This document provides an overview of new features in IBM InfoSphere MDM version 11.3, including: improved integration with other IBM offerings like BigInsights; enhanced Salesforce integration; new healthcare, clinical data, and application licensing capabilities; improved DataStage integration; and core MDM enhancements. Key new features include probabilistic matching for BigInsights, Salesforce integration improvements, healthcare provider data warehousing enables, clinical data services, and application-based licensing options.
Customer-Centric Data Management for Better Customer ExperiencesInformatica
With consumer and business buyer expectations growing exponentially, more businesses are competing on the basis of customer experience. But executing preferred customer experiences requires data about who your customers are today and what will they likely need in the future. Every business can benefit from an AI-powered master data management platform to supply this information to line-of-business owners so they can execute great experiences at scale. This same need is true from an internal business process perspective as well. For example, many businesses require better data management practices to deliver preferred employee experiences. Informatica provides an MDM platform to solve for these examples and more.
Reference matter data management:
Two categories of structured data :
Master data: is data associated with core business entities such as customer, product, asset, etc.
Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail.
Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
Customer-Centric Data Management for Better Customer ExperiencesInformatica
With consumer and business buyer expectations growing exponentially, more businesses are competing on the basis of customer experience. But executing preferred customer experiences requires data about who your customers are today and what will they likely need in the future. Every business can benefit from an AI-powered master data management platform to supply this information to line-of-business owners so they can execute great experiences at scale. This same need is true from an internal business process perspective as well. For example, many businesses require better data management practices to deliver preferred employee experiences. Informatica provides an MDM platform to solve for these examples and more.
Reference matter data management:
Two categories of structured data :
Master data: is data associated with core business entities such as customer, product, asset, etc.
Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail.
Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
Data-Ed Webinar: Best Practices with the DMMDATAVERSITY
The Data Management Maturity (DMM) model is a framework for the evaluation and assessment of an organization’s data management capabilities. The model allows an organization to evaluate its current state data management capabilities, discover gaps to remediate, and strengths to leverage. The assessment method reveals priorities, business needs, and a clear, rapid path for process improvements. This webinar will describe the DMM, its evolution, and illustrate its use as a roadmap guiding organizational data management improvements.
Takeaways:
•Our profession is advancing its knowledge and has a wide-spread basis for partnerships
•New industry assessment standard is based on successful CMM/CMMI foundation
•Clear need for data strategy
•A clear and unambiguous call for participation
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
This presentation covers the definition of Master Data Management, outlines 5 essential elements of MDM, and describe 10 real-world best practices for MDM and data governance and 4 advanced topic areas, based on years of experience in the field.
Master Data Management's Place in the Data Governance Landscape CCG
For many organizations, Master Data Management is a necessity to ensure consistency and accuracy of essential business entities. It further plays alongside data architecture, metadata management, data quality, security & privacy, and program management in the Data Governance ecosystem.
Join CCG's data governance subject matter experts as they overview the fundamentals of Master Data Management at our Atlanta-based Data Analytics Meetup. This event will discuss how to enable components of data governance within your organization and review how to best leverage Microsoft's SQL Server Master Data Services.
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.
Customer Event Hub - the modern Customer 360° viewGuido Schmutz
Today, companies are using various channels to communicate with their customers. As a consequence, a lot of data is created, more and more also outside of the traditional IT infrastructure of an enterprise. This data often does not have a common format and they are continuously created with ever increasing volume. With Internet of Things (IoT) and their sensors, the volume as well as the velocity of data just gets more extreme.
To achieve a complete and consistent view of a customer, all these customer-related information has to be included in a 360 degree view in a real-time or near-real-time fashion. By that, the Customer Hub will become the Customer Event Hub. It constantly shows the actual view of a customer over all his interaction channels and provides an enterprise the basis for a substantial and effective customer relation.
In this presentation the value of such a platform is shown and how it can be implemented.
Requirements for a Master Data Management (MDM) Solution - PresentationVicki McCracken
Working on Requirements for a Master Data Management solution and looking for thoughts on how to approach the requirements? This is an overview presentation that complements my guide on how to approach requirements for a Master Data Management solution (Requirements for an MDM Solution). You may be able to leverage all or some of the approach described in this guide to formulate your approach.
Gartner: Master Data Management FunctionalityGartner
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm
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
Embarking on building a modern data warehouse in the cloud can be an overwhelming experience due to the sheer number of products that can be used, especially when the use cases for many products overlap others. In this talk I will cover the use cases of many of the Microsoft products that you can use when building a modern data warehouse, broken down into four areas: ingest, store, prep, and model & serve. It’s a complicated story that I will try to simplify, giving blunt opinions of when to use what products and the pros/cons of each.
Master Data Management - Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
Data Warehousing Trends, Best Practices, and Future OutlookJames Serra
Over the last decade, the 3Vs of data - Volume, Velocity & Variety has grown massively. The Big Data revolution has completely changed the way companies collect, analyze & store data. Advancements in cloud-based data warehousing technologies have empowered companies to fully leverage big data without heavy investments both in terms of time and resources. But, that doesn’t mean building and managing a cloud data warehouse isn’t accompanied by any challenges. From deciding on a service provider to the design architecture, deploying a data warehouse tailored to your business needs is a strenuous undertaking. Looking to deploy a data warehouse to scale your company’s data infrastructure or still on the fence? In this presentation you will gain insights into the current Data Warehousing trends, best practices, and future outlook. Learn how to build your data warehouse with the help of real-life use-cases and discussion on commonly faced challenges. In this session you will learn:
- Choosing the best solution - Data Lake vs. Data Warehouse vs. Data Mart
- Choosing the best Data Warehouse design methodologies: Data Vault vs. Kimball vs. Inmon
- Step by step approach to building an effective data warehouse architecture
- Common reasons for the failure of data warehouse implementations and how to avoid them
Presentation of use cases of Master Data Management for product Data. It presents the five facets of MDM for product Data (MDM for Material, MDM for Lean Managed Services, MDM for Regulated Products, Product Information Management, MDM for “Anything”) and how Talend platform for MDM can adress them
Introduction to Microsoft’s Master Data Services (MDS)James Serra
Master Data Services is bundled with SQL Server 2012 to help resolve many of the Master Data Management issues that companies are faced with when integrating data. In this session, James will show an overview of Master Data Services 2012, including the out of the box Web UI, the highly developed Excel Add-in, and how to get started with loading MDS with your data.
How a Logical Data Fabric Enhances the Customer 360 ViewDenodo
Watch full webinar here: https://bit.ly/3GI802M
Organisations have struggled for years in understanding their customers, this has mainly been due to not having the right data available at the right point in time. In this session we will discuss the role of Data Virtualization in providing customer 360 degree view and look at some of the success stories our customers have told us about.
Data-Ed Webinar: Best Practices with the DMMDATAVERSITY
The Data Management Maturity (DMM) model is a framework for the evaluation and assessment of an organization’s data management capabilities. The model allows an organization to evaluate its current state data management capabilities, discover gaps to remediate, and strengths to leverage. The assessment method reveals priorities, business needs, and a clear, rapid path for process improvements. This webinar will describe the DMM, its evolution, and illustrate its use as a roadmap guiding organizational data management improvements.
Takeaways:
•Our profession is advancing its knowledge and has a wide-spread basis for partnerships
•New industry assessment standard is based on successful CMM/CMMI foundation
•Clear need for data strategy
•A clear and unambiguous call for participation
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
This presentation covers the definition of Master Data Management, outlines 5 essential elements of MDM, and describe 10 real-world best practices for MDM and data governance and 4 advanced topic areas, based on years of experience in the field.
Master Data Management's Place in the Data Governance Landscape CCG
For many organizations, Master Data Management is a necessity to ensure consistency and accuracy of essential business entities. It further plays alongside data architecture, metadata management, data quality, security & privacy, and program management in the Data Governance ecosystem.
Join CCG's data governance subject matter experts as they overview the fundamentals of Master Data Management at our Atlanta-based Data Analytics Meetup. This event will discuss how to enable components of data governance within your organization and review how to best leverage Microsoft's SQL Server Master Data Services.
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.
Customer Event Hub - the modern Customer 360° viewGuido Schmutz
Today, companies are using various channels to communicate with their customers. As a consequence, a lot of data is created, more and more also outside of the traditional IT infrastructure of an enterprise. This data often does not have a common format and they are continuously created with ever increasing volume. With Internet of Things (IoT) and their sensors, the volume as well as the velocity of data just gets more extreme.
To achieve a complete and consistent view of a customer, all these customer-related information has to be included in a 360 degree view in a real-time or near-real-time fashion. By that, the Customer Hub will become the Customer Event Hub. It constantly shows the actual view of a customer over all his interaction channels and provides an enterprise the basis for a substantial and effective customer relation.
In this presentation the value of such a platform is shown and how it can be implemented.
Requirements for a Master Data Management (MDM) Solution - PresentationVicki McCracken
Working on Requirements for a Master Data Management solution and looking for thoughts on how to approach the requirements? This is an overview presentation that complements my guide on how to approach requirements for a Master Data Management solution (Requirements for an MDM Solution). You may be able to leverage all or some of the approach described in this guide to formulate your approach.
Gartner: Master Data Management FunctionalityGartner
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm
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
Embarking on building a modern data warehouse in the cloud can be an overwhelming experience due to the sheer number of products that can be used, especially when the use cases for many products overlap others. In this talk I will cover the use cases of many of the Microsoft products that you can use when building a modern data warehouse, broken down into four areas: ingest, store, prep, and model & serve. It’s a complicated story that I will try to simplify, giving blunt opinions of when to use what products and the pros/cons of each.
Master Data Management - Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
Data Warehousing Trends, Best Practices, and Future OutlookJames Serra
Over the last decade, the 3Vs of data - Volume, Velocity & Variety has grown massively. The Big Data revolution has completely changed the way companies collect, analyze & store data. Advancements in cloud-based data warehousing technologies have empowered companies to fully leverage big data without heavy investments both in terms of time and resources. But, that doesn’t mean building and managing a cloud data warehouse isn’t accompanied by any challenges. From deciding on a service provider to the design architecture, deploying a data warehouse tailored to your business needs is a strenuous undertaking. Looking to deploy a data warehouse to scale your company’s data infrastructure or still on the fence? In this presentation you will gain insights into the current Data Warehousing trends, best practices, and future outlook. Learn how to build your data warehouse with the help of real-life use-cases and discussion on commonly faced challenges. In this session you will learn:
- Choosing the best solution - Data Lake vs. Data Warehouse vs. Data Mart
- Choosing the best Data Warehouse design methodologies: Data Vault vs. Kimball vs. Inmon
- Step by step approach to building an effective data warehouse architecture
- Common reasons for the failure of data warehouse implementations and how to avoid them
Presentation of use cases of Master Data Management for product Data. It presents the five facets of MDM for product Data (MDM for Material, MDM for Lean Managed Services, MDM for Regulated Products, Product Information Management, MDM for “Anything”) and how Talend platform for MDM can adress them
Introduction to Microsoft’s Master Data Services (MDS)James Serra
Master Data Services is bundled with SQL Server 2012 to help resolve many of the Master Data Management issues that companies are faced with when integrating data. In this session, James will show an overview of Master Data Services 2012, including the out of the box Web UI, the highly developed Excel Add-in, and how to get started with loading MDS with your data.
How a Logical Data Fabric Enhances the Customer 360 ViewDenodo
Watch full webinar here: https://bit.ly/3GI802M
Organisations have struggled for years in understanding their customers, this has mainly been due to not having the right data available at the right point in time. In this session we will discuss the role of Data Virtualization in providing customer 360 degree view and look at some of the success stories our customers have told us about.
GlobalSoft is a MDM-focused software consultancy, specializing in Informatica MDM. GlobalSoft has been a long-term strategic partner of Informatica since the days of Siperian, providing project delivery and training services, as well as support and engineering services from our US & India offfices. Today, GlobalSoft has leveraged its deep product knowledge gained over the past 8 years and over 40 MDM projects into the preeminent service provider for Informatica MDM, and has used this knowledge to develop and offer specialized services and products for MDM.GlobalSoft headquartered in San Jose, CA maintains expert staff in the US and in India is capable of managing and delivering projects or augmenting existing project teams.
How In-memory Computing Drives IT SimplificationSAP Technology
Discover how the in-memory technology of SAP HANA can reduce complexity and simplify the IT landscape to foster real-time results, innovation and lower costs.
Learn the advantages and disadvantages of machine learning algorithms versus traditional statistical modelling approaches to solve complex business problems.
Best Practices to Navigating Data and Application Integration for the Enterpr...Safe Software
Navigating the complexities of managing vast enterprise data across multiple systems can be challenging. This webinar is your guide to navigating and simplifying enterprise integration.
As a technology leader, you may grapple with legacy systems, shadow IT, and budget constraints. Data and personnel silos often impede technological progress. FME champions integrating superior business systems to bolster your organization's digital strength – efficiently and affordably, using your current team and accessible services.
Join us and partner guest speakers from Seamless in an engaging session exploring the essential roles of data and systems in modern enterprises. We'll provide insights on achieving high-quality data management, establishing strong governance, and enabling teams to manage their data effectively. Delve into strategies for ensuring high-quality data and building robust governance structures, with tips and tricks along the way.
This webinar features real-life case studies demonstrating success in diverse industries. Learn cutting-edge strategies for data governance and system integration. Don't miss this opportunity to gain valuable insights and best practices for transforming your data governance and system integration processes.
Microsoft Fabric & Profisee MDM Are Better TogetherProfisee
Learn how Microsoft Fabric will help modern organizations unlock the power of their data and lay the foundation for the era of AI — directly from experts at Microsoft and Profisee. Watch the full webinar recording here: https://profisee.com/event/better-together-profisee-mdm-microsoft-fabric/
Illustrating the gaps in the traditional solutions proposed to achieve single customer view and also elaborates on how a unified system can bridge these gaps and solve data problems for good.
7 Emerging Data & Enterprise Integration Trends in 2022Safe Software
2021 was a year full of unexpected data integration challenges, but one thing that didn’t change was the continued growth of the importance and value of data. By watching our customers adapt and cope through the consistent application of technology, we’ve learned that the future can be quickly adjusted to if we have up-to-date and readily available data to make decisions.
As we consider the data integration landscape and look forward into 2022, we see a set of trends (some new, some old) that data leaders will need to consider as they work to provide competitive business value to their organizations:
- The Continued Importance of Spatial
- Data Ops as a Practice
- Rising Data Volumes Demand Data Quality
- Ubiquitous Hardware Supporting Augmented Reality
- Agile Enterprise Integration Effortlessly Connects Systems
- Real-Time Data Stream Processing
- Flexible, Hybrid Deployment Options
- Cost effective ARM based processing
In this webinar, join co-founders Don Murray and Dale Lutz as they offer insight and predictions on what’s to come in these areas. To follow, they’ll host a Q&A session where you can get feedback and advice on solutions to your data challenges.
Making Information Management The Foundation Of The Future (Master Data Manag...William McKnight
More complex and demanding business environments lead to more heterogeneous systems environments. This, in turn, results in requirements to synchronize master data. Master Data Management (MDM) is an essential discipline to get a single, consistent view of an enterprise\’s core business entities – customers, products, suppliers, and employees. MDM solutions enable enterprise-wide master data synchronization. Given that effective master data for any subject area requires input from multiple applications and business units, enterprise master data needs a formal management system. Business approval, business process change, and capture of master data at optimal, early points in the data lifecycle are essential to achieving true enterprise master data.
Bridging Data Gaps with a Solid Data Foundation - A Key Imperative for Today’...Denodo
Watch full webinar here: https://bit.ly/3CjoaxS
In this session, the panel will discuss the importance of laying out a solid data foundation for everything digital for any financial institution. The panelists from UFCU and DevFacto will share their journey and agile approach toward data management in a hybrid data environment.
From this session, you will learn how UFCU gained unprecedented agility in data management and built the foundation for a “member 360” view. Devfacto worked with UFCU to design and set up multiple service streams. To streamline cloud adoption, and seamlessly unify cloud and on-premise data sources. Denodo’s Logical Data Platform enabled UFCU with reusable Lego-like building blocks to create different data views for business teams.
Booz Allen Hamilton uses its Cloud Analytics Reference Architecture to build technology infrastructures that can withstand the weight of massive datasets – and deliver the deep insights organizations need to drive innovation.
Similar to Présentation IBM InfoSphere MDM 11.3 (20)
Artificia Intellicence and XPath Extension FunctionsOctavian Nadolu
The purpose of this presentation is to provide an overview of how you can use AI from XSLT, XQuery, Schematron, or XML Refactoring operations, the potential benefits of using AI, and some of the challenges we face.
E-commerce Application Development Company.pdfHornet Dynamics
Your business can reach new heights with our assistance as we design solutions that are specifically appropriate for your goals and vision. Our eCommerce application solutions can digitally coordinate all retail operations processes to meet the demands of the marketplace while maintaining business continuity.
Transform Your Communication with Cloud-Based IVR SolutionsTheSMSPoint
Discover the power of Cloud-Based IVR Solutions to streamline communication processes. Embrace scalability and cost-efficiency while enhancing customer experiences with features like automated call routing and voice recognition. Accessible from anywhere, these solutions integrate seamlessly with existing systems, providing real-time analytics for continuous improvement. Revolutionize your communication strategy today with Cloud-Based IVR Solutions. Learn more at: https://thesmspoint.com/channel/cloud-telephony
Introducing Crescat - Event Management Software for Venues, Festivals and Eve...Crescat
Crescat is industry-trusted event management software, built by event professionals for event professionals. Founded in 2017, we have three key products tailored for the live event industry.
Crescat Event for concert promoters and event agencies. Crescat Venue for music venues, conference centers, wedding venues, concert halls and more. And Crescat Festival for festivals, conferences and complex events.
With a wide range of popular features such as event scheduling, shift management, volunteer and crew coordination, artist booking and much more, Crescat is designed for customisation and ease-of-use.
Over 125,000 events have been planned in Crescat and with hundreds of customers of all shapes and sizes, from boutique event agencies through to international concert promoters, Crescat is rigged for success. What's more, we highly value feedback from our users and we are constantly improving our software with updates, new features and improvements.
If you plan events, run a venue or produce festivals and you're looking for ways to make your life easier, then we have a solution for you. Try our software for free or schedule a no-obligation demo with one of our product specialists today at crescat.io
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
Need for Speed: Removing speed bumps from your Symfony projects ⚡️Łukasz Chruściel
No one wants their application to drag like a car stuck in the slow lane! Yet it’s all too common to encounter bumpy, pothole-filled solutions that slow the speed of any application. Symfony apps are not an exception.
In this talk, I will take you for a spin around the performance racetrack. We’ll explore common pitfalls - those hidden potholes on your application that can cause unexpected slowdowns. Learn how to spot these performance bumps early, and more importantly, how to navigate around them to keep your application running at top speed.
We will focus in particular on tuning your engine at the application level, making the right adjustments to ensure that your system responds like a well-oiled, high-performance race car.
Utilocate offers a comprehensive solution for locate ticket management by automating and streamlining the entire process. By integrating with Geospatial Information Systems (GIS), it provides accurate mapping and visualization of utility locations, enhancing decision-making and reducing the risk of errors. The system's advanced data analytics tools help identify trends, predict potential issues, and optimize resource allocation, making the locate ticket management process smarter and more efficient. Additionally, automated ticket management ensures consistency and reduces human error, while real-time notifications keep all relevant personnel informed and ready to respond promptly.
The system's ability to streamline workflows and automate ticket routing significantly reduces the time taken to process each ticket, making the process faster and more efficient. Mobile access allows field technicians to update ticket information on the go, ensuring that the latest information is always available and accelerating the locate process. Overall, Utilocate not only enhances the efficiency and accuracy of locate ticket management but also improves safety by minimizing the risk of utility damage through precise and timely locates.
Graspan: A Big Data System for Big Code AnalysisAftab Hussain
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations.
These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI AppGoogle
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See My Other Reviews Article:
(1) AI Genie Review: https://sumonreview.com/ai-genie-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
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Présentation IBM InfoSphere MDM 11.3
1. InfoSphere User Group France MDM v11.3 New Features
Aomar BARIZ Information Governance Client Technical Professional Mobile:+33 6 73 48 40 72 E-mail: Aomar.Bariz@fr.ibm.com
2. InfoSphere MDM – Release Timeline
eGA: June 2013
Target eGA: Q4 2014
eGA: Oct. 2013
This Release Target eGA: June 27, 2014
v11.0
refresh
vNext
v11.0
V11.3
•Continued Integration of Development organization (all MDM Flavors)
•Simultaneous delivery of all supported platforms
•Simultaneous release with a number of InfoSphere offerings (incl. Information Server)
2
3. •InfoSphere MDM probabilistic matching engine for BigInsights: Enhances bulk search and performance for BigInsights matching.
•Salesforce.com integration: Improves Salesforce.com experience by leveraging InfoSphere MDM for search, remediation, and integration with external data. Invokes virtual MDM.
•IBM Health Care Provider data warehouse: Enables patient-centric analytics by pushing a 360-degree view of the patient into the warehouse.
•Clinical data services: Integrate patient clinical data for research, care coordination, and wellness initiatives.
•Application-based licensing: Offers new licensing and pricing options when acquiring MDM in support of other IBM products.
•InfoSphere DataStage integration: Reduces implementation time and cost by speeding and simplifying integration development both for initial load and ongoing production integration.
MDM Industry /LOB Solutions
•Collaboration Server free text search: Improves user experience with a more intuitive search facility powered by IBM Watson Explorer.
•Virtual MDM performance: Enhances control of record linking to reduce the risk of system performance issues.
Core MDM Enhancements
Overview of Key InfoSphere MDM v11.3 Features
MDM for Big Data
IIG Portfolio Integration
3
4. InfoSphere MDM v11.3 (Bali) Collaborative MDM Free Text Search with Watson Explorer
4
5. Positioning – Free Text Search with Watson Explorer
5
What are the business or technical benefits of solving this problem(s)?
What problem(s) and for whom (role, industry) does this capability solve?
How is this capability different in solving this problem than competitive offerings?
How does this capability solve this problem(s)?
•Searching PIM systems is not intuitive and often requires training
•Search performance becomes an issue when dealing with large volumes
•Providing external access to PIM data is complex and costly
•All roles across all industries are impacted:
•Analysts, Admins, Stewards, Executives, etc
•Retail, Banking, Industrial, Telco, All
•Intuitive access to data with Google-like capabilities
•Improved search performance with larger volumes
•Externalize search and access outside of the PIM system
•Data is pushed to Watson Explorer and indexed for high performance
•New static search bar on every screen allows users to search by key words and phrases
•Results page allows for opening a single record or multiple records for mass edit
•Competitors are not currently offering a free text search capability
•Watson search leverages best in class Big Data capabilities for high performance
•Only offering to provide a true web experience for search.
10. Search can be externalized for Enterprise access
Search directly on Watson Explorer
10
11. Capabilities
Enable or disable through configuration file
Static search bar on every screen
Search examples
–Term
–Term1 OR Term2
–Term1 AND Term2 (Term1 Term2 also works)
–Catalog:CatalogName Term
–Combine the above for complex searches
Search across specific catalogs
Launch in single edit or bulk edit
Limited use license of Watson Explorer included in the v11.3 bundle
11
13. Matching Approaches
Deterministic Rules-based fuzzy matching
Apply logical rules sequentially or hierarchically
Deterministic Rules-based exact matching
Deterministic Scoring-based matching
Probabilistic Self-learning algorithms
Compare records attribute by attribute.
Assign a score for each attribute match.
If the total score is high enough, they match.
How do you decide how much a partial date match should be worth? An edit distance of 2? A nickname match?
Account for misspellings and typographical errors
Metaphone
Edit distance
The algorithm learns how to score attributes from the data itself
How common are partial date matches within your data?
How common are nicknames?
Tuned to your data
Big Data needs more sophisticated capability
13
14. Using out of the box fuzzy functions to enable accurate data searching/matching in your Hadoop environment
Nov 6,
Phonetics Mohammed vs. Mahmoud
Synonyms Andrew = Andy George = Jorge 1st = First
Abbreviations AIG = American International Group Road = Rd
Concatenation Van de Velde = Vandevelde
Misalignment Kim Jung-il = Kim il Jung
Edit Distance 867-5309 ~ 876- 5309
Region Specific トヨダ = トヨタ株式会社
Date Similarity 01/01/1973 ~ 01/03/1973
Proximity Geocodes and great-circle distance
Noise Words Roadster Inc. = Roadster
Typographical Errors John Smith vs. John Snith
14
15. C. Johnson 123 Main Street 512-545-1234
CRM
Supply Chain
Fulfillment
Support Ticketing
External Sources
3rd Party
Chris Johnston 123 Main Street 512-554-1234 Shipping: 456 Pine Ave
Christine. Johnson 123 Main Street Call length Semi-structured notes Satisfaction
C. Johnson Main Street 512-554-1234
C. Johnson 125 Main Street 512-554-1234
ChrisJohnson65 “Likes” Clothes, Camping Gear
@ChristyJohnson65
Christy65 Circle / Network data
Order Mgmt.
Internal / Structured
External / Unstructured
Web
Chris.johnson@cj.net
Big Match empowers customer analytics at Hadoop scale
Big Match matches all these records
Big Match combines the MDM probabilistic matching engine & pre-built algorithms & BigInsights for customer matching natively within Hadoop
Increased Value of Customer only if…
Christine Johnson Married 1 child 4/15/74
Christy65 Mail Order responder Specialty Apparel Partner Sales data
VIP: Gold Customer Sat: 80% Influence Score: 8/10
15
16. What is Big Match
Big Match allows you to run the MDM probabilistic matching engine natively within IBM’s open source Hadoop distribution (Infosphere BigInsights)
Your clients are implementing customer analytics projects using Hadoop today
Use Big Match to differentiate the IBM stack – no other vendor has it
Infosphere Master Data Management (Advanced Edition, Standard Edition, Collaborative Edition)
16
17. Big Match as a foundation of your customer analytics in Hadoop
Accurate – Matches via statistical learning algorithms based on your data (customer see improvements between 5-15%)
Simple & Fast Time to Value - Hours to use configurable pre-built customer algorithms, instead of weeks or months of developing code
Performance - Hours to match initial data sets of big data volumes via use of MapReduce distributed processing
Proven - Leverages the experience of over 10 years and 900 customers across worldwide deployments dealing with individuals and organizations
Is your client using Hadoop within customer analytics? Then they need Big Match
17
18. InfoSphere MDM v11.3 (Bali) IBM Stewardship Center for - Physical MDM, Individual Domain
19. Three takeaways
1.Deliver a differentiating, prescriptive user experience for LOB users
WHY?
1.LOB users need to explore and discover how master data can help their business
2.Knowledgeable LOB users make the most informed data quality decisions & their involvement increases their confidence in master data
20
Stewardship Center is a physical MDM application for LOB users and stewards
20. Positioning – IBM Stewardship Center
21
What are the business or technical benefits of solving this problem(s)?
What problem(s) and for whom (role, industry) does this capability solve?
How is this capability different in solving this problem than competitive offerings?
How does this capability solve this problem(s)?
•Data quality decisions are low quality because they do not include LOB user insight
•LOB users do not trust master data because they struggle to understand how their system’s data contributes to the golden record
•Stewardship managers struggle to show their team’s value & contribution to the business
•All roles across all industries are impacted:
•Analysts, Admins, Stewards, etc
•Retail, Banking, Industrial, Telco, All
•LOB discovers MDM value by browsing and investigating MDM, gaining new insights
•If issues are identified, LOB users can make master data updates directly
•Direct data quality decisions to the right LOB users at the right time
•Stewardship dashboard enables stewardship managers to demonstrate efficacy and make informed decisions to improve team performance
•IBM Design Thinking brings the prescriptive UX necessary to leverage knowledge workers
•Enable data quality users to collaborate using social and mobile features
•Business rules tailor which user is assigned a given task based on task type and entity segment
•The dashboard displays task breakdown and team/individual performance by reporting from the Stewardship Center’s data warehouse
•Prescriptive OOTB UX allows Stewards and LOB users to commune on data quality decisions using social collaboration and mobile
•Keep the business connected to master data with mobile stewardship, approval, & notifications
•Dashboard allows for the quick assessment the data quality metrics, team monitoring and rerouting
•Intelligent Inbox prioritizes work w/ auto-escalation
•Quickly extend or customize the Stewardship Center’s WF or UI using MDM AT & IBM BPM
•Options for Cloud deployment
21. 22
LOB Knowledge Workers
LOB Owners & Governance Team
IT Stewards
Web
Mobile
Social Collaboration
Data Quality Application
Business Processes
Analytics
Stewardship Center
Customer Centricity
Know Your Customer
Operational Excellence
Dashboard
Workflow & Rules
Comprehensive data quality application delivering business confidence
22. Capabilities needed to deliver data quality to the business?
Ensure most knowledgeable LOB users contribute in quality decisions
Provide LOB users business context and prescriptive experience
Align stewards and LOB users to efficiently remediate data quality tasks
Include the right participant at the right time within the data quality process
Ensure task ownership and accountability with traceability
Demonstrate team performance and provide management insight
23
23. Stewardship Center keeps the business connected to master data, driving ownership
LOB users
Explore, learn, and discover master data
–Discover relationships
–Data quality root cause analysis, take corrective action
–Master data survivorship
–Review/approval and notifications for critical data issues
–Stay connected with mobile stewardship
–Only view appropriate information
24
24. Stewardship Center increases data quality through LOB user and steward collaboration
Stewards and LOB user
Cross team connectedness with social collaboration
Data quality workflow assigns tasks to the right user at the right time
Automate common decisions reduce time and cost of human involvement
Increase throughput by including LOB users while infusing business knowledge into DQ decisions
Increase business confidence and ownership of master data
Prescriptive business tools for data maintenance and matching records
25
25. Stewardship Center provides visibility and insight to ensure effective team performance
Data Steward Manager
Dashboard optimized for data steward manager activities
Quickly assess areas of risk and take corrective action
Identify active stewards and commune
Track at risk/high priority tasks for better team mgmt and resource loading
Identify data quality trend/bottlenecks and make informed improvements
Ensure task ownership and accountability along with traceability
26
26. Complete task visibility
Identify data quality trends
View team and status
Commune with team
View team’s tasks and manage
Data Steward Management Dashboard
27
28. All CEOs; n = 229
Which technology-enabled capabilities will be an important area of investment to improve your business over the next five years?
Source: Gartner Report - CRM in a Sea of Change 2013
29
Gartner Technology Investment Survey 2013
29. What are the primary objectives of your 2013 CRM programs?
0 10 20 30 40 50
Improve customer data quality
Increase customer loyalty
Improve lead quality and conversion
Increase customer retention
Create a single view of the customer
Enhance cross-sell or upsell of products
and services
Increase customer satisfaction
Increase sales revenue
Increase acquisition of new customers
Enhance customer experience
Percentage of Respondents
Revenue
Information
Loyalty/
Satisfaction
Source: Gartner Report - CRM in a Sea of Change 2013
n = 190
Gartner CRM Survey 2013: Top 10 CRM Objectives in the U.S.
30
30. Source: Aberdeen Group, July 2011
A CRM assessment report published by Aberdeen in 2011 showed that Peak CRM Performance is directly related to the accuracy and availability of customer records
n = 261
Gartner believes that bad data quality is the #1 reason why CRM projects to fail
Data Quality and Accessibility – by Best in Class
31
33. Customer Relationship Mgmt
Improve win-rates & seller productivity
Contact
• Identify duplicate customer and prospect records & reduce duplication at the point of entry
• Find the right customer faster by leveraging advanced search capabilities from MDM
• Enrich customer data in Salesforce with collective knowledge from internal & external data sources
• Identify relationships between customers/entities
InfoSphere MDM can help organizations optimize client-focused
initiatives by delivering a Single View of Customer
34
34. An InfoSphere MDM powered Salesforce initiative can deliver real business benefits
35
35. InfoSphere MDM – SFDC solution capabilities
36
InfoSphere MDM Powered Probabilistic Search
Publish enriched master information from InfoSphere MDM to SFDC
Event Notifications
Search for Accounts from SFDC as well as from other sources
Enrich Account information in SFDC by leveraging the broader enterprise master information in InfoSphere MDM
Automatically receive MDM events in SFDC whenever a SFDC record gets added, updated or linked in MDM
Enhanced Security using WebSphere Cast Iron
Secure data and calls between InfoSphere MDM (on-premise) and SFDC (an external SaaS application)
Perform Bulk data ops using InfoSphere Information Server (SF-Pack)
Perform Bulk data movement from MDM to SFDC using Information Server (SFPack)
36. IBM MDM
No Inbound No In-out bound
IS-SP
HTTPS
JMS
Queue
HTTPS
SSL
Tunnel
1
2
3
1
Real-time Sync
2
Near Real-time Sync with reliable
queuing
3
Batch Import/Export using InfoSphere
Server Pack (IS-SP) for SFDC
Customer Firewall
InfoSphere MDM-Salesforce Integration Architecture
37
38. User Technologies
41
An MDM Hub is only useful when integrated with the “Extended” enterprise.
MDM projects require a high performance ETL solution for loading data into and extracting data from an MDM hub.
The ETL solution should be integrated so as to hide the complexity of the underlying MDM data model and to make integration easy.
IBM MDM by itself, not provide a fully integrated, end –to-end integration , quality and data governance for master data
The bundled 3rd party Clover ETL is just a point solution for ETL
Clover ETL is not integrated with other IBM IIS components
MDM bundles only IIS for Data Quality
IBM MDM by itself, does not provide end-to-end metadata management for MDM data
Changes in the MDM model are not automatically shared across integration components and governance tools.
MDM assets are not „natively‟ available to the Information Server Information Governance Catalog (IGC)
The Problem?
41
39. 42
IBM IIS Enterprise Edition bundled with IBM MDM (with license restrictions) providing end to end ETL, governance and data quality
Out-of-the-box MDM Connector Stage within InfoSphere DataStage/QualityStage Designer that simplifies MDM load and extract for DS/QS developers
InfoSphere MDM metadata in IIS drives automation and makes integration configurable so very little development is required for MDM data load and/or extract
Enables configurable data integration for MDM
Provides governance for the MDM information supply chain
Provides design lineage through MDM metadata in IGC
Clover ETL is removed from MDM V11.3 as a bundled component
Customers can obtain licensing and support directly from Javelin in order to use existing Clover Graphs with MDM V11.3
The Solution?
42
40. User Technologies
Build a MDM metadata model to describe assets in the IS repository Enables all tools in the suite, particularly IMAM, IGC, DataStage and DataClick to work with MDM assets
Build export functions into the MDM workbench Allows individual MDM users to document and manage their projects metadata assets for use by IS repository
Build a MDM Connector that can consume the MDM metadata and enable the memget and memput MDM interactions memget and memput interactions are broadly used to read and write data resp. Implement the MDM Connector over the Java Integration Stage Leverage the Parallel engine capability
Bundle Information Server Enterprise Edition with MDM Limited license terms Gives MDM customers the relevant Information Server functions out-of-the-box
How are we integrating?
43
41. Metadata Admin
DataStage/Quality Stage
Job Developer
XMeta
(MDM, ASCL)
MDM Developer
MDM Workbench
Exports the project metadata as XMI files for use by MDM Connector
XMI Files
SCM or DevOps Repository
Import XMI files, analyze, preview and upload to Metadata Server
IMAM Asset Manager
[ MDM Design MetaData ]
DataStage/ QualityStage Designer
Configure MDM Stage with MDM Hub Connection and other settings
Query MDM Model in XMeta
MDM Model Bridge
XMeta (DSX)
Persist Stage configuration in DSX Model
Compile, Deploy & Test Jobs
[ Job MetaData ]
MDM Connector Usage (Design time)
45
43. 47
Notable:
No support for Power Linux
Windows only supported for Standard Edition
WAS only (started previously)
No FireFox support for Collaborative Edition
Information Server v11.3 release has two delivery tiers (platforms)
Latest information online – Refer to InfoSphere MDM System Requirements on ibm.com
Component
Flavor
Version(s)
Notes
Operating System
AIX (Power)
Solaris (SPARC)
Linux (RHEL)
Linux (SLES)
zLinux (RHEL)
zLinux (SLES)
Windows
v6.1 and v7.1
v10
v6
v11
v6
v11
2008R2, 2012
X86-64 only
X86-64 only
SE ONLY
App Server
WAS
v8.5.5
Database
DB2 LUW
DB2 for z/OS
Oracle
v10.1, v10.5
v10.1, v11
11g R2, 12c
Web Browser
IE
FireFox
9, 10
ESR 24
Not CE
Other
Information Server
MQ
BPM
Portal Server
v11.3
v7.5
v8.5.0.1
V8.0.0.1
Tiered Release
InfoSphere MDM v11.3 – Supported Platforms
44. 48
Makes it easier for customers to deploy an MDM environment (e.g. Development)
There should not be an expectation that all deployment scenarios are supported with the Supporting Programs … Additional licensing (e.g. RAD) is often required!
Limitations/Restrictions:
–Primary Limitation – Only when in support of InfoSphere MDM
–See LI for others
Important Note: The LIs for the Supporting Programs is also in effect
Supporting Programs for InfoSphere MDM v11.3
IBM Rational Application Developer for WebSphere Software v9.0
IBM DB2 Enterprise Server Edition V10.5
IBM Content Integrator 8.6
IBM Cognos Business Intelligence V10.1.1
IBM Cognos Business Intelligence Modeling v10.1.1
IBM Cognos Business Intelligence Samples v10.1.1
IBM Cognos Supplementary Language Documentation v10.1.1
IBM Process Server Standard v8.5
IBM Process Server Standard for Non-production Environment v8.5
IBM Process Center Standard v8.5
IBM Process Designer v8.5
IBM InfoSphere Information Server Enterprise Edition v11.3 (for MDM Editions)
IBM InfoSphere Information Server for Data Quality v11.3 (for RDM and CDH Stand-alone)
IBM InfoSphere Data Explorer v9.0
IBM InfoSphere BigInsights Standard Edition v2.1.2
IBM InfoSphere Blueprint Director v2.2
IBM WebSphere Message Broker v8.0.0.3
IBM WebSphere Message Broker Connectivity for Healthcare v8.0
IBM WebSphere Application Server Network Deployment V8.5.5
IBM WebSphere Application Server Base 8.5.5
IBM WebSphere MQ V7.5
IBM WebSphere Portal Server 8.0.0.1
IBM Installation Manager & IBM Packaging Utility for Rational Software Development Platform v1.7
IBM Security Directory Server v6.3.1
IBM Support Assistant Data Collector v2.0.1
Supporting Programs – v11.3