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.

You maybe interested in "Big Data to create new business opportunities"

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 The use of imprecise, outdated, repeated or irrelevant data also damages the decision-making processes.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."

Elfinancierocr.com 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".

More on this topic

Big Data and Business Growth

April 2019

Having the required resources to manage the data needed to make decisions is crucial to the success of businesses in today's environment.

Today's data savvy organizations, those with a top-down approach to decision making, do a better job of extracting value from the data, explains a Coursera publication.

The Risks of Mishandling Big Data

February 2017

When using data to make business decisions, companies must understand that having a lot of information is not the same as having real, verified and high quality information.

EDITORIAL 

Every day more and more companies are using new methods of analyzing information to make their business decisions, but on the path towards change it is all too easy to make the mistake of believing that having a lot of information,real, is the same as having real, verified and high quality information.

How to Compete in a data-driven World

January 2017

The success of companies increasingly depends on their ability to integrate data analysis both for strategic and operational decisions.

Both the availability of data and the ability of technology to use it for analysis, have increased exponentially in recent years. More sophisticated algorithms have been developed and computational and storage power has steadily improved. The convergence of these trends is fueling rapid technological advances, aiding better business management.

Business Information "Convenient for Me"

November 2016

The failure of polls on the presidential election in the US shows that in order to get the right information, data must be collected and analyzed with scientific rigor, free from any bias caused by the personal interest of pollsters and analysts.

EDITORIAL

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