Universal connectivity is fueling streams of event data from a variety of event sources. Increasingly, organizations are developing and deploying event driven applications to harness the growing volumes of event data. IBM Db2 EventStore offers a scalable integrated system for enterprises to ingest
In the connected world of today’s digital economy, apps, IoT devices, vehicles, appliances and servers are generating endless stream of event data. The stream of events describes what is happening over time and offers the opportunity to track and analyze things as they happen.
If you’re truly data-driven, how often do you make a critical decision based solely on information from one part of the company? At the organizational level, how valuable is data when decision makers have to rely on IT (not to mention a tangle of technical and bureaucratic red tape) just to access
A decade ago, governance was dictated and enacted by a select group of people. Today, while the principles of governance are largely owned by the same select group of people, everyone has a hand and shared responsibility in the enactment and fulfillment of governance.
No matter what site you search, it’s pretty clear that self service data is a top trend in the data market today. The knowledge and insight that we can obtain from data is truly a secret weapon. But the challenge is making the data available while keeping it trusted and governed.
In any successful modern organization, analytics is likely to play a central role in helping decision-makers design and execute effective business strategies. At IBM, as we work with clients across the globe, we’re seeing ever-increasing levels of maturity and confidence in data-driven business
Data, insights, cloud, agile, analytics. These are all terms that get thrown around a lot in technology these days. But the truth is that unless you can combine some or all of these concepts, the bottom line benefit to your business will likely not as great as you may expect.
Context-aware stream computing helps you become more responsive to emerging opportunities. By using innovative technologies to understand the context of data and analyze data in real time, you can put data to work.
For today’s data scientists and data engineers, the data lake is a concept that is both intriguing and often misunderstood. While there are many good resources about data lakes on ibm.com and other websites, there is also a lot of hype and spin. As a result, it can be difficult to get a clear
The Academy Awards provided a great example of the challenges of data integration. The business output of the data integration processes in the award ceremony is the announcement of a winner in a specific category.
Building a data lake is one of the stepping stones towards data monetization use cases and many other advance revenue generating and competitive edge use cases. What are the building blocks of a “cognitive trusted data lake” enabled by machine learning and data science?
Data is often the catalyst that drives business direction and growth. However, if data is cryptic and not understood, then how can such data contribute to such direction or growth? Just like in life, we learn from our past, as we gain direction and insight from previous events or activities to make