Search Results

In the past, data governance was looked upon as a thankless task, more of a hindrance to business than a facilitator. However, because of today's data privacy regulations, data governance is increasingly seen as a critical function across most organizations.

The onset of the pandemic witnessed acceleration in digital transformation of major sectors, especially financial services. Financial establishments are redefining the digital customer journey by understanding the customers’ changing priorities and preferences, providing innovative and personalized offerings with an integrated digital framework.

Engie is a major energy generation and distribution company in Mexico. The rise of digital technologies and the explosion of data from customers and business processes pushed Engie towards building the capabilities to fully exploit the potential of these technologies and that of its data assets. DA VINCI Project (Data Virtualization and Capability Integration) was designed to further Engie’s data-driven strategy, which has already resulted in the enablement of various new data-driven use cases. Through the prism of DA VINCI Project, Luis Guadarrama will showcase how Engie successfully implemented its various data-driven initiatives and the role data virtualization played in that.

When virtualization became mainstream in the early 2000’s we realized that we could decouple applications from the physical limitations of the underlying infrastructure. This led to a revolution in how we design and operate applications in the modern enterprise. Fast-forward to 2021 and virtualization is now being applied to data in much the same way.

Presented at Chief Data Officer September 2021 (A/NZ)Watch on-demand this session to understand how data virtualization can be used to:

What started to evolve as the most agile and real-time enterprise data fabric, data virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics.

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.

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.

In the recent Building the Unified Data Warehouse and Data Lake report by leading industry analysts TDWI, we have discovered 64% of organizations stated the objective for a unified Data Warehouse and Data Lakes is to get more business value and 84% of organizations polled felt that a unified approach to Data Warehouses and Data Lakes was either extremely or moderately important.

In the first webinar of the series, we bust the 'performance' myth.“What about performance?” is usually the first question that we get when talking to people about data virtualization. After all, the data virtualization layer sits between you and your data, so how does this affect the performance of your queries? Sometimes the myth is perpetuated by people with alternative solutions… the ‘Put all your data in our Cloud and everything will be fine. Data virtualization? Nah, you don’t need that! It can't handle big queries anyway,’ type of thing.Watch this webinar to look at the basis of the 'performance' myth and examine whether there is any underlying truth to it.