Organizations today are facing an opportunity that they must seize. If they could access the full wealth of their data that is distributed across cloud and on-premises, they could leverage the data for advanced analytics and operational efficiencies, leading to faster time-to-insights and more impactful decisions. However, the greatest barrier to seizing this opportunity is the fact that valuable enterprise data is distributed across many IT systems, each with its own data models, semantics, and interfaces. Distributed data has long been a challenge to leveraging and reusing data on premises, and the distribution is broadening as organizations embrace data architectures that are hybrid or multi-cloud.

In this presentation, data thought leader Philip Russom (formerly an analyst with Gartner, TDWI, and Forrester) will explain the opportunities and challenges of today’s cloud and on-premises distributed data, while highlighting logical solutions and desirable business use cases based on data virtualization.

Data-led transformations are becoming more prevalent in recent years, across numerous industries. More and more senior leaders are looking for data to drive their business decisions and impact their bottom line. One key challenge facing such businesses is the ability to pivot to new technologies while maintaining investments in legacy systems they have grown to rely on. In an age where automation, internet-scale search, and advanced analytics are driving many new advances, it is important to understand that this is not only a pivot in terms of technologies, it is a pivot in terms of how we think about and utilize data of different types. Traditional systems since the 1970’s have been built around database concepts where data is physically pipelined, mapped together, statically modeled, and locked away in vaults. The types of vaults have evolved over time from basic databases, to data warehouses, to data lakes, to lake houses, and so on. The fundamental premise remains: data is placed into sealed containers, such that the critical approach is around storage, instead of being aimed at retrieval. Reversing this approach can, instead, lead to understanding data as transient, on-demand, and immediately available to end users within a certain context. This talk will discuss certain contemporary concepts that are expanding the notion of data storage devices and, instead, are moving to loosely connected data retrieval devices, or in some cases, data generation devices. We will examine this shift in approach and what it means for designing and deploying new types of technologies that can be more flexible and provide improved business value for clients in the fast-paced evolving world of Artificial Intelligence.

Data that is increasingly distributed across on-premises and multiple cloud platforms offers both opportunities and challenges for insights-driven business decision making. This is true for any industry and any organization, small or large. While modern data architectures such as data fabric or data mesh offer innovative solutions to extract maximum value from organizational data, in many instances physical replication or consolidation of data makes those solutions ineffective. In this session Paul Moxon, SVP of Data Architecture and Chief Evangelist at Denodo will present a number of customer examples illustrating how organizations have successfully implemented a logical data architecture.

Modern data and analytics landscape is becoming more and more complex by the day, as data driven decision making becomes ubiquitous for every functional area within every imaginable organization. While being promising, cloud data warehouses and data lakes are falling short of solving the complex data management problem and adding to security and governance complexity. Even modern architectures like data fabric and data mesh cannot solve the problem if they are not thought through a logical first strategy.

Join this panel, where Rex Washburn from CDW, Jacob Lynn from Textron and Inessa Gerber from Denodo will discuss:

• What role data fabric and data mesh play in modern data ecosystem
• What is a logical first strategy and its importance in modern data architectures
• How organizations can be future ready by embracing a logical first strategy

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.

The current complexities of the data landscape, often hybrid in location and distributed in nature, have catapulted the Data Fabric to the forefront of the data management industry. However, as a broad and strategic initiative, it is not always clear how to start and how to evolve it, what are the critical pieces that require more attention, and how to measure its progress and value. In this panel, we will:

• Review the key concepts of this architecture
• Discuss with Denodo customers the successes and challenges of their implementations
• Highlights what to avoid an what to focus on first

In today’s turbulent economies, manufacturers and their supply chain partners know that to improve time-to-value, they need to accelerate the pace of operations and to make better, more informed decisions faster. That’s a challenge when petabytes of collected data may be trapped in disparate, siloed systems─ in the cloud, in a data center, or on an edge device. In this panel, subject matter experts will discuss how manufacturing and supply chain leaders can optimize "time", and deliver more customer value faster and at a lower cost.