High-quality data using Spotless Data's machine learning filters is the fundamental pre-requisite for effective rather than misleading data analysis.
The concept sounds easy enough. Get all your data in one location, known as a data lake, buy some expensive data analysis software tool, run it through your data and hey presto you now have the data mining and business intelligence which will allow your company to stand out among its rivals.
In practice, if your data quality is so poor, so untrustworthy, that the big data analytics software fails to deliver, you probably shouldn't blame the software and start looking for an alternative. Instead, you should take a good look at the data you have and make sure that your dreamed of data lake is not, in fact, a mud pit. And because these untrustworthy and rogue data are a data management issue does not mean that the solution is that you should replace your CDO, or whoever is in charge of your data. This would likely not solve the problem either but instead waste six months, firing one person and then employing and training up a second, merely to discover that nothing has improved because the problem is the lack of data integrity in the data themselves.
A classic example of how this unfortunate situation might occur could be getting the location data of your potential customers wrong, resulting in a data-driven marketing campaign which targets the wrong people. The worst of it is that you don't know that the problem is caused by the untrustworthy data and so you fire your marketing team, only to discover, again six months down the line, that your new marketing team, working with the same poor quality data mud pit, have done no better than the original team. Meanwhile, your competitors, with their better quality data, are grabbing all the potential customers, and unless you act quickly will be impossible to remove from the top spot in your particular industry.
What is required is the data cleaning of your mud pit to turn it into the pristine data lake which it should have been at the beginning where all the data have undergone data validation and data integration before entering your data platforms. There are two ways of doing this. You can employ some data scientists, who will expect a salary of at least the equivalent of $100,000 a year and will then complain because they spend at least 60% of their working lives cleaning your data mud pit. As a result, they will be much harder to hang on to as they start to dream of working for another company with cleaner data so they can, for the same salary, do the types of things they imagined themselves doing when they trained to become data scientists.
Or you can choose to clean your data lake and have data quality that you and your team can trust to do what you want it to, by using Spotless Data's unique web-based API solution, based on machine learning filters. This will ensure that your data analysis software does what it is supposed to, giving you the much-needed business intelligence and other useful information your business requires and ensuring that your data-driven marketing campaign is a success.
To ensure the ongoing success of your data analysis, you can build Spotless into your data projects to guarantees their data quality in your workflow and indeed throughout their lifecycle. You can integrate Spotless API with all your systems using our rule-driven, proprietary, data cleaning algorithm. When your files are cleaned to a spotless quality, you will receive a notification that they are now ready for analysis and use. Given that poor quality data is costing businesses $611 billion each year in the US alone, Spotless Data focusses entirely on the creation of quality data through cleaning to allow your company to focus on the business values and the data analysis so essential for success in the competitive modern world.
Spotless can now offer offline processing of your data to ensure GDPR compliance. You can read our introduction to using our API to validate your data and then try out our service on your my filters page but, for this, you need to log in first. You can take advantage of our free offer of 500Mb of free data cleaning to see how much you like our service. If you haven't already done so, you can sign-up using your email address, Facebook, Google or GitHub accounts. You may also view our video on data cleaning an EPG file, which also explains how to use our API.
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If your data quality is an issue or you know that you have known sources of dirty data but your files are just too big, and the problems too numerous to be able to fix manually please do log in and try now