Data Lake

Download the document to see the full case study and how Denodo data virtualization technology helped this healthcare company.

Data lakes have been both praised and loathed. They can be incredibly useful to an organization, but it can also be the source of major headaches. Its ease to scale storage with minimal cost has opened the door to many new solutions, but also to a proliferation of runaway objects that have coined the term data swamp. However, the addition of an MPP engine, based on Presto, to Denodo’s logical layer can change the way you think about the role of the data lake in your overall data strategy.ATTEND & LEARN:The new MPP capabilities that Denodo includesHow to use them to your advantage to...

In this webinar, we will cut through the noise and focus on five key principles you must consider to modernize your data architecture and drive value for the business. Register now!

MPP integration within a Logical Data Fabric

There is much hype around new data management approaches, from Cloud Data Warehouses to Data Lakes, Data Fabrics, and more. In this webinar, we will cut through the noise and focus on five key principles you must consider to modernize your data architecture and drive value for the business.What You’ll Learn:Practical advice on modernizing your data architectureHow to quickly deliver value to the businessKey considerations to position yourself for future change

Partner Keynote by Eric Little, Industry Innovation Principal Director at Accenture.

Understanding the Differences Between Data Lake Engines, Data Virtualization, and Data Fabric

Data Lakes were identified as the best option for consolidating data in one location and supporting organisational reporting and analytics needs. However, physical data lake solutions are often constrained by factors such as duplication of data, governance limitations, and the risk of becoming another data silo. Data virtualization allows you to leave all of the source data in place, stored across myriad, heterogeneous systems, and establish a virtual, “logical data lake” for accessing all of your enterprise data.During this webinar we will discuss how a logical approach to data integration...

With the appearance of cloud object storage services like AWS S3 or Azure ADLS, the data lake has seen an upturn in usage as some of the challenges of the original idea were addressed. However, companies across the globe still find it challenging to adopt data lakes into the corporate data ecosystem. While almost infinite in storage, data retrieval from these sources and integration of the data with the corporate ecosystem is still an arduous task for data engineers. This leads to data lakes becoming either a silo or a secondary form of storage instead of feeding business processes and...

Traditional Data Management approaches that rely on collecting data within a centralized data store, such as a cloud data warehouse or data lake, are core building blocks for your data modernization efforts. However, you need more to address the diverse needs of today's businesses. Hybrid/Multi-cloud, SaaS, and data privacy laws are just a few examples of why data will remain distributed.In this session, Paul Moxon, SVP Data Architecture and Chief Evangelist with Denodo, will discuss why you need to complement these centralized solutions with a logical data management platform that...