How to avoid errors in data analysis?

Using information without defined objectives and not integrating it across the entire company are part of the mistakes that organizations can make when analyzing large volumes of data.

Thursday, March 21, 2019

Although there are still many companies that have not begun to analyze the information they accumulate in their operation, there is a risk that the efforts they make in the future will not achieve the expected results if the mistakes that some organizations tend to make in the process are not avoided.

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Some of the most common errors include not clearly defining objectives and not knowing what to look for in the data sea, as well as not implementing a special system for information management.

Another error occurs when the different databases held in the company are not integrated, as information that could be used for the global analysis of the information is excluded. The use of imprecise, outdated, repeated or irrelevant data also damages the decision-making processes.

Also see "The Risks of Mishandling Big Data"

Not having the data needed in real-time is another of the most common problems in organizations, because this situation can result in decisions being made at the wrong time.

"... Carlos Vargas of Cisco warns that a common business error is to create isolated business intelligence or data analytics initiatives or projects, rather than programs that reach the entire organization." reviews: "... Juan David Rothe, CEO of Grupo CESA, indicated that companies must distinguish between service or software providers and integrators, which can provide end-to-end solutions with different brands. The gap in agility must be overcome to acquire new technologies".

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