Logical Data Warehouse

Hybrid Logical Data Warehouse

Panel by Jacob Lynn, Data & Analytics Manager at Textron and Rex Washburn, Lead Architect & Head of Portfolio, Modern Data Platforms at CDW; and moderated by Inessa Gerber, Director of Product Management at Denodo.

In today’s world, management of data can be a major challenge. For many systems, including SAP, data in real-time and integrating it with other disparate sources has historically been difficult to accomplish. The traditional Data Warehouse approach can also be quite expensive to keep data fresh and control access to meet new and future data protection requirements. Denodo and Gateway Architect’s Meister Core™ offers a high-performance data virtualization solution, designed to fulfill those needs.

Agility is a key element of today’s marketplace, whether the need is to adjust product offerings or improve delivery of services. We seek clarity and strive for practical solutions to complex business challenges.Seven Verbs and Denodo have partnered to combine seasoned Data Professionals with the industry’s most advanced data virtualization platform to simplify data access in support of the most critical business needs.

In the last few years, Data Virtualization technology has experienced tremendous growth, emerging as a key component for enabling modern data architectures such as the logical data warehouse, data fabric, and data mesh.Gartner recently named it “a must-have data integration component” and estimated that it results in 45% cost savings in data integration, while Forrester has estimated 65% faster data delivery than ETL processes.However, there are still misconceptions in the market about data virtualization technology, how it can be leveraged, and the real benefits that it can provide.Catch...

Landsbankinn wanted to accelerate its key operational and BI reporting capabilities and provide real-time data for informed decision-making across all kinds of users in the organization. To streamline its data infrastructure and integrate more than 45 data sources, Landsbankinn implemented a logical data warehouse using the Denodo Platform.

Presented at Enterprise Architecture Virtual Summit (Australia)The current data landscape is fragmented, not just in location but also in terms of processing paradigms: data lakes, IoT architectures, NoSQL and graph data stores, SaaS applications, etc. are found coexisting with relational databases to fuel the needs of modern analytics, ML and AI. The physical consolidation of enterprise data into a central repository, although possible, is both expensive and time consuming.A logical data warehouse is a modern data architecture that allows organisations to leverage all of their data...

The current data landscape is fragmented, not just in location but also in terms of processing paradigms: data lakes, IoT architectures, NoSQL, and graph data stores, SaaS applications, etc. are found coexisting with relational databases to fuel the needs of modern analytics, ML, and AI. The physical consolidation of enterprise data into a central repository, although possible, is both expensive and time-consuming. A logical data warehouse is a modern data architecture that allows organizations to leverage all of their data irrespective of where the data is stored, what format it is stored in...

Presented at Data Architecture Online A/NZThe current data landscape is fragmented, not just in location but also in terms of processing paradigms: data lakes, IoT architectures, NoSQL and graph data stores, SaaS applications, etc. are found coexisting with relational databases to fuel the needs of modern analytics, ML and AI. The physical consolidation of enterprise data into a central repository, although possible, is both expensive and time consuming.A logical data warehouse is a modern data architecture that allows organisations to leverage all of their data irrespective of where the data...

What makes data scientists happy? Of course data. They want it fast and flexible, and they want to do it themselves. But most classic data warehouses (DW) and data lakes are not easy to deal with for agile data access. A more practical solution is the logical data warehouse (LDW), which has shown to be a more agile foundation for delivering and transforming data and makes it easy to quickly plug in new data sources.Attend this webinar to learn:How easily new data sources can be made available for analytics and data scienceHow your organization can successfully migrate to a flexible LDW...