Data quality requires a certain level of sophistication within a company to even understand that it’s a problem. – Colleen Graham
A different set of skills and tools are often used to improve data quality after it has been measured. At the strategic level, a good understanding of corporate culture, architecture, technology and other factors is important, however, a number of essential technical skills are also required when dealing with the data itself.
These include analysis, standardization, record linking or matching, data cleansing, data profiling, and data auditing or monitoring. These skills are often used extensively when undertaking projects such as data migrations where improvements in data quality must be achieved in tight time scales.
Data quality dimensions are often used by experts to generically group different types of tests that typically encompass different project requirements. Although there is some disagreement about the number of dimensions and the terms used for these, in the end they are necessary for making decisions and planning strategies and operations.
In the revolutionary era of digital transformation of communications and technology, data quality is vital. IT, data scientists, and engineers are becoming increasingly important. This is a result of the fact that more and more information is being produced, which requires the development of better systems to manage and make use of it. All this has a great effect on the effectiveness of business management. There are many reasons why it is important to use data as a resource. The first of these is that it allows us to create and implement more successful tactics to achieve our goals. Naturally, these tactics require investments in hardware and software or qualified personnel.
“Datos Maestros” is spanish for Master Data and thats all we know. With over 40 years of combined experience, accross 40 countries and more than 400 system integrations under our belt, we have seen the good the bad and the ugly. It’s safe to say we know a thing or two about data quality.
Why pay more for less, our unicorn business model allows a one man band and small to medium companies pay on the go, with credits or our pay per match check out options. For the the big dogs we don’t sacrifice quality for quantity and can count on the best bang for your buck with guaranteed lowest price without loosing our Fortune 500 memory.
Getting clean is the first step in data cleansing process the next challenge is staying clean. With our business automation integration reap the following benefits:
We integrate world class data quality with your preexisting tools and workflow for your team to have easy to access data that is processable and that yields real measurable results.