employing the extensible, scalable infrastructure afforded by Kafka.
Over the past few months, we have successfully developed a containerized Kafka implementation at a major healthcare provider. In addition, we created producers to publish messages to the Kafka cluster and consumers to receive them on the other end. By capturing a plethora of data around customer activity, we created opportunities for the business to act upon real-time metrics in order to provide an improved customer experience.
In this talk, we will cover the user-related data sources we connected to Kafka, the reasons we chose them, and how the insights gained from each source can be leveraged in your business. You will walk out understanding how capturing a wide variety of customer activity data can create opportunities for the business to act on real-time metrics in order to provide an improved customer experience.
apidays LIVE Paris - The Rise of GraphQL for database APIs by Karthic Raoapidays
apidays LIVE Paris - Responding to the New Normal with APIs for Business, People and Society
December 8, 9 & 10, 2020
The Rise of GraphQL for database APIs
Karthic Rao, Founder of Pixelbytestudio
When breaking your monolith into components, services or even functions you must understand WHERE and HOW you break your existing code base and architecture into smaller units to allow it to SCALE, PERFORM and make it EASY enough to operate!
In this session a Dynatrace Technical AWS Advocate, shows us how companies such as Barbri, Landbay and Citrix redefined their architecture on top of AWS; how Dynatrace was leveraged to re-platform and re-architecture; and how these lessons learned can benefit all of us to transform Fearless from Monolith to Serverless!
Smart Markets of Services / ATG meetup TorontoStefan Ianta
Evolutionary machine intelligence in a smart services market. Presentation at Analytics and Technology Group meetup / Ivey Tangerine Centre of Leadership, Toronto, Aug 18, 2016
Ripping off the Bandage: Re-Architecting Traditional Three-Tier Monoliths to ...Amazon Web Services
The world is powered by many monolithic applications that were written many years ago. These applications have complicated code bases. They are also difficult to maintain, deploy, and operate. The cloud, microservices, and serverless provide agility, efficiency, and resiliency. In this chalk talk, we highlight various approaches for rearchitecting three-tier monoliths to serverless microservices for your customers.
Platform governance, gestire un ecosistema di microservizi a livello enterpriseGiulio Roggero
A livello enterprise, le moderne architetture distribuite coinvolgono molti team differenti, centinaia di sviluppatori e operations e migliaia microservizi ed API in produzione. Come si può gestire questa
e o
un'esplosione di costi e preservando il time-to-market?
Sap Leonardo - what is it, and why would I want one?Tom Raftery
A quick run through of the technologies running through SAP's Innovation portfolio of products, called SAP Leonardo, and use cases where it has been deployed successfully with customers
DEM04 Fearless: From Monolith to Serverless with DynatraceAmazon Web Services
When you break your monolith into components, services, or functions, you must understand where and how to break your existing code base and architecture into smaller units so that it scales, performs, and is easy to operate. In this session, Andreas Grabner, technical AWS advocate, shows you how Dynatrace redefined its architecture. He discusses the migration capabilities Dynatrace engineers built into their product and explains how the lessons learned can help you fearlessly transition from monolith to serverless. This session is brought to you by AWS Partner, Dynatrace.
DEM09 [Repeat] Fearless: From Monolith to Serverless with DynatraceAmazon Web Services
When you break your monolith into components, services, or functions, you must understand where and how to break your existing code base and architecture into smaller units so that it scales, performs, and is easy to operate. In this session, Andreas Grabner, technical AWS advocate, shows you how Dynatrace redefined its architecture. He discusses the migration capabilities Dynatrace engineers built into their product and explains how the lessons learned can help you fearlessly transition from monolith to serverless. This session is brought to you by AWS Partner, Dynatrace.
This presentation provides a brief overview of APM solutions for the Azure cloud computing platform. We identify three challenges unique to cloud computing which APM can address, and we summarize which APM techniques can be applied in IaaS, PaaS, and SaaS application architectures. To illustrate APM techniques for IaaS and PaaS we look at a variety APM offers in the Azure marketplace, including Riverbed AppInternals, Microsoft Application Insights, and NewRelic. To illustrate APM techniques for SaaS, we look at how SharePoint Online can be instrumented using JavaScript injection. This presentation was prepared and delivered by Ian Downard to the Portland Azure User Group on March 28th, 2016.
Why and How to Monitor App Performance in AzureIan Downard
This presentation provides a brief overview of APM solutions for the Azure cloud computing platform. We discuss three challenges unique to cloud computing which APM can address, and we summarize which APM techniques can be applied in IaaS, PaaS, and SaaS application architectures. To illustrate APM techniques for IaaS and PaaS we look at a variety APM offers in the Azure marketplace, including Riverbed AppInternals, Microsoft Application Insights, and New Relic. To illustrate APM techniques for SaaS, we look at how SharePoint Online can be instrumented using JavaScript injection. This presentation was prepared and delivered by Ian Downard to the Portland Azure User Group on March 28th, 2016, in Portland Oregon.
Building Microservices with Containers (CON308-R1) - AWS re:Invent 2018Amazon Web Services
Microservices are minimal function services that are deployed separately, but can interact together to function as a broader application. Microservices can be built, changed, and deployed quickly with a relatively small impact, empowering developers to speed up the rate of innovation. In this session, we show how containers help enable microservices-based application architectures, discuss best practices for building new microservices, and cover the AWS services that allow you to build performant microservices applications.
Similar to sMART Store of Cypher-Annotated Microservices (20)
Manhattan Project 2017 - Building the Socially Controlled AI NetworkStefan Ianta
Dec 2, 2017 - Presentation at Manhattan Algorithmic Innovations Reactor Meetup at Columbia University, Pupin Physics Laboratory where Einstein, Szilard and Fermi launched 77 years ago the Manhattan Project to exploit massive chain reactions
From Copycat Codelets to an AI Market Internet ProtocolStefan Ianta
Presentation for the Transformative Code Pile 1 Programming Meetup on Aug 3, 2017 on expanding the Copycat Project into an AI Genetic Internet of Reactive Services
Applications of automated problem solvingStefan Ianta
The presentation at the TCP1P Meetup May 11 @Paytm Labs downtown Toronto: Applications of Algorithmic Problem Solving:
- Gamification of Problem Solving
- Automated Agile Project Management
- Big Business = (Big Data + Big Code) x DevOps
The Innovation Language and The Social Innovation NetworkStefan Ianta
Introduction to the concepts and benefits of the Universal Innovation Language and how to implement it as the Semantic AI Internet / Digital Democracy.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
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.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
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.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
sMART Store of Cypher-Annotated Microservices
1. sMART Store of
Cypher-Annotated
microservices
Building a sMART API Store on a
Neo4j Recommendation Engine
Stefan V Ianta
servi sMART & Ianta Labs
@v_ianta
Self-assembling Wires
Stanford Complexity Group
www.youtube.com/watch?v=PeHWqr9dz3c
microServices Market Worldwide
8. Agile X Change
Context Change Management
Agile Project Management
Story | Change | Service
Confluence | JIRA/Agile | GitHub
Solutions = Σ Services
Optimal Software generation
Optimal Business workflows
Smart Market of Services
servi.ca
9. Graph Reactor / Ianta Labs
Initial Business Context – Data & Code – Entities/Roles & Processes
ClientsRules
Rivals
Code
Meta
Data
Plans
Data Team
Sales
Bank
Skills
CONTEXT
10. Graph Reactor / Ianta Labs
Final Business Context – Data & Code – Entities/Roles & Processes
ClientsRules
Rivals
Codes
Meta
-Data
Plan
Data
Team
Sales
Money
Skills
CONTEXT
11. Graph Reactor / Ianta Labs
Epic / Story / Change = (Initial Context, Services, Final Context)
Change
Service = (Initial Context Pattern, Microservices, Final Context Pattern)
Microservice = (Input Query, Function, Output Query)
12. Graph Reactor / Ianta Labs
Project = Sum (Services)
Service 1
Service 2
Service n
17. Graph Reactor / Ianta Labs17
Solution
=
Path
Target Context
Metadata
Data
Software
Initial Context
Metadata
Data
Software
Software & Biz Process Development is a Solution Search Process
Initial Context / Code Target Context / Code
Changes
Transformation
18. Graph Reactor / Ianta Labs18
Expanding Service Recommendation Engine into an Solution Build & Rank Engine
AdWords
Advertisers
Pay Per Click
AdSense
Web Masters
Pay Per Click
Internet Pages Search
Internet Users
One question/search
Microservices
Programmers
Pay Per Use
Cypher Annotations
Business Analysts
Pay Per Use
Budgeted Projects
Product Managers
Pay Per Use
19. Types of Changes:
Create, Read, Update, Delete
Growing Abstract Syntax Tree from Business Model Graphs
Uber ( Services ) | path from current context to destination
Neo4j ( Services ) | find the services covering the Delta
Similarity with Git processes
Stage ~ Extract Input vars from Business Data Graph
Commit ~ Insert AST statement(s) into file AST
Branch ~ Automatic logical branches
servi.ca
Coding Algorithm with Cypher annotated microservices
Ianta Labs
https://www.youtube.com/watch?v=YGhSDV7nrtw
25. Graph Reactor / Ianta Labs25
Workflow Solutions: Solving The 3 Recipients Problem
26. Graph Reactor / Ianta Labs26
Implementation Steps
• Translate existing APIs into Microservices / Coders + DevOps
• Annotate microservices with Cypher queries / BAs
• Define projects including test queries / Product Managers / BAs
• Build a Service compiler or join a Service Smart Market – Servi.ca
27. Summary
Agile Service Exchange
Growing parse trees from business model data
Solving a Simple Workflow Problem
Smart markets of services
servi.ca
DNA Code Self-Replication
YourGenome.org
www.youtube.com/watch?v=TNKWgcFPHqw
Self-assembling Wires
Stanford Complexity Group
www.youtube.com/watch?v=PeHWqr9dz3c
28. Q & A
Stefan Ianta
@v_ianta
servi.ca
https://ca.linkedin.com/in/stefanianta
http://www.slideshare.net/StefanIanta/evolutionary-
design-patterns-for-software-development
servi.ca
DNA Code Self-Replication
YourGenome.org
www.youtube.com/watch?v=TNKWgcFPHqw