Data Warehouses

The data landscape has become more complex with new use cases like IoT, Streaming and Edge analytics. To better manage enterprise data distributed across data lakes, data warehouses, and many other systems residing on-premises and in the cloud, enterprises are turning to various data management technologies like query accelerators, data virtualization, and data fabrics. Each address specific needs of an organization, but which is the right solution to help you meet your business objectives?Join Denodo for a webinar featuring guest speaker, Forrester VP and Principal Analyst, Noel Yuhanna, to...

The data landscape has become more complex with new use cases like IoT, Streaming and Edge analytics. To better manage enterprise data distributed across data lakes, data warehouses, and many other systems residing on-premises and in the cloud, enterprises are turning to various data management technologies like query accelerators, data virtualization, and data fabrics. Each address specific needs of an organization, but which is the right solution to help you meet your business objectives?Join Denodo for a webinar featuring guest speaker, Forrester VP and Principal Analyst, Noel Yuhanna, to...

The data landscape has become more complex with new use cases like IoT, Streaming and Edge analytics. To better manage enterprise data distributed across data lakes, data warehouses, and many other systems residing on-premises and in the cloud, enterprises are turning to various data management technologies like query accelerators, data virtualization, and data fabrics. Each address specific needs of an organization, but which is the right solution to help you meet your business objectives?Join Denodo for a webinar featuring guest speaker, Forrester VP and Principal Analyst, Noel Yuhanna, to...

The data landscape has become more complex with new use cases like IoT, Streaming and Edge analytics. To better manage enterprise data distributed across data lakes, data warehouses, and many other systems residing on-premises and in the cloud, enterprises are turning to various data management technologies like query accelerators, data virtualization, and data fabrics. Each address specific needs of an organization, but which is the right solution to help you meet your business objectives?Join Denodo for a webinar featuring guest speaker, Forrester VP and Principal Analyst, Noel Yuhanna, to...

Data architecture is more relevant than ever today, because so many user organizations are migrating data to the cloud, modernizing analytics and data warehouses, deploying data lakes and lakehouses, and adopting new practices for data virtualization, sharing, monetization, and marketplaces.These and other data-driven use cases demand massive volumes of data in every structure imaginable, together with a wide range of processing capabilities. A well-designed, cloud-based data architecture provides a home for such highly diverse data and the numerous use cases it enables.This Tactical...

The cloud is no longer the future; the cloud is now. Companies continue to shift their workloads and data to the cloud to leverage the speed, agility, and efficient scalability the cloud offers. As a result, there is increasing attention given to cloud-based data warehouses, data lakes, and lake houses as a way for organizations to simplify managing their ever-increasing volumes of data. However, many find that these new technologies only complicate the data management process.Join Kevin Bohan, Director of Product Marketing at Denodo as he explores the challenges faced when adopting cloud...

In almost every organization, both public or private, data is distributed in an evolving IT infrastructure. That is mainly why organizations want their data strategies to evolve, migrating to the cloud, or unifying data warehouses and data lakes, without affecting business.Denodo’s data integration and data management platform, leveraging data virtualization technology, offers a new logical data delivery approach, enabling organizations to connect to various sources, integrate, manage and secure data quickly and efficiently.In order to cover the entire scope of the data value chain, combined...

Agencies that have had legacy data warehouse, data marts, and analytics reporting technologies for the last 10 plus years are looking to modernize them, especially to a cloud equivalent. For e.g., many are migrating from on-premises data warehouses like Teradata to its cloud data warehouses equivalents like Snowflake. However, such transition is sure to impact internal and external data consumers in many ways: applications not being available due to downtime during the migration, training on the new analytics technologies, and new ways to search, find, and use the data in the new system. Such...

According to a recent Forrester survey, while 85% of organizations want to improve their use of data insights in their decision-making, 91% of the respondents report that they are not able to improve upon their data-driven decision making. The problem - organizations often turn to the data lakes, data lake houses, cloud data warehouses, etc. as their monolithic data repository, for all of their data and analytics needs. But the hard reality is that data is and will be spread across multiple repositories that extend across cloud and regional boundaries.Attend this webinar to gain key insights...

Presented at DAMA VancouverFor more than three decades, business users have demanded a unified view of organizational data. Technologists have addressed this need, over time, first with databases, then with data warehouses, and more recently with data lakes. However, these technologies have become data silos housing different types of data. That’s where technologies like data virtualization played a critical role to provide a unified view of the enterprise information, without replicating data and delivering faster speed-to-market for products and services. As businesses go increasingly...