Global DataOps

IBM Virtual Community Day: Business Ready Data for AI

By Katie Kupec posted Thu April 18, 2019 04:17 PM

  

Join data and governance experts at this free, online conference! 


Hear from your peers, partners, and IBM experts around creating Business-Ready Data for AI & digital transformation, driven by IBM Unified Governance and Integration.

You and your team can join for the entire day or you can attend as many sessions as you find appropriate for your needs. If you attended THINK and thought that your team member should have been there, this is the event for you!

Event details:

  • April 25 from 7am-5pm EDT / 11am-9pm GMT
  • 20+ industry-leading professionals presenting
  • 3 concurrent tracks covering the journey to AI, technical deep-dives, and success stories. 


To learn more and to register, click here!

Start Time Journey To AI Technical Deep Dives Success Stories
7am EDT Speakers Andre De Locht of IBM Glenn Steffler of IBM John McKeever and Justin McCamish of Data Migrators and Elvis Zgomba of IBM
Title Data Governance Has Evolved from "Should Do" to "Must Do"-But How to Prove Its Value? Exploit the Full Potential of Real-Time Analytics in Your Data Lake Rapid DataStage Accelerators
Abstract As organizations become data-driven and “success” increasingly correlates with “insights,” trust and understanding regarding the data becomes the foundational prerequisite of AI-supported analytics. Data governance has therefore evolved from “should do” to “must do.” But senior leadership needs to see proof points and a demonstration of business value—calculated in hard numbers—before they will dedicate resources. From identification and validation of the use case to the cost reduction opportunity and the incremental business value, this session shares proven best practices and model gleaned from numerous client engagements to help you prove the business case for data governance. A data lake offers significant potential for enhancing enterprise analytics and reporting. Learn how IBM’s Data Replication solution can add significant value to your data lake by delivering critical data from source systems to the data lake in real-time. We will explain how the integration of IBM’s Data Replication and BigIntegrate platforms provides a powerful solution through a discussion of customer use cases. Want to move to the latest version of IBM InfoSphere DataStage but aren't sure where to start, how long an upgrade might take, or the cost involved? Our new Rapid DataStage Upgrade offering removes these anxieties by automating the estimation and upgrade steps. Your code is delivered to a target version and is integration-testable in just days, via a flexible, monthly software subscription and elite services package. This offering minimizes or eliminates code freezes and downtime while reassuring both developers and budget-holders with highly visible progress. The rapid upgrade experience leaves you with your upgraded code under version control, plus opportunities to further improve testing and delivery practices through DevOps techniques.
8am EDT Speakers Priyanka Jain of IBM   Brian Eckert of InfoMagnetics Technologies Corporation (IMT)
Title Data Discovery and StoredIQ   Master Data Management
Abstract Coming Soon   Coming Soon!
9am EDT Speakers Daniel Hernandez and Michael Lock
Title Building a Foundation for AI with Data Excellence
Abstract

Abstract Coming Soon!

10am EDT Speakers Jo Ramos, David Nelson, and John Van Buren of IBM Ambal Balakrishnan of IBM Martin Oberhofer and Scott Schumacher of IBM
Title Successful Data Lake Implementation through Data Integration, Data Quality and Data Governance IBM InfoSphere Regulatory Accelerator IBM Master Data Management Innovation focus: Applied Machine Learning for Data Stewards and Future Model Design
Abstract Implementing a data lake is a cornerstone of modernizing an enterprise analytics architecture. This session will explore how growing evidence suggests that the difference between successful and unsuccessful data lakes is often determined by whether data integration, data quality and data governance are addressed effectively. The session will use real examples of successful and unsuccessful data lakes to illustrate best practices. Abstract Coming Soon!  This session will look at the latest MDM release and the machine learning assisted data stewardship.    Stewardship tasks are an important part of MDM, reviewing and resolving suspected duplicates to optimize downstream business process errors.  This capability brings a modern user interface and applies machine learning techniques to reduce the number of clerical stewardship tasks required based on prior actions taken.  We’ll also preview innovations designed to reduce the effort involved in establishing an MDM system configuration by taking a data-first approach.  Rather than spending many person-weeks defining or mapping to a known data model, these data first techniques build an adaptive data model based on the data itself. (need to tie-in exactly what ML is involved here beyond just auto-classification)
11am EDT Speakers Brylan Achilles and Brian Reagan of Actifio and Peter Costigan of IBM  Amir Jaibaji and Thomas Hampp of IBM Jack McCarthy of The State of NJ Judiciary
Title Accelerate Application Modernization with IBM InfoSphere Virtual Data Pipeline GDPR: Overcoming Data Discovery Hurdles with the Next Generation of IBM StoredIQ How the State of New Jersey Used Unified Governance for Criminal Justice Reform
Abstract Learn how IBM InfoSphere Virtual Data Pipeline enables: Developers and DBAs to instantly provision or refresh database copies, regardless of size, on-premises or in any cloud; integrate database copy creation and presentation with developer tools like IBM UrbanCode, Chef, Puppet, Ansible or Salt; and deliver database copies while ensuring that all security policies are maintained including access controls, masking and encryption. With a combination of real-world customer examples and live demonstration, this session will provide a practical understanding of the InfoSphere VDP solution, the business and technical impact delivered, and how to get started quickly. Confidently uncovering where personal or sensitive information exists across petabytes of unstructured data, spanning dozens of data sources and living on-premises or in the cloud can be a daunting task. In this session, we'll discuss the latest technology from IBM StoredIQ that will help you overcome these hurdles. We'll present new solutions for dealing with cloud data, show you how the solution can quickly give you confidence that large volumes of data are free from sensitive data and go into detail on how machine learning can help improve the accuracy of sensitive data discovery. New Jersey legislation requires the courts to run a risk assessment against a defendant to determine the risk for non-appearance or likelihood to re-offend. The Public Safety Assessment (PSA) application sweeps criminal justice system databases to build a risk profile. Using Master Data Management (MDM) the assessment completes in seconds. IBM InfoSphere Information Server’s Data Stage analyzes party data from source systems through the MDM hub. It matches and links independent parties, then selectively retrieves information from respective sources. The PSA application uses these to score and build the risk assessment. New Jersey’s criminal justice reform is a resounding success—the state’s jail population dropped 35% in 2017.New Jersey legislation requires the courts to run a risk assessment against a defendant to determine the risk for non-appearance or likelihood to re-offend. The Public Safety Assessment (PSA) application sweeps criminal justice system databases to build a risk profile. Using Master Data Management (MDM) the assessment completes in seconds. IBM InfoSphere Information Server’s Data Stage analyzes party data from source systems through the MDM hub. It matches and links independent parties, then selectively retrieves information from respective sources. The PSA application uses these to score and build the risk assessment. New Jersey’s criminal justice reform is a resounding success—the state’s jail population dropped 35% in 2017.
12pm EDT Speakers Shreyas Shah and Pankuj Chachra of IBM Somil Kulkarni of IBM Candace McCabe, JB Hunt Transport
Title High availability MDM for always-on customer applications Automagic ETL-Smarter, Faster, Simpler, More Resilient Information Cataloging to Enable Governance and Value in the Information Economy
Abstract Today's organizations are realizing the benefits accurate and trusted master data brings to their mobile and online applications. Companies of all sizes are looking at how to deliver master data to downstream applications in a zero-downtime environment.  Another recent delivery provides an operational cache environment for high capacity and high performance read access. With low latency use cases with the highest demands on responsiveness (e.g. mobile user interactions) can be realized. The cache can be set up in single or multiple data centers, either locally or globally as business processes require.  We’ll also look ahead at forthcoming capability designed to make connecting these consuming SaaS applications easier via a robust application integration framework.   Do the letters ETL make you cringe? Learn how ETL is made super easy with IBM InfoSphere DataStage. A data engineer can easily build new jobs using an ML-powered Smart Palette, group similar jobs with an ML-powered Smart Cluster, and use an ML-powered Smart Stage Suggestion that suggests what stage comes next. GitHub integration enables a data engineer to work on multiple versions of a job and easily integrate changes into CI/CD pipelines. Checkpointing adds resiliency by automatically restarting failed jobs. Come see how all of these and other cool capabilities are possible! Teddy Roosevelt said, “Do what you can, with what you have, where you are.” Data has been described as the new oil, the new bacon, and the world’s newest currency. Information governance is key to capitalizing on your investment in your data. At the heart of governance is cataloging. Not knowing what data exists, where it is, how to protect it, how it complies with laws, what its level of quality is, or its context, makes it difficult, if not impossible to monetize the world's newest and, arguably, most valuable commodity. This session will center on the reasons for cataloging your information, in all of its various forms and locations, to address concerns in security, quality, compliance, eDiscovery, and more.
1pm EDT Speakers Jason Caplan of the Vanguard Group Kevin Wright of Mastech InfoTrellis, Inc Marc Hebert of Estuate, Inc. and Chris Durst of Integro
Title Evolving Data Governance for Vanguard's Next-Gen Infrastructure  IBM InfoSphere MDM Advanced Edition in Modern Retail Clients - Case Studies & Commentary including GDPR & Consent Management Coming Soon!
Abstract Vanguard established its data governance program to answer four basic questions: What data do we have? Where is the data located? What systems are using that data and for what purpose? Does that use meet regulatory and business requirements? A comprehensive set of processes and procedures was established to achieve these objectives. This session will discuss how the shift in the Vanguard IT infrastructure and delivery methodology impacted our data governance process and procedures. and how we are evolving our data governance program with the help of IBM InfoSphere Information Governance Catalog 11.7 to support the new IT landscape and reduce the amount of manual entry. a. Mastech InfoTrellis, a Gartner-recognized Master Data Management Systems Integrator, has 12 years of experience implementing data management programs.  With a particular focus on the IBM InfoSphere MDM suite, we have a long history of successful implementations across all industries, but we've derived some particular insights from implementing MDM for Retail (or CPG, etc) clients.  Please come join us for this discussion as we discuss some of our past project successes, results, and, lessons-learned from those engagements; additionally, we'd like to share what we're seeing in the modern market as compliance issues like GDPR and CCPA come into a sharp focus for the industry overall and MDM/UG&I in particular. Coming Soon!
2pm EDT Speakers Jo Ramos and Emma Tucker of IBM David Douccette of Lighthouse Computer Services, A Converge Company Jeff Crose of Alaska Airlines
Title Demystifying Metadata Management and Data Catalogs: The Missing Link to AI MDM Express for Retail Banking  Alaska Airlines Flies Safely with Fast, Accurate Test Data Management
Abstract For years, organizations have been diligently collecting, organizing and storing data while ensuring it conforms to regulatory and corporate governance policies. Now as organizations strive to make the leap to AI, how can all of this collected data be flipped into sources of knowledge? In this session, you'll learn about IBM's Unified Governance and Integration vision and strategy, and how IBM has brought about the unification of various governance capabilities, supporting cloud and on-premises structured and unstructured data. Join us for a discussion and demonstration of our next-generation data catalog that infuses AI to automate governance and support regulation and quality, integrated with data science and analytics. For banks looking to improve their Know Your Customer (KYC) capabilities -- to manage risk as well as to improve customer service - Single customer view provides a single, authoritative repository for managing and distributing accurate customer data for all lines of business and disparate systems.  Benefits include:

o Reduce Operational cost

o Better customer experience and personalization

o Enhanced & unified view of Customer 

o Contextual relationships and analysis

o Elevated customer service opportunities increasing revenue
Alaska Airlines, like all airlines, must carefully plan for and calculate accurate weight and balance for every flight. We implemented a SmartLoad system in 2014 to automate the weight and balance calculation process. The system has complex feeds from multiple systems on heterogeneous platforms, and requires extensive ongoing development and testing to maintain currency. It was a real challenge for us to provision and refresh fresh test data for this environment quickly and accurately. We solved this problem with IBM InfoSphere Optim Test Data Management by creating right-sized data subsets with masking of sensitive data elements.
3pm EDT Speakers Rakesh Ranjan and Simao Liu of IBM Beate Porst of IBM Marc Hebert of Estuate and Chris Durst of Integro
Title Cognitive Data Governance at Enterprise Scale Data Integration and Transformation from IBM: What's New and Where Do We Go from Here? Coming Soon!
Abstract Organizations are under two competing business goals: running a profitable business while reducing risk in conforming to laws and regulations that are evolving monthly. How can you survive and thrive in this regulatory climate while being subject to existing regulations such as CCAR, FDIC, SOX, General Data Protection Regulation (GDPR), UK Data Protection Act (DPA) plus upcoming mandates like California’s CCPA and other state laws that are sure to follow shortly? Join us at this demo to see how IBM applies machine learning to understand and simplify the complexity of these regulatory mandates to accelerate your journey to readiness and reduced risk. In this session, we look at how the IBM InfoSphere Information Server has been updated and modernized to serve modern-day demands on the data integration and transformation capabilities offered through the portfolio. We will dive deeper into what's new and exciting, and talk about our short- to longer-term roadmap as well. Coming Soon!
4pm EDT Speakers Desiree Amirgholi of IBM Ron Davis of Prolifics Dennis James of Element Blue
Title Regulatory Compliance and Data Privacy: Building Blocks and Success Stories Data-Centric Evolution-Are You Ready for It? DSXchange Community Turning Data into Governance
Abstract Most organizations spend a great deal of time and energy wrestling dirty, poorly-integrated data. They either cannot find the right data or cannot trust the data they find. On top of that, they must deal with multiple regulations in their industry that are barriers to self-service and data democratization. As a result, they try to fix their data through a variety of labor-intensive tasks, from writing custom programs to global replace functions—overall diminishing their productivity as data analysts and data scientists. This session will take you through the journey of data curation and governance using AI and machine learning at enterprise scale. Coming Soon! Coming Soon!

#UGICommunityDay
#IBMCommunityDay
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