Self Service Analytics

Presented at Chief Data Officer September 2021 (A/NZ)Watch on-demand this session to understand how data virtualization can be used to:Seamlessly implement the concept of 'Data Marketplace'Enable all business users to derive value from self-service analytics toolsApply consistent security and governance policies across the enterprise data architecture

The case study is about a global investments bank dedicated to helping clients manage and service their financial assets throughout the investment lifecycle. The bank itself is composed of several lines of business such as capital markets, financing and liquidity, securities services, treasury services, investment management, wealth management, and data and analytics. As of March 31, 2021, the bank had more than $40 trillion in assets under administration, and more than $2 trillion in assets under management.To promote a data-driven culture and make it effortless for business users to...

Presented at Chief Data Officer July 2021 (A/NZ)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. Data Virtualization is a modern data integration technique in which a single semantic layer can be built containing semantic definitions of all of the underlying sources.Watch on-demand this session to understand how data virtualization:Helps organisations...

Companies with corporate data lakes also need a strategy for how to best integrate them with their overall data fabric. To take full advantage of a data lake, data architects must determine what data belongs in the Lake vs. other sources, how end users are going to find and connect to the data they need as well as the best way to leverage the processing power of the data lake. This webinar will provide you with a deep dive look at how the Denodo Platform for data virtualization enables companies to maximize their investment in their corporate data lake.Watch on-demand this webinar to learn:...

Presented at FIMA Connect Virtual EventSelf-service is often touted as the holy grail of analytics - allowing users to discover and access data without having to ask IT to create them a data mart or otherwise extract and export the data. The challenge is not just to provide access to the data - there are tools that do this already - but to do this in a managed and governed way so that you can trust the output of the analysis. Without this, we end up with the fabled 'Tower of Babel' with no standards and no governance.

In today’s digital economy, customers are all-powerful. They have the ability to search for and find products and services, find reviews and ratings, find out about alternative products and services via search and social networks, ask questions of others about products and services, and find comparison sites. All of this can be done from a mobile device while on the move and with so many options available to them. They can switch to a competitor at the touch of a mobile phone screen or the click of a mouse.In this kind of economy, customer loyalty is cheap and so it is essential to know more...

Reporting tools, while important and necessary, focus on the visualization of data and it’s presentation to the business user. Data virtualization is a governed data access layer designed to connect to and provide transparency of all enterprise data. Yet the myth suggests that these technologies are interchangeable. So we’re going to take it on!Watch this webinar as we compare and contrast BI tools and data virtualization to draw a final conclusion.

Denodo customer presentation by Nicolas Brisoux, Director of Product Management at Tableau Software.

Realizing the Promise of Self-Service AnalyticsSelf-service analytics promises to liberate business users to perform analytics without the assistance of IT, and this in turn promises to free IT to focus on enhancing the infrastructure. Download this solution brief to learn more about the following:How fragmented data is seamlessly unified.How a high-maintenance data integrations are replaced by a single, low-maintenance data virtualization layer.How data delays are virtually eliminated, as data can be accessed in real time.How data integrity is preserved.How data lineage is fully traceable....