Data needs to flow to be of any use. That flow needs to pervade the often complex infrastructures through which data is processed and delivered and mirror the rhythm of activities within which the data is being originated.
A Turing test may mimic human intelligence, but true intelligence is acquired through life experiences
Industrial processes fascinate me, not just in their automation, speed, and efficiency, but also in their ability to give precise shape to an otherwise unruly raw material.
Information flows through many channels as it rushes from myriad sources to the places where people apply it in real-world situations. Data’s diversity is a challenge that can best be met through implementation of the right tools for integration, capacity, and delivery of its precious payload of insight and guidance.
Does in-memory persistence remove technological barriers that prevent business outcomes at any latency?
Smart thoughts come quite readily to the prepared mind. Finding insights inside big data is easy if you’ve prepared, organized, and tuned it all for speedy access.
Nature doesn’t reveal its deepest secrets to the casual observer. The edifice of scientific knowledge has risen because of the diligence and ingenuity of many smart people over many centuries. But it’s never perfectly secure in its foundations
Find out how data scientists can use geospatial analytics to help mitigate risks from natural disasters
The best data scientists are critical thinkers par excellence. Acquiring skills in quantitative analysis and programming is not enough, and even a strong background in some domain specialty doesn’t guarantee a data scientist’s effectiveness.
Enterprise data is useless if it doesn’t flow where it’s needed. And it’s just a waste of precious resources if it takes an army of technicians and analysts to put it in the right shape and context.
Holistic data analytics environments help organizations to access, manage, and leverage their information assets comprehensively.
When you’re betting the business on your infrastructure, stringent requirements come into play. Determining whether you have an enterprise-grade big data platform requires many interlocking considerations. Compliance, extensibility, functionality, performance, reliability, and security are among the many criteria you need to build into both the infrastructure and your operating procedures. Lacking comprehensive controls and assurances in all these areas exposes the organization and all its assets to excessive risk. In IBM Data magazine the first week of 2015, we have …