Presented by Donna Burbank

With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in data architecture, along with practical commentary and advice from industry expert Donna Burbank.

Presented by John O’Brien

We keep hearing that data modeling is dead or that it’s no longer relevant with modern data technologies when in reality, it’s more important than ever. Actual data modeling seeks to demonstrate a thorough understanding of your business functions and goals to represent them accurately with data collected from its activities. With this mindset toward data modeling, you can decide which data modeling techniques are well-suited, which database technologies are ideal for its implementation, and how to distinguish data transport methods. This session will explore several essential aspects of how data modeling is critical for data management and analytics capabilities.

You will learn:

• how business understanding is different from its systems
• how data persistence and transport differ from their semantic meanings and changes
• the implications of various database technologies on data integration, management, and analytics

Presented by David Wells

Data management architecture has changed substantially in recent years and continues to evolve at a steady pace, with much of the evolution driven by data demands of advanced analytics and data science. Many architectural concepts and frameworks have emerged recently including data fabric, data mesh, and data network (aka, zero copy integration). In this session we will explore these trends to understand the purpose and structure of each and to highlight the similarities and differences. Perhaps most importantly, we’ll consider how modern practices can evolve your existing architecture without requiring that you rebuild your data management approach from scratch.

You will learn:

• The what and why of data fabric, data mesh, and data network
• How fabric, mesh, and network can work together
• How to avoid “Big Bang” with planned evolution of your architecture

We will resume at 11:30am

Presented by April Reeve

Is Master Data Management still needed? Has it been replaced by other modern architectural solutions?  MDM as a capability is still a critical part of every enterprise application architecture but the technologies used to accomplish it are changing: supporting a broader group of use cases, becoming faster, and (hopefully) less expensive.

“Master Data Management” has been an important capability in most organizations since well before there were computers (all businesses need to manage their customer lists). The need for Master Data Management systems was broadly recognized in the 1990s, although some industries always had the capability since they had computer systems.

Modern MDM isn’t just focused on analytics but a broader group of operational stakeholders and leveraging emerging data technologies such as machine learning and artificial intelligence as well as older technologies like graph, that is coming into it’s own in critical areas such as MDM and metadata management.

This presentation will cover:

• Master Data Management and why we need it
• Traditional Master Data Management
• Changes in Master Data Management for Modern Data Architectures
  • Operational MDM
  • Using graph databases
  • Leveraging machine learning
• Does Master Data Management have a future?

Presented by: Chris Marino

For years, a notable large retailer has been struggling to manage a vast array of the learning content of different types, formats, and systems. Though the content itself was of high value, it was too often hidden in siloed systems, or difficult to find due to lack of integration across platforms. To address this long-standing challenge, this retailer developed a graph database to bring together diverse content and surface it via a semantic search and entity association engine.

This detailed case study will walk through the retailer's journey, including the early stages of planning, software selection, Agile design and development, and ongoing iteration to add new features. It will also include the proven methodology applied to engage business users in the design process, helping to drive the adoption of this highly formative new tool for the large retailer.

Attendees of the session can expect to learn:

• The value of graph databases to unite content (ranging from structured to unstructured) and surface key connections;
• Specific approaches and methodologies for use case development, software selection, and Agile planning and integration; and
• Techniques to engage business users in highly complex design and build efforts.

Presented by Zhamak Dehghani

According to ThoughtWorks , “Data Mesh is an analytical data architecture and operating model where data is treated as a product and owned by teams that most intimately know and consume the data.” Join us in this keynote presentation to hear directly from the Founder of Data Mesh and author of the book “Data Mesh: Delivering Data-Driven Value at Scale”. During our keynote presentation, Zhamak will discuss the underlying principles of this emerging data architecture designed to assist organizations on their journey to becoming data-driven.