Hi, everyone. This is Tim Fritz from Quest Software. I'm a Database Technologist and Market Strategist a Quest. Today we're going to talk about data empowerment in a diverse data ecosystem.
So to start this conversation, let's talk about digital transformations. They're happening everywhere, probably no surprise to anyone on this call. But I wanted to just give you a feel for the breadth of the issues or transformations that we're seeing out there, and why we think data empowerment is so meaningful-- even those of us who work with databases every day. Right?
So you might be wondering, well, I manage MongoDB, I manage different flavors of databases. Why do I need to be concerned about something called data empowerment? OK. So anyway, data transformations include things like movement to cloud, application modernization, shifting things to the cloud, pandemic-driven changes, more people working from home means even more devices out there that can connect to your corporate data, and keeping that data private from all those new endpoints out there is critical. Compliance is not going away, certainly. Right? Data breaches-- there have been some very high profile examples of that lately within in the last few months, and continues to be a huge challenge for organizations to make sure that data breaches are not happening.
Data is proliferating around organizations. A vast majority of data has begun to accumulate in organizations, especially over the last few years. And it's growing exponentially in a lot of companies, and that's an issue-- just knowing where all that data is and what it's useful for things.
And then data democratization is really where we're heading as far as making sure that the data is useful for business decisions. The thing is, democratization-- one aspect of that is that so many of us now are being considered data analysts. We're being asked to create reports, go after different data sources, on the same reports visualize the data in certain ways. So the democratization of data raises many issues in organizations for how to make that happen safely. Make sure that decisions are being made soundly on data that is being used the correct way.
So all those things taken together are challenges that our customers are facing and that you are probably facing to some extent as well. And we think data empowerment is really the answer here as far as making sure that the challenges brought by these transformations are not keeping businesses from making use of a lot of data that is probably useful in organizations, and they may not even know it yet.
So in summary, we're seeing reinvention of businesses from the data perspective, or from data out. And so the data is really at the center of all this, and it's woven throughout all these transformations. All these parts of the businesses are touched by the transformations.
So few things that we've heard from our customers. I'm going to address Quest's platform for data empowerment here. Right? So what we've heard from customers-- first of all, people who work in data governance actually want visibility into more context around the data that they're governing, including the systems, the business processes, and the security and protection of the data, all those aspects of data. And building data literacy, making sure, again, that the data is useful, understood by everyone-- it's all comes down to data governance. It's all part of that.
Now, another pillar of the state empowerment framework is data protection. And our definition of data protection is broader than a lot of people's definitions of data protection, but we think our definition is where the market is heading and where more and more people's heads are thinking about data protection in a broader sense. Right? It's not just backup and recovery, although that's still a critical part of it-- making sure that the data is stored somewhere safe and it's accessible. But audit and compliance fall into this category too.
And access management-- making sure that only people who need access get access, and keep malicious use of data at a minimum. Security endpoint management, like I mentioned before-- making sure that you know all the devices that can access your data and make sure that, again, only people who should be accessing your data are.
All right. And then data operations is the first column here, and that's what we're going to spend the majority of this 30 minutes on. But first, let's dive into a few details about data protection and data governance.
So data protection is all the things listed on the screen. Like I said, our definition is broader than some people's definition of data protection. And here are some specifics. Proactive and defensive methodologies-- so you need to be defensive, as far as protecting your data, but you also need to have offensive tactics in place to identify and protect against those endpoints out there that might be able to access your data. Visibility, securing assets, and encrypting-- OK, all those things are data protection.
And here are some of the aspects of it that kind of translate to what your business is probably doing with data right now. And people around the organization are going to really reap the benefits of solid data protection policies in the company-- policies, practices, hopefully tools that can help with all that. It's going to benefit various areas and businesses, as this slide depicts right here.
All right. Now data governance-- here is kind of how we define data governance. What are the sorts of things that have to get done in data governance? Well, identifying technical assets. Knowing what data exists. Where it is. Curating the data assets and with business and quality context-- so that's important. That means documenting things a lot, and I'll talk more about that as we go. That's a key aspect to it. Right? Documenting it so everyone knows the truth about the data, where it came from,
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