When you hear data virtualization, do you think BI and analytics? If so, you’re misinformed and missing out on a whole set of possibilities and capabilities of this technology. It is probably also why you think data virtualization is of no use to you if you need to access your data through APIs.
This is why we’re back with another episode of Myth Busters!Watch on-demand
So you’re building a data lake to solve your big data challenges. A data lake will allow you to keep all of your raw, detailed data in a single, consolidated repository; therefore, your problem is solved. Or is it? Is it really that easy?
Data lakes have their use and purpose, and we’re not here to argue that. However, data lakes on their own are constrained by factors such as duplication of data and therefore higher costs, governance limitations, and the risk of becoming another data silo.Watch on-demand
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.Watch on-demand
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.Watch on-demand