Why test your data? An exploration of the benefits of testing.
If you haven’t checked out our previous guide “What is testing? (A closer look at big data testing)“, head over, read it and come back. This article will deal with the second most important question when it comes to testing your data – why? In this piece, we will discuss the benefits of testing, navigating you through elements such as data quality, scalability, and data confidence.
Testing leads to increased data quality
Testing your data (i.e. performing tests to ensure that actual output matches expected output) allows you to ensure data quality. For this reason, the benefits that follow testing are closely related to the benefits of achieving high data quality. These benefits are extensive, and so we will not be discussing all of them. However, some of the most prominent reasons as to why you should be testing your data include:
This one sounds a lot more complicated than it is. Basically, with a strong testing infrastructure in place – it becomes simple to ensure that data is consistent throughout the entire organization. You’ll be able to answer yes to all of the following questions:
- Is data that should remain constant the same today as it was yesterday?
- Is data harmonious throughout your business intelligence solution?
- Is your business intelligence logic consistent and unchanged?
While this might be more crucial for larger organizations, it is still hugely beneficial regardless of size.
Currency encapsulates the notion of having data that is up-to-date. Has your business intelligence solution been reloaded recently? Is your most recent data available within your solution? Is your solution current? All of these questions can be answered through testing.
An additional benefit of testing comes in the form of reasonable data. For clarity’s sake, we use reasonableness synonymously with accuracy and validity in this instance. While you will have to establish your own definition for what is reasonable, accurate and valid, testing enables you to ensure that your business intelligence solution is adhering to said definition. For example, testing can ensure that all of the new sales data that was added to your solution today is within a certain range and that the total sales value is larger today than it was yesterday.
Testing makes it possible for organizations to scale up while still ensuring that the data remains trustworthy and reliable. Furthermore, through the use of automated testing, it also becomes possible to scale up without jeopardizing the quality of your data and without necessarily increasing manpower. To read more about this, visit our page Embrace Scalability.
Although there are many more benefits that can be reaped as a result of testing, the final one we are going to visit is that of reliability. Here, we are referring to the trust and confidence that follows knowing that your business intelligence solution is operating exactly the way you want it to. This trust, in turn, can lead to many other benefits – including better decision making and a more optimized business strategy.
Get started with testing
Do you want to learn more? Then request a personalized demo of our Data Quality Manager today by clicking below.