There is a lot of demand growing for data intelligence being embedded inside processes, applications, solutions, Cloud services and devices. Obviously we've been talking about embedded for quite some time, forever really, but we're seeing these things changing how demand is looking.
There is increased demand for data intensive applications. Setting aside just those kind of movements towards embedding intelligence in things, just to have from a user perspective that we get more users interact with more data, and they're more dependent on data insights.
Because certainly as we begin to democratize business intelligence and analytics, and have more users involved in it, particularly non-technical users, managers and personnel, including frontline personnel who are not versed in how to access data and so forth and don't really have the time to do all the training and develop the skills to do it.
This is becoming an issue in organizations. It's stressing the platforms. It's a stress on traditional systems that demand more of a standalone environment that requires a lot of training and expertise in using data. Then as I mentioned, I think in the earlier slides, speed is a competitive advantage. Organizations want to be able to close the gap between the creation of the data and its availability for analysis and visualization.
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This is becoming business critical and particularly when you think of the kinds of users in terms of in operations, working with customers and working with web applications that are depending on data insights, and they're in a competitive environment. It's very important for them to receive that data or receive notice of data events much sooner than many traditional architectures can support, and that's an issue.
By the time users can view the data in dashboards and be able to analyze the data, it's often too late to really have the maximum effect, and that's what we're really talking about here is maximizing the power with embedded analytics. Some of the top drivers that we see, and I think when we think about the types of users that are becoming part of the whole spectrum of users and organizations that are working with data and working with analytics, immediately it goes to the top as operational.
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Users in different operations throughout organizations, different business functions, subsidiaries around the globe that are now being asked to be more data-driven in their decision making and be able to use data effectively to determine how they can make business processes more efficient. How, for example, customer interactions maybe, could be more effective, business partner interactions, and so 74% of those that are researchers make that the top priority for their BI and analytics investment.
Again, there is a great opportunity, as I'll be talking about, I'm probably getting ahead of myself, for embedded analytics in operations to improve operational efficiency and effectiveness. Again, tightening it is much better than the kind of looser arrangement that most organizations are working with. Performance Management KPIs metrics, that's often a way that organizations try to communicate objectives to operational users or other kinds of users around the organization using key performance indicators and other types of metrics to understand business performance where they are now if they are where they expect it to be.
What they could do to be better? This is key information for improving operational efficiency and effectiveness. Again, in many organizations, this is supported by a standalone system where they have to move away from their business application environment and have to deal with the BI platform separately or some sort of a dashboard system separately, or if dashboards are embedded there, they don't carry all the KPIs or other metrics that they're looking for.
We see here that this is a top priority as well, in 50% of organizations. This is very close is reducing cost and improving profitability, which is often the key focus in many kinds of parts of organizations in operations, and really throughout organizations everyone's asked to do both those things, reduce costs and improve profitability. The better information they get, the more timely information, decision makers can get there the better it's going to be.