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Data Quality Blog

http://blog.naveego.com

Wes Sovis

Wes Sovis

Wes is a technology professional who specializes in marketing and business development.


Data Quality: The Link Between Marketing and Sales

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For as long as marketing and sales departments have existed, they seemingly have been at odds. Sales wants more leads from the marketing team, while the marketing team accuse the sales people of rarely following up on the leads they pass along. After spending ample time in both marketing and sales roles, I think I’ve discovered the cause for this common discord, and it’s likely not what you think.

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Our Four Steps to Data Quality Confidence

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A Hollistic Approach to Data Quality For all the algorithms and tech jargon associated with the intricate details of a data quality solution, the process itself is a relatively straightforward endeavour. In fact, the more simple the DQ solution is, the more accessible it is for users and the less time-consuming it is to use. Simplicity, ease of use, and time-management were all critical components for us when designing our data quality solution, Naveego DQS. We believe our solution’s four-step approach to addressing data quality is second-to-none within the industry. In fact, we don’t know of a solution that addresses the crucial aspects of data quality like Naveego DQS does. To help give you an idea of how our solution works, here’s an overview of how our solution works.

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When We Talk Data Quality, We Need to Talk About Waste

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When we discuss data quality, what we really need to be talking about is waste. The reality is that poor data generates an inordinate amount of physical and abstract waste in any organization, and it does this in a myriad of ways. It’s important to keep in mind the negative impact poor data has on your business, even if you haven’t thought of its impact in these general terms before. Here are a few ways to think about waste associated with data quality that you may have not considered.

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Data Quality Industry Report

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The latest Research and Markets report on the direction on the data quality market was recently released. The report suggests that the data quality tools market size will increase from $610 million in 2017 to $1.3 billion in 2022. The in-depth report tells us quite a bit about the projected growth of the industry, as well as some reasons for the explosion in data production on behalf of consumers and businesses.

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Who Would Benefit from a Data Quality Solution?

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Who is a Data Quality Solution For? On our blog, we often discuss the benefits of using a data quality solution to help businesses use better data to make smarter decisions to run their businesses. We use this example because it paints the clearest picture of the benefits of utilizing a data quality solution. But if we’re leading readers to believe that you have to be at the C-level in order to get the most out of our data quality solution, we’re very much leading you astray. The fact is that so many different roles within business could find immediate and profound positives from a data quality solution.

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Data as a Competitive Advantage in Business

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Data Quality and Decision Making Data quality is quickly becoming a high priority for many businesses in a variety of industries. But it’s important to realize that the objective of clean data isn’t just to tick a box at a quarterly meeting. The implications of having clean, reliable and accessible data reach far outside any conference room or goal list on a whiteboard. The reality is that your data, whether clean or otherwise, likely affects nearly every aspect of your business - from the C-level to the mailroom, and most especially your bottom line.

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Bad Data is a Problem for Everyone in Business

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Poor Data Quality? You’re Not Alone Checking out an article on TechWire, we found several statistics that perfectly support what we’ve seen within the data quality industry for ourselves. The basis of the article was really two-fold: first, that data quality is an inherent problem in every industry, and second, that these quality issues are extremely costly to organizations for a plethora of reasons. The numbers simply don’t lie. It is further proof that bad data is detrimental to most businesses and that addressing data quality can deliver immediate improvements in efficiencies, profitability, and offer a competitive advantage to businesses that adopt data quality protocols.

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Your Data is Valuable - Here's Proof

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Why Your Data Has Value Many blogs in the realm of data management, data quality, analytics, etc. go to painstaking lengths to get into the nitty gritty of managing, cleaning, and interpreting data. What a lot of these blogs miss is the bigger picture. By that I mean we need to take a step back to come to consensus that all of these metrics we’re measuring and manipulating are valuable to an organization.

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OPEC's Latest Move? Big Data

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OPEC Announces Oil and Gas Big Data Project With the oil and gas industry experiencing a period of turbulence not experienced in decades, the Organization of the Petroleum Exporting Countries (OPEC) have recently put a new emphasis on big data. This week, OPEC announced plans for the creation of of the Oil and Gas Big Data Project, an effort to use publically-available data sources related to the oil and gas industry to give market shareholders access to “comprehensive, well represented, user-friendly and transparent oil and gas-related information.”

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