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Data Quality Blog

http://blog.naveego.com

Becoming a Data-Driven Organization

by on in Data Quality , Data Accuracy

Data is the “oil” for all digital transformation initiatives including big data analytics, AI, Machine Learning, and more. Many of these initiatives intend to relentlessly improve customers’ experience with your business. However, failure can occur when computing with inaccurate data resulting in lower ROI, costly overruns, decreased productivity, and loss of trust. IT executives, business managers, and knowledge workers all have a shared responsibility to implement the best processes and technology to eradicate bad data. The negative impact of data inaccuracy can be widespread throughout organizations.

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Avoid “Technology Indigestion” with Naveego

by on in Data Quality , Data Accuracy

Companies are now able to cut unnecessary infrastructure purchases by nearly 50%, by avoiding processing duplicate or incorrect data.

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Naveego Proof of Value without a shadow of a doubt

by on in Data Accuracy , News , Data Quality

In this day and age, with technology ever advancing, most corporate IT departments are constantly evaluating new products and services to accomplish common goals that we all share when it comes to information management, data quality, and master data management (MDM).

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How Data Quality Impacts Manufacturing 4.0

by on in Data Accuracy , Data Quality

How good is your data?

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How Best to Leverage Data Scientists’ Time

by on in Data Quality , Data Accuracy

Give data scientists clean data. Give them clean data to analyze, instead of having them spend top wage dollars on scrubbing and prepping data. Recent reports reveal that data scientists spend, on average, 80 percent of their time cleaning data rather than analyzing it. Not only is this preventing the highest use of wage dollars, but it is irritating and frustrating the scientists, who are walking out.

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Why Data Accuracy and Master Data Management Are Ready for the Cloud

by on in Data Quality , Data Accuracy

It’s time to take a fresh look at an old problem: “garbage in, garbage out.” Everyone knows that information is only as good as the data it was built upon, yet according to Harvard Business Review, only 3 percent of companies’ data meets basic quality standards. With data becoming the world’s most valuable resource, it raises the question, “How is this possible?” I believe the answer is that traditional approaches to data accuracy and master data management simply cannot keep up with the digital transformation that is happening all around us.

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COMPELLING ROI WITH NAVEEGO – 800 PERCENT!

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by on in Data Quality

Many companies have searched for decades for accurate data in order to be able to provide key information for making board-level decisions. Some of the areas for which accurate information is needed include where to launch new products and how to keep repeat customers and maintain or expand market presence. If the data is inaccurate, these decisions can, in many cases, make or break a company.

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Bringing Data Accuracy to Healthcare

by on in Data Quality , Data Accuracy

In the business of health care, patient appointments mean revenue. If there are no appointments, there is no revenue. If appointment-scheduling software goes amok and appointments are lost or are error-ridden, revenue is lost.

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The Immediate Benefits of a Data Quality Solution

by on in Data Quality , Insider

If you’re relatively new to the concept of utilizing a data quality tool to improve the veracity, timeliness, and structure of your data, then there are some benefits to this investment that you may have not considered. As a business leader, having more accurate metrics on which to run your business sounds great, but how does this change your business in such a way to justify the investment? Here are some simple, immediate, and overarching benefits to consider before you even get into the numbers themselves.

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Need Your Business Data in One Place? Meet Naveego SYNC

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by on in Data Quality

Data’s ubiquitous nature in modern business has only increased in volume over the last five years. Coupled with the emergence of Cloud storage, this means companies are dealing with not only exponentially more date, but also with the fact it’s being stored in an increasing number of places. Across a company, data is captured, accumulated, and stored across innumerable applications, databases, and repositories. How, then, do data professionals generate the required metrics for higher ups to make informed businesses decisions if the company’s data is scattered across a number of silos?

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