Data Landscape

In an increasingly distributed and complex data landscape, it is becoming increasingly difficult to govern and secure data effectively throughout the enterprise. Whether it be securing data across different repositories or monitoring access across different business units, the proliferation of data technologies and repositories across both on-premises and in the cloud is making the task unattainable. The challenge is only made greater by the ongoing pressure to offer self-service data access to business users.  Watch on-demand and learn:How to use a logical data fabric to build an enterprise-...

In an increasingly distributed and complex data landscape, it is becoming increasingly difficult to govern and secure data effectively throughout the enterprise. Whether it be securing data across different repositories or monitoring access across different business units, the proliferation of data technologies and repositories across both on-premises and in the cloud is making the task unattainable. The challenge is only made greater by the ongoing pressure to offer self-service data access to business users.  Tune in and learn:How to use a logical data fabric to build an enterprise-wide...

Organizations continue to collect mounds of data and it is spread over different locations and in different formats. The challenge is navigating the vastness and complexity of the modern data ecosystem to find the right data to suit your specific business purpose. Data is an important corporate asset and it needs to be leveraged but also protected.By adopting an alternate approach to data management and adapting a logical data architecture, data can be democratized while providing centralized control within a distributed data landscape. The web-based Data Catalog tool acts as a single access...

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...

Presented at DATAVERSITY Demo Day 2022We have all heard about corporate Self-Service initiatives, or maybe your company has even attempted to implement one. With the evolution of the data landscape we have become data driven, when we should be information driven because data without context lacks meaning. Data that has meaning is what drives valuable business insights. We need to deliver the right information to our consumers, while providing a guided and governed experience across a diverse consumer community.Watch on-demand this session to learn:What it takes to deploy a successful Self-...

Organizations continue to collect mounds of data and it is spread over different locations and in different formats. The challenge is navigating the vastness and complexity of the modern data ecosystem to find the right data to suit your specific business purpose. Data is an important corporate asset and it needs to be leveraged but also protected.By adopting an alternate approach to data management and adapting a logical data architecture, data can be democratized while providing centralized control within a distributed data landscape. The web-based Data Catalog tool a single access point...

Presented at Data Analytics for Enterprise (Australia)Today most organizations rely on data-driven insights to make critical operational and strategic decisions. But given the complexity and vastness of the modern enterprise data ecosystem, finding the right data set and extracting actionable insights is an extremely complicated and time-consuming process.That’s where data virtualization can be used to abstract that complexity and introduce simplicity. Data Virtualization is a modern data integration technique that uses a single unified semantic layer to give you visibility into all of your...