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
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.
There is a growing need for versatile, hybrid architectures that can combine the best of both data warehousing and big data analytics. The cloud is the perfect solution, because it makes it easier to build a robust data warehouse as a central “hub”, and then add other environments that can be
The reality is that AI is still heavily-reliant upon smart, willing and trained humans in order for AI to behave in a manner that we would expect. Humans are needed to scope the problems, identify relevant examples and verify the results. Without humans as a guide, current AI is no more capable
There is so much talk about data as a new natural resource. The amount of data organizations and citizens across the globe produce, is authored in many systems and consumed by various organizations and users in different formats. This begs the following questions: Who owns this data? And why it is
It is said that more data has been created in the past two years than in the entire preceding history of mankind. It would be interesting to find out how much of this data has been analyzed and put to good use. Analyzing and harnessing big data is undoubtedly the major challenge of the day for all
IoT is the next goldmine of data. Today, it’s still largely untapped information that is primarily used for operational monitoring. By combining that data with traditional “corporate” data, you can improve customer service through faster problem recognition and response, react more quickly to a