Tips for avoiding nulls & errors using Tableau

Tableau Software requires spotless data quality

High quality data can transform Tableau data visualisation.

Tableau, the data visualization software, is a way of illustrates data that is particularly useful when dealing with data which changes over time. It has a great mapping functionality, with a number of geographic identifiers built into their software, such as country, region and sometimes postcode. However, when using Tableau in order to plot various physical addresses, which have been geocoded into longitude and latitude coordinates, this functionality is tempered by the large number of nulls or errors that many users often get when they actually use the software, indicating a lack of data integrity.

Data from multiple sources

This is particularly noticeable if your company needs to enter data from multiple sources into your database, to make transactions, or for any other purpose. It may well be that when you use the Tableau Software in this way it produces mismatched data fields, which can then seriously impede your accurate reporting and affect the ability of the software to illustrate your data. As a response to this problem, Spotless Data has created a number of solutionss that will fix the errors or nulls problem and transform these geocoding errors in your data into data quality that illustrates the actual locations of cities, countries and states by ensuring the data validation of all your data. Using our unique web-based data quality API solution also makes it easy to ensure their quality through data cleaning the data you receive from multiple sources before it enters your database. The data can then be plotted successfully in maps and graphs in order to illustrate them, both for your clients and for your management reporting.

Postcodes

As a United States company Tableau has received particular criticism for its inability to deal with postcodes from outside that country, and this can result in maps and graphs containing a lot of different plotted points or symbols, but which fail to create the coloured polygon (filled) shades which the software is designed to create, and which are what make illustrating and reporting so easy using Tableau Software.

Correcting or updating of badly formatted postal addresses is of itself a more universal problem and is something that we specialise in. Your best solution in all these cases is to pass your data sources through Spotless in order to thoroughly scrub them before then sending them on to Tableau. We can guarantee that you will get far fewer nulls and errors by doing so, and will thus be able to create the maps and graphs which your business requires in order to stand out among its competitors, attract customers and ensure accurate management reporting.

Please do sign up for our service using your email address, Facebook, Google or GitHub accounts. Here is a quick link to our FAQ. You can also check out our range of subscription packages and pricing, and try it out with 500Mb of free data cleansing. You can also view our videos on data cleaning an EPG file and data cleaning a genre column which explain how to use our API. If you would like to contact us you can speak to one of our team by pressing on the white square icon with a smile within a blue circle, which you can find in the bottom right-hand corner of any of the web pages on our site.

Spotless Data, the one-stop data quality API solution!

 

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