Big Data And Little Mistakes

In the age of big data and everyone being told that data collection is the key a lot of us are stuck with a ton of tiny little mistakes that we are incorrectly doing that is destroying the effectiveness of our data. In this article we will discuss how data quality audit tools can correct this issue.

Your Data Is Only As Good As Its Quality

Everyone is collecting data and it has become almost cliche to use the term big data or to suggest that data driven XYZ is the present and the future and anyone who doesn’t get this will be left behind. We have all gotten those emails, we’ve watched those commercials, we’ve seen those blogs about that and probably 101 Ted Talks about it. The truth about data, be it big or small that it is only as good as its quality. Junk data will give you junk results. So you need to do much more than collect data— you need to make use of it, clean it, parse, make sure that it is accurate and make sure that you are using it in the right way. Having things like best data quality tools, data quality checklist and data quality manager will definitely help.

Automating Data Quality

Most of us are not data experts and our expertise is in another area beside manipulating data. Most of us just use data to call customers and to shape our sales and marketing efforts. We simply need good data to make sense of things and to help us at our core duty, making more money. This is why we need a way to automate the process of data collection, data quality check and data allocation.

Auditing Your Data For Efficiency And Optimization

How good is your data and are you getting the most out of it? This is a very troubling question for people who are not washing their data and checking it for quality and accuracy. These same people do not have an efficient system in place to sanitize, correct, eliminate and optimize their data. It is our suggestion that anyone who deals with large and small amounts of data utilize some sort of data quality audit tool to do this for them. Once your perimeters are set, it is pretty much a set and forget one button process.

Data Quality Audit Tool – In Conclusion

How does one wrap up an article like this one? I think that the best approach is to summarize what we have covered. The first thing we covered is a topic that we routinely go over and that is in the world of big data, the most important things are the quality of your data and how you utilize it. Everyone is collecting data but everyone is not getting the most out of it. A lot of us are collecting junk data, we are incorrectly storing it, it is full of errors and it is not helping us improve our business. Data quality audit tools are all about making sense of the data, making sure that it is accurate and highlighting issues with data. Everyone who uses data in their business should be running this form of quality control on their data.

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