A Quote by Jim Frey

EMA research evidences strong and growing interest in leveraging log data across multiple infrastructure planning and operations management use cases. But to fully realize the potential complementary value of unstructured log data, it must be aligned and integrated with structured management data, and manual analysis must be replaced with automated approaches. By combining the RapidEngines capabilities with its existing solution, SevOne will be the first to truly integrate log data into an enterprise-class, carrier-grade performance management system.
With customers' permission, fintech firms have increasingly turned to data aggregators to 'screen scrape' information from financial accounts. In such cases, data aggregators collect and store online banking logins and passwords provided by the bank's customers and use them to log directly into the customer's banking account.
One of the myths about the Internet of Things is that companies have all the data they need, but their real challenge is making sense of it. In reality, the cost of collecting some kinds of data remains too high, the quality of the data isn't always good enough, and it remains difficult to integrate multiple data sources.
Security incidents have gone up 5-10 times during the pandemic, so there is an increased need for security operations risk management, identity and access management, data privacy and compliance.
Management must provide employees with tools that will enable them to do their jobs better, and with encouragement to use these tools. In particular, they must collect data.
There's a tendency in graphics to allow the trimming of certain parts. But I think that if you're open about your process, your methodology, such as introducing thresholds, introducing filters, techniques people use in research and data management, it's legitimate. It's legitimate to say, "We're only going to show data above this level, or between levels."
Today, I think a CFO needs to be more of an operating CFO: someone who's using the financial data and the data of the company to help drive strategy, the allocation of capital, and the management of risks.
There will be many cases when researchers will need to look at data to come closer to a cure, in maybe five years, 10 years, 15 years. We can help make that data analysis easier. We can't let this wait. Dementia has potential to cripple our economy.
There is the GIS world that is largely managing authoritative data sources, supporting geocentric workflows like fixing roads, making cities more livable through better planning, environmental management, forest management, drilling in the right location for oil, managing assets and utilities.
The biggest mistake is an over-reliance on data. Managers will say if there are no data they can take no action. However, data only exist about the past. By the time data become conclusive, it is too late to take actions based on those conclusions.
One [Big Data] challenge is how we can understand and use big data when it comes in an unstructured format.
Philips is uniquely positioned to help reshape and optimize population health management by leveraging big data and delivering care across the health continuum, from healthy living and prevention to diagnosis, minimally invasive treatment, recovery, and home care.
Scientific data are not taken for museum purposes; they are taken as a basis for doing something. If nothing is to be done with the data, then there is no use in collecting any. The ultimate purpose of taking data is to provide a basis for action or a recommendation for action. The step intermediate between the collection of data and the action is prediction.
Video is originally a de-corporation, a disqualification of the sensorial organs which are replaced by machines. The eye and the hand are replaced by the data glove, the body is replaced by a data suit, sex is replaced by cybersex. All the qualities of the body are transferred to the machine.
A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.
We all say data is the next white oil. [Owning the oil field is not as important as owning the refinery because what will make the big money is in refining the oil. Same goes with data, and making sure you extract the real value out of the data.]
Data!data!data!" he cried impatiently. "I can't make bricks without clay.
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