Siemens and SAP are partnering to create an end-to-end digital thread that integrates product design, manufacturing, and asset lifecycle management. The partnership will leverage SAP's enterprise applications and Siemens' product lifecycle management software to provide real-time information across the product development process. Key areas of synergies between the two companies include portfolio and project management, systems engineering, configuration management, supplier collaboration, visualization, and intelligent asset management. The goal is to realize a single digital thread that improves time to value, accelerates revenues, and ensures total integration and business concurrency.
Graph technology has truly burst onto the scene with diverse new products and services, proving that graph is relevant and that not all graph use cases are equal. Previously relegated to niche implementations and science projects, graph now finds itself deployed as the foundational technology for enterprise analytics solutions and enterprise Data Fabric strategies. It is no surprise that many are calling 2018 “The Year of the Graph”.
The Zen of DataOps – AWS Lake Formation and the Data Supply Chain PipelineAmazon Web Services
Many organizations have adopted or are in the process of adopting DevOps methodologies in their quest to accelerate the delivery of software capabilities, features, and functionalities to support their organizational objectives. By applying the same practices, DataOps aims to provide the same level of agility in delivering data and information to the organization. AWS Lake Formation, in coordination with other AWS Services, enables DevOps methodologies to be realized through the Data Supply Chain Pipeline.
Data Warehouse or Data Lake, Which Do I Choose?DATAVERSITY
Today’s data-driven companies have a choice to make – where do we store our data? As the move to the cloud continues to be a driving factor, the choice becomes either the data warehouse (Snowflake et al) or the data lake (AWS S3 et al). There are pro’s and con’s for each approach. While the data warehouse will give you strong data management with analytics, they don’t do well with semi-structured and unstructured data with tightly coupled storage and compute, not to mention expensive vendor lock-in. On the other hand, data lakes allow you to store all kinds of data and are extremely affordable, but they’re only meant for storage and by themselves provide no direct value to an organization.
Enter the Open Data Lakehouse, the next evolution of the data stack that gives you the openness and flexibility of the data lake with the key aspects of the data warehouse like management and transaction support.
In this webinar, you’ll hear from Ali LeClerc who will discuss the data landscape and why many companies are moving to an open data lakehouse. Ali will share more perspective on how you should think about what fits best based on your use case and workloads, and how some real world customers are using Presto, a SQL query engine, to bring analytics to the data lakehouse.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
Graph technology has truly burst onto the scene with diverse new products and services, proving that graph is relevant and that not all graph use cases are equal. Previously relegated to niche implementations and science projects, graph now finds itself deployed as the foundational technology for enterprise analytics solutions and enterprise Data Fabric strategies. It is no surprise that many are calling 2018 “The Year of the Graph”.
The Zen of DataOps – AWS Lake Formation and the Data Supply Chain PipelineAmazon Web Services
Many organizations have adopted or are in the process of adopting DevOps methodologies in their quest to accelerate the delivery of software capabilities, features, and functionalities to support their organizational objectives. By applying the same practices, DataOps aims to provide the same level of agility in delivering data and information to the organization. AWS Lake Formation, in coordination with other AWS Services, enables DevOps methodologies to be realized through the Data Supply Chain Pipeline.
Data Warehouse or Data Lake, Which Do I Choose?DATAVERSITY
Today’s data-driven companies have a choice to make – where do we store our data? As the move to the cloud continues to be a driving factor, the choice becomes either the data warehouse (Snowflake et al) or the data lake (AWS S3 et al). There are pro’s and con’s for each approach. While the data warehouse will give you strong data management with analytics, they don’t do well with semi-structured and unstructured data with tightly coupled storage and compute, not to mention expensive vendor lock-in. On the other hand, data lakes allow you to store all kinds of data and are extremely affordable, but they’re only meant for storage and by themselves provide no direct value to an organization.
Enter the Open Data Lakehouse, the next evolution of the data stack that gives you the openness and flexibility of the data lake with the key aspects of the data warehouse like management and transaction support.
In this webinar, you’ll hear from Ali LeClerc who will discuss the data landscape and why many companies are moving to an open data lakehouse. Ali will share more perspective on how you should think about what fits best based on your use case and workloads, and how some real world customers are using Presto, a SQL query engine, to bring analytics to the data lakehouse.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
Modern Data Warehousing with the Microsoft Analytics Platform SystemJames Serra
The traditional data warehouse has served us well for many years, but new trends are causing it to break in four different ways: data growth, fast query expectations from users, non-relational/unstructured data, and cloud-born data. How can you prevent this from happening? Enter the modern data warehouse, which is able to handle and excel with these new trends. It handles all types of data (Hadoop), provides a way to easily interface with all these types of data (PolyBase), and can handle “big data” and provide fast queries. Is there one appliance that can support this modern data warehouse? Yes! It is the Analytics Platform System (APS) from Microsoft (formally called Parallel Data Warehouse or PDW) , which is a Massively Parallel Processing (MPP) appliance that has been recently updated (v2 AU1). In this session I will dig into the details of the modern data warehouse and APS. I will give an overview of the APS hardware and software architecture, identify what makes APS different, and demonstrate the increased performance. In addition I will discuss how Hadoop, HDInsight, and PolyBase fit into this new modern data warehouse.
How Can I Build a Landing Zone & Extend my Operations into AWS to Support my ...Amazon Web Services
AWS Landing Zone accelerates customer adoption of the cloud by providing a prescriptive set of instructions for deploying an AWS-recommended foundation of interrelated AWS accounts, networks, and core services. AWS Landing Zone provides prescriptive guidance and best practice templates that a customer can deploy into their initial AWS environment with confidence that it will grow to meet future business needs including security and regulatory compliance requirements. Learn More: https://aws.amazon.com/government-education/
DataOps: An Agile Method for Data-Driven OrganizationsEllen Friedman
DataOps expands DevOps philosophy to include data-heavy roles (data engineering & data science). DataOps uses better cross-functional collaboration for flexibility, fast time to value and an agile workflow for data-intensive applications including machine learning pipelines. (Strata Data San Jose March 2018)
Qlik and Confluent Success Stories with Kafka - How Generali and Skechers Kee...HostedbyConfluent
Converting production databases into live data streams for Apache Kafka can be labor intensive and costly. As Kafka architectures grow, complexity also rises as data teams begin to configure clusters for redundancy, partitions for performance, as well as for consumer groups for correlated analytics processing. In this breakout session, you’ll hear data streaming success stories from Generali and Skechers that leverage Qlik Data Integration and Confluent. You’ll discover how Qlik’s data integration platform lets organizations automatically produce real-time transaction streams into Kafka, Confluent Platform, or Confluent Cloud, deliver faster business insights from data, enable streaming analytics, as well as streaming ingestion for modern analytics. Learn how these customer use Qlik and Confluent to: - Turn databases into live data feeds - Simplify and automate the real-time data streaming process - Accelerate data delivery to enable real-time analytics Learn how Skechers and Generali breathe new life into data in the cloud, stay ahead of changing demands, while lowering over-reliance on resources, production time and costs.
Data Analytics Meetup: Introduction to Azure Data Lake Storage CCG
Microsoft Azure Data Lake Storage is designed to enable operational and exploratory analytics through a hyper-scale repository. Journey through Azure Data Lake Storage Gen1 with Microsoft Data Platform Specialist, Audrey Hammonds. In this video she explains the fundamentals to Gen 1 and Gen 2, walks us through how to provision a Data Lake, and gives tips to avoid turning your Data Lake into a swamp.
Learn more about Data Lakes with our blog - Data Lakes: Data Agility is Here Now https://bit.ly/2NUX1H6
Jade Global Digital Transformation & Cloud Consulting Partner - OverviewJade Global
Jade Global is well-positioned to be your strategic IT services partner. We create value through our vast portfolio of IT services delivered by highly skilled and experienced consultants. Our services include business application implementations, integrations, software product engineering, Cloud services, technology advisory, testing, and managed services. We have domain expertise in a variety of industries including manufacturing, high-tech, energy, pharmaceuticals and warehouse distribution. Jade Global is a member of the Oracle Cloud Excellence Implementor (CEI) Program, a Salesforce Ridge Partner, Boomi Platinum Partner, ServiceNow Elite Services Partner, NetSuite Systems Integrator Partner, SAP Partner and Snowflake Select Partner providing comprehensive implementation, integration, and optimization services across these mature technologies’ ecosystem. The Company has been recognized as one of the fastest-growing companies in North America by Inc. 5000 and Stevie.
The quest for the insight-driven enterprise has spurned a mass exodus to the cloud. But cloud data ecosystems can be very complex with multiple data storage and processing options.
These slides-based on the webinar featuring leading IT analyst firm EMA, Amazon Web Services (AWS), and Trifacta--will help you: understand technology trends that simplify your analytics modernization journey; learn best practices to operationalize data management on AWS; establish operational excellence leveraging AWS data storage and processing; accelerate time-to-value for analytics projects with data preparation on AWS.
Driving Data Intelligence in the Supply Chain Through the Data Catalog at TJXDATAVERSITY
Roles and responsibilities are a critical component of every Data Governance program. Building a set of roles that are practical and that will not interfere with people’s “day jobs” is an important consideration that will influence how well your program is adopted. This tutorial focuses on sharing a proven model guaranteed to represent your organization.
Join Bob Seiner for this lively webinar where he will dissect a complete Operating Model of Roles and Responsibilities that encompasses all levels of the organization. Seiner will detail the roles and describe the most effective way to associate people with the roles. You will walk out of this webinar with a model to apply to your organization.
In this session Bob will share:
- The five levels of Data Governance roles
- A proven Operating Model of Roles and Responsibilities
- How to customize the model to meet your requirements
- Setting appropriate role expectations
- How to operationalize the roles and demonstrate value
How_to_build_your_cloud_enablement_engine_with_the_people_you_already_haveAmazon Web Services
One of the biggest misconceptions we hear from IT leaders is the belief that not having the right people on staff stops you from moving faster, saving money, and expanding your business on the cloud. You already have the people you need to succeed in the cloud, and these highly skilled, experience and dedicated employees have the ability to learn AWS cloud skills and become certified experts. Transforming your talent has a profound impact on workforce productivity and satisfaction, and in this session we will walk through best practices and AWS capabilities to help you along the way.
O caminho para a nuvem tem muitas opções e diferentes passos. O intuito desse webinar é fornecer uma breve visão sobre a adoção da nuvem e dar subsidios para construção do seu roteiro de migração. Vamos falar sobre como construir seu roadmap de migração, entender diferentes padrões, métodos e sobre as possibilidades que a AWS tem alavancado com sucesso centenas de clientes em todo o mundo. Saiba quais os desafios que os clientes enfrentam ao planejar as migrações para cloud, e como eles superá-los para minimizar riscos e acelerar a adoção.
Review existing data management maturity models to identify core set of characteristics of an effective data maturity model:
DMBOK (Data Management Book of Knowledge) from DAMA (Data Management Association)
MIKE2.0 (Method for an Integrated Knowledge Environment) Information Maturity Model (IMM)
IBM Data Governance Council Maturity Model
Enterprise Data Management Council Data Management Maturity Model
MLOps with serverless architectures (October 2018)Julien SIMON
Talk @ AWS Loft Stockholm, 23/10/2018
But why?
A quick recap on Amazon SageMaker
A quick recap on serverless architectures
Open Source tools: AWS Chalice, Serverless Framework
Demos
Resources
Modern Data Warehousing with the Microsoft Analytics Platform SystemJames Serra
The traditional data warehouse has served us well for many years, but new trends are causing it to break in four different ways: data growth, fast query expectations from users, non-relational/unstructured data, and cloud-born data. How can you prevent this from happening? Enter the modern data warehouse, which is able to handle and excel with these new trends. It handles all types of data (Hadoop), provides a way to easily interface with all these types of data (PolyBase), and can handle “big data” and provide fast queries. Is there one appliance that can support this modern data warehouse? Yes! It is the Analytics Platform System (APS) from Microsoft (formally called Parallel Data Warehouse or PDW) , which is a Massively Parallel Processing (MPP) appliance that has been recently updated (v2 AU1). In this session I will dig into the details of the modern data warehouse and APS. I will give an overview of the APS hardware and software architecture, identify what makes APS different, and demonstrate the increased performance. In addition I will discuss how Hadoop, HDInsight, and PolyBase fit into this new modern data warehouse.
How Can I Build a Landing Zone & Extend my Operations into AWS to Support my ...Amazon Web Services
AWS Landing Zone accelerates customer adoption of the cloud by providing a prescriptive set of instructions for deploying an AWS-recommended foundation of interrelated AWS accounts, networks, and core services. AWS Landing Zone provides prescriptive guidance and best practice templates that a customer can deploy into their initial AWS environment with confidence that it will grow to meet future business needs including security and regulatory compliance requirements. Learn More: https://aws.amazon.com/government-education/
DataOps: An Agile Method for Data-Driven OrganizationsEllen Friedman
DataOps expands DevOps philosophy to include data-heavy roles (data engineering & data science). DataOps uses better cross-functional collaboration for flexibility, fast time to value and an agile workflow for data-intensive applications including machine learning pipelines. (Strata Data San Jose March 2018)
Qlik and Confluent Success Stories with Kafka - How Generali and Skechers Kee...HostedbyConfluent
Converting production databases into live data streams for Apache Kafka can be labor intensive and costly. As Kafka architectures grow, complexity also rises as data teams begin to configure clusters for redundancy, partitions for performance, as well as for consumer groups for correlated analytics processing. In this breakout session, you’ll hear data streaming success stories from Generali and Skechers that leverage Qlik Data Integration and Confluent. You’ll discover how Qlik’s data integration platform lets organizations automatically produce real-time transaction streams into Kafka, Confluent Platform, or Confluent Cloud, deliver faster business insights from data, enable streaming analytics, as well as streaming ingestion for modern analytics. Learn how these customer use Qlik and Confluent to: - Turn databases into live data feeds - Simplify and automate the real-time data streaming process - Accelerate data delivery to enable real-time analytics Learn how Skechers and Generali breathe new life into data in the cloud, stay ahead of changing demands, while lowering over-reliance on resources, production time and costs.
Data Analytics Meetup: Introduction to Azure Data Lake Storage CCG
Microsoft Azure Data Lake Storage is designed to enable operational and exploratory analytics through a hyper-scale repository. Journey through Azure Data Lake Storage Gen1 with Microsoft Data Platform Specialist, Audrey Hammonds. In this video she explains the fundamentals to Gen 1 and Gen 2, walks us through how to provision a Data Lake, and gives tips to avoid turning your Data Lake into a swamp.
Learn more about Data Lakes with our blog - Data Lakes: Data Agility is Here Now https://bit.ly/2NUX1H6
Jade Global Digital Transformation & Cloud Consulting Partner - OverviewJade Global
Jade Global is well-positioned to be your strategic IT services partner. We create value through our vast portfolio of IT services delivered by highly skilled and experienced consultants. Our services include business application implementations, integrations, software product engineering, Cloud services, technology advisory, testing, and managed services. We have domain expertise in a variety of industries including manufacturing, high-tech, energy, pharmaceuticals and warehouse distribution. Jade Global is a member of the Oracle Cloud Excellence Implementor (CEI) Program, a Salesforce Ridge Partner, Boomi Platinum Partner, ServiceNow Elite Services Partner, NetSuite Systems Integrator Partner, SAP Partner and Snowflake Select Partner providing comprehensive implementation, integration, and optimization services across these mature technologies’ ecosystem. The Company has been recognized as one of the fastest-growing companies in North America by Inc. 5000 and Stevie.
The quest for the insight-driven enterprise has spurned a mass exodus to the cloud. But cloud data ecosystems can be very complex with multiple data storage and processing options.
These slides-based on the webinar featuring leading IT analyst firm EMA, Amazon Web Services (AWS), and Trifacta--will help you: understand technology trends that simplify your analytics modernization journey; learn best practices to operationalize data management on AWS; establish operational excellence leveraging AWS data storage and processing; accelerate time-to-value for analytics projects with data preparation on AWS.
Driving Data Intelligence in the Supply Chain Through the Data Catalog at TJXDATAVERSITY
Roles and responsibilities are a critical component of every Data Governance program. Building a set of roles that are practical and that will not interfere with people’s “day jobs” is an important consideration that will influence how well your program is adopted. This tutorial focuses on sharing a proven model guaranteed to represent your organization.
Join Bob Seiner for this lively webinar where he will dissect a complete Operating Model of Roles and Responsibilities that encompasses all levels of the organization. Seiner will detail the roles and describe the most effective way to associate people with the roles. You will walk out of this webinar with a model to apply to your organization.
In this session Bob will share:
- The five levels of Data Governance roles
- A proven Operating Model of Roles and Responsibilities
- How to customize the model to meet your requirements
- Setting appropriate role expectations
- How to operationalize the roles and demonstrate value
How_to_build_your_cloud_enablement_engine_with_the_people_you_already_haveAmazon Web Services
One of the biggest misconceptions we hear from IT leaders is the belief that not having the right people on staff stops you from moving faster, saving money, and expanding your business on the cloud. You already have the people you need to succeed in the cloud, and these highly skilled, experience and dedicated employees have the ability to learn AWS cloud skills and become certified experts. Transforming your talent has a profound impact on workforce productivity and satisfaction, and in this session we will walk through best practices and AWS capabilities to help you along the way.
O caminho para a nuvem tem muitas opções e diferentes passos. O intuito desse webinar é fornecer uma breve visão sobre a adoção da nuvem e dar subsidios para construção do seu roteiro de migração. Vamos falar sobre como construir seu roadmap de migração, entender diferentes padrões, métodos e sobre as possibilidades que a AWS tem alavancado com sucesso centenas de clientes em todo o mundo. Saiba quais os desafios que os clientes enfrentam ao planejar as migrações para cloud, e como eles superá-los para minimizar riscos e acelerar a adoção.
Review existing data management maturity models to identify core set of characteristics of an effective data maturity model:
DMBOK (Data Management Book of Knowledge) from DAMA (Data Management Association)
MIKE2.0 (Method for an Integrated Knowledge Environment) Information Maturity Model (IMM)
IBM Data Governance Council Maturity Model
Enterprise Data Management Council Data Management Maturity Model
MLOps with serverless architectures (October 2018)Julien SIMON
Talk @ AWS Loft Stockholm, 23/10/2018
But why?
A quick recap on Amazon SageMaker
A quick recap on serverless architectures
Open Source tools: AWS Chalice, Serverless Framework
Demos
Resources
Best practices process, including how to develop the IoT Concept. Design of your Business Model and End to End Scenario. Case study with Tennant Manufacturing.
Wie Sie ungenutzte SAP BusinessObjects Lizenzen für die SAP Analytics Cloud n...Wiiisdom
Learn how you can easily use all unused SAP BusinessObjects licenses for SAP Analytics Cloud and give your company more flexibility with a hybrid analytics landscape.
Speaker: Jürgen Bauer, Head of CoE Business Intelligence, SAP
Cynoteck for over a decade has been successfully delivering quality salesforce consulting services to organizations across the globe. We have delivered an array of customized salesforce services to our clients. From initial rollout of Salesforce to providing completely customized functionalities to building custom AppExchange applications, we have done it all.
Cynoteck continues to work with organizations as their Salesforce implementation and managed services partner along with offering end to end salesforce consulting, to ensure their Salesforce instance provides optimum business value. We feel proud of the fact that our solutions are helping our clients in their growth and meeting business goals.
We have an excellent delivery team and have immense experience in designing intuitive solutions using Salesforce customization features, namely, Apex, Visualforce, Lightning components framework and other latest features, to deliver a seamless user experience.
Feel free to reach us if you are looking for a salesforce consulting partner.
We are a niche organization providing IT and IT enabled Business Transformation & Consulting services in Analytics, Enterprise Applications, Engineering Services with future focus on Cognitive Systems, Smart Devices, Man-Machine Interface, Next-Generation Application Architecture and Software Defined Everything for our local, regional and global companies
SAP Active Global Support - Support for Innovation - Quality Assurance at Cus...Bernhard Luecke
For enterprises , Time to Value is what most counts in the more and more rapidly changing world. As a software provider, SAP needs to ensure the quality of the configured and extended product, integrated as part of the solution landscape of the customer. This is achieved through the SAP Control Center Concept delivered within the SAP MaxAttention or Active Embedded engagement by SAP Active Global Support.
Presentation held at "II Jornadas de Calidad del Producto" in Madrid ( http://calidaddelproductosoftware.com/2014/programa/ )
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.
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.
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.
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.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
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!
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.
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.
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.
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
3. The world leader in enterprise
application software and end-to-
end supply chain solutions, from
product design to operations. Built
on a digital platform that delivers a
completely intelligent enterprise
with the world’s largest business
network.
The leader in product lifecycle
software and digital
transformation, with expertise in
mechanical, electronic and
software engineering, Siemens
Digital Industries Software is an
innovation and technology leader
in industrial automation and
digitalization.
The best of both worlds
• Design products with
real-time supply chain
• Create a single
digital thread
• Dramatically improve
time to value
• Create a sustainable
product development
process
Reduce redundancies, eliminate overlapping processes, and turn serial processes into concurrent ones to
Design products with real-time supply chain considerations to eliminate the typical lag to manufacturing.
Create an ethically and environmentally responsible product development process that is driven by sustainability analytics
Create a single digital thread of common data that is shared across all manufacturing relevant entities
Siemens & SAP Partnership
SAP and Siemens strategic partnership in the area of Enterprise Portfolio and Project Management will allow companies to combine Siemens’ strength in planning and managing PLM programs with SAP’s deep integration of enterprise project management capabilities into ERP functions. The integration scenarios enable manufacturing companies to plan, execute and monitor design, development and construction projects which are truly linked with engineering information and digital twin objects.
Customer Challenges
Project driven R&D organizations have to deal with stand alone project management solution which are decoupled from their ERP processes as integration is rarely provided as a standard solution capability
Insufficient visibility into the progress of the project or inconsistent information about actual project costs, budget consumption or confirmed work cause a lot of manual effort when creating project reports for stakeholder and customers
decision making in such an environment is very challenging for customers if they lack of insights into the overall project demand, resource capacity or available financial budget
The consequence is that a project will fail to meet expected outcomes and timelines and with that will cause significant financial risk for the company
The Solution – Integrated Enterprise Portfolio and Project Management
SAP and Siemens will seamlessly integrate the Engineering Activities managed in Team Center into the overall Portfolio and Program planning resifing in SAP Enterprise Portfolio and Project Management.
This integration will allow to control, monitor and measure the entire innovation process from the very first new product idea to portfolio investment decision and to the execution of the necessary engineering work in Siemens team center.
The bi directional integration scenario will allow to feed back scheduling , status and progress information into SAP' Enterprise Portfolio and Project Management , which enables the portfolio manager to monitor the performance of projects in real time without the nead to manually consolidtae the information from various decoupled resources
Siemens & SAP Partnership
SAP and Siemens are known for excellence in area of instituting engineering excellence and enabling enterprise grade product development. The combined solution portfolio in the area of Model Based System Engineering builds the most comprehensive solution and a well-orchestrated path for the product engineering & manufacturers across discrete industries
.
Customer Challenges
Reduced time to market, increasing product complexity and increasing product variations necessitates product manufacturers to efficiently manage value chain across product lifecycle. Companies must orchestrate integrated engineering and development of complex products involving systems with increasing levels of electrical, electronics, and software. They need to make business decisions involving financials models in combination with engineering models that accurately predict real world tradeoffs and results.
The Solution – Model Based Systems Engineering
Effectively incorporate the experience data related to products & its users and consolidate the true voice of customer into product requirements and development processes
Translate product requirements into multi-disciplinary digital models for further synthesis, simulation and optimization
Efficiently manage the complexity of multi-disciplinary product definition across Mechanical, Electrical, Electronics and Software disciplines
Reduced latency between engineering and business enabling them to accomplish MBSE and aspire for realizing model-based enterprise vision
True Digital thread for the entire product lifecycle by combining design, engineering, product definition with the business data
Systems Modeling
Define and manage system models that are relevant at engineering and enterprise levels
Drive transparency into enterprise business data and enable relevant trade studies and optimizations by combining engineering and business data
Translate high level product requirements into multi-disciplinary digital models to drive simulation and optimization in development of detail digital designs in mechanical, electrical/electronic & Software disciplines
Accomplish Model Based Systems Engineering approach by verifying and validating the product performances against its requirements with reduced latency between engineering & business
VALUE OF THE PARTNERSHIP
The partnership delivers a best-in-class product configuration experience throughout the extended enterprise. Customers can use Teamcenter Configurator to author "Product variability" and use it downstream for Manufacturing, Production and Sales.
CHALLENGES
1.Companies today are facing high pressure to reduce the time from ideation phase to product design. Without a proper management of product features , their re-use information, their relation to other features is often slow and requires multiple iterations between product planning and engineering departments.
2.Cost situation of a product will be driven by a proper feature based planning and can be much easier be influenced in the early phase of development. Cost-Intensive combinations drive the product cost up, without proper knowledge about how important they are, and if they could even get excluded or avoided.
3.Many Product Producers own 3-4 Configurators per product, one for Design, one for Manufacturing, one for Sales, or after Sales. These dis-connected Configurators cause a delay in getting changes into the market, do not allow to use digital content in downstream manufacturing for high variable product, and even allow combinations to be sold which cause conflicts.
KEY INTEGRATION VALUE POINTS
Plan Variability:
The Key benefits are the definition of reuse early in the process, to meet the later cost position of the product in the market.
Design and Manufacturing:
Engineering validation based on a digital twin of the product helps to find problem areas in the configuration and can be removed by writing rules and constraints which will dis-allow selling these features combinations.
Production Execution:
Adding, removing or changing a sell-able Product Feature is a key process in Product maintenance. The Integration between Teamcenter Configurator and SAP Advanced Variant Configurator will allow to connect the change cycles in PLM with ERP.
Sales Integration with Configure Price Quote (CPQ):
By connecting eCommerce processes directly with the Configuration Knowledge from PLM allows fast and accurate updates, make sure only viable products getting sold, and allow digital content like a 3D-model to be used very early in the sales process.
BENEFITS
1. Planning of re-use of Features and concepts from an earlier product, from a similar product can lower time to market and reduce cost in a planned manner. This should happen during the system engineering phase, where configurator features are a valuable outcome.
2. By validation of buildable combinations of a product in the digital engineering phase, errors and quality problems can be reduced in the physical phase in manufacturing. Configurator can help to validate a large number of combinations without requiring engineers to build these BOM structures individually. They will be generated by the configurator.
3. Introducing a change into a Product often start by defining the effected "Product Feature", the Condition under which the new Features is used and allowed, and the effect to the Product data. By validating a change thru Engineers, Adopting the Change by Manufacturing Engineers, the Change can be published to Sales in a integrated coordinated manner.
Siemens & SAP Partnership
SAP Siemens Supplier collaboration provides comprehensive & integrated environment for collaboration to drive efficiency and performance across the product lifecycle by bringing together design/engineering design data, business data and partners.
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Customer Challenges
All enterprises in design and manufacturing industries are under high pressure when it comes to reduce time to market and manage the rise in complexity and variability of products.
They need to engage with diverse and global supplier ecosystems at different phases of product development.
Informed decision making with insights that combine engineering and business data becomes critical to accelerate the market introduction of products.
The Solution – Collaboration
Siemens collaboration solution is well-suited to the needs of their target users in design and engineering. They support with the best in class capabilities for sharing design/engineering information in pre/post contract scenarios. SAP provides the most comprehensive end-to-end solution to manage the collaboration along the entire lifecycle of product.
SAP & Siemens are keen to further drive synergies from this partnership. They are keen to deliver a mutually agreed upon and validated collaboration solution. The customers should look forward, to having a well-orchestrated end-to-end support with a best in class environment for their entire needs of collaboration.
Collaboration across Product lifecycle
Effectively manage the complete spectrum of collaboration from early design pre-contract collaboration to post contract design collaborations
Well orchestrated workflows and access controls to onboard the relevant stakeholders along stages of collaboration
Instant Collaboration on Product data
Collaboration on unstructured data & structured data incl BoMs, XCAD designs, engineering models along the value chain
Collaboration with embedded 3D Viewer & redlining capabilities to support better decision making with business partners along the value chain
Comprehensive Process support
Seamlessly collaborate with the suppliers right through early design to procurement for scale processes.
Enabling decision making by combining design data & business data across business process and business partners
Siemens & SAP Partnership
The partnership delivers a best-in-class visual user experience to the extended enterprise. Designers and engineers can work with familiar engineering visualization tools; business and operations users can leverage a 3D visual index to business data, training, operations and service procedures, all being assured that product data integrity and change management is maintained across all interfaces.
Customer Challenges
All enterprises in manufacturing industries are under pressure to deliver products and services faster, better and cheaper.
Friction and information loss at critical interfaces.
Visualization and mockup for Multi-CAD engineering data
Mockup and visualization of large scale product configurations
Communicating documented engineering information to suppliers, while managing company IP
After market documentation based on information directly from engineering
Disconnected engineering and enterprise change management
Reuse of Engineering data downstream in the extended enterprise.
The Solution - Visual Data Integration
SAP and Siemens will seamlessly integrate Teamcenter and Teamcenter Visualization with S/4HANA and SAP 3D Visual Enterprise solutions and take their combined portfolio to market. This simplifies our customers integration challenges and enables out-of-box enterprise business processes.
In addition, this partnership opens opportunities to deliver rapid business value in new opportunities. An example is interactive 2D/3D spare parts ordering in SAP’s Commerce Cloud.
Siemens and SAP plan to deliver the visual data interface in Q3 of 2020, and a solution for Design to Spares and Service as a joint product offering in Q1 2021, with further enhancements to the Visual Digital Thread throughout the following quarters.
Siemens and SAP are still in the early phases of defining the plans for the future common integration between Teamcenter and S/4HANA. There is a common intent to build this new integration out into something that we call Next Generation Integration, with capabilities exceeding currently available offerings. This intent is yet to be formalized and to be converted into a commitment with roadmap and timeline, which should happen over the next couple of months.
Both companies plan to release an integration product to be offered by both parties in the near future as a first step. This new product will initially not provide the full functional coverage of existing integration products but will serve as the foundation for the future.
With that in mind, Siemens will absolutely continue supporting T4S for the foreseeable future to serve customers who need a richer feature set for the integration today, and intend to offer migration plans when the time is right to move our T4S customers to Next Generation Integration.
For any customer project, it should be carefully assessed what the specific requirements towards the integration are and when those need to be available, comparing the deployment timeline derived from those requirements with the integration product capability sets published in available documentation and product roadmaps, to arrive at a well founded decision which product to use for the specific project.
This method is in line with the joint Siemens & SAP approach to put the customer first and let the customer benefit drive the decision on which integration product to offer and deploy. The individual assessment and therefore the product to be deployed initially will vary by customer but the end point will be the same for all.
Today’s state of integration:
Information silos across disciplines prevent effective collaboration and reuse of data. Workers can only access information for their own domains, related information from other domains is difficult or impossible to access if it is stored in a system different from their main environment. Current integration capabilities provide some support but not sufficient to allow pervasive access.
Representations of related data in different systems diverge so much that this situation cannot simply be fixed by improving just the integration itself – needs to be viewed as an system of systems
Teamcenter IntegrationS4/HANA
Manual & disconnected business processes slow the exchange of information and increase errors preventing reuse of critical data which could be used to improve decision making
Lessons lost lacking real world performance. Without an IoT feedback loop from the operational assets, companies miss out on opportunities to learn lessons and improve performance – our integrations today do not support this
Next Gen Vision: to-be state of integration
Harmonize data representations (domain model) across the Siemens and SAP domains in Teamcenter and SAP S/4HANA LCS and SAP investment required (technical guidance from Integration)
Align the meaning and semantics of the shared business objects in Teamcenter and SAP S/4HANA
Extend the Teamcenter data model to cover ERP relevant aspects OOTB for persistent information, such as plant specific product information, alignment of effectivity model, etc.
Define a virtual data model that combines the engineering view and operations view as a foundation for seamless integration based on transient data, such as cost, stock, sales view, etc.
Transform a design/engineering structure to represent a product structure that is representing a fixed structure in the harmonized domain model for consumption by operations
Replace explicit data transfer with data federation concepts across the entire landscape which needs to be implemented Integration investment required
Conceptualize design usage scenarios that showcase and make best use of future harmonized capabilities across the Siemens and SAP domains LCS, SAP and integration investment required
