Search
Friday 24 May 2019
  • :
  • :

Ensuring High-Quality Data for Analytics, AI and Machine Learning Technologies

Ensuring High-Quality Data for Analytics, AI and Machine Learning Technologies

At face value, the difference between good data and bad data appears to be simple. It’s either accurate or inaccurate. However, when you think about it, you will realize that the quality of your data depends on so much more than just accuracy. For example, if you only have half the relevant data, no matter how accurate the data is, you can’t say that you have high-quality data. Another example is that you can have data that is correct but not timely. The lack of timeliness can have a negative impact on the overall integrity and usefulness of the data.

You may be wondering how you can ensure the quality of your data. Here are a few tips that can follow to ensure all the data you collect is high-quality. Why should you be concerned?  With the advent of AI and Machine Learning, and the business decisions that you are trying to make from analytics reports, they all will benefit from the high-quality data that you can get.

What Is Data Integrity?

The word “integrity” creates images of sincerity, strength, and honesty. You can trust an individual who is known for having integrity. Also, every time you choose to sit on a chair, you trust the integrity of the structure. You should be able to trust your data’s integrity in the same way. The quality of your data has a major impact on the success of your business decisions. As a result, data quality is essential. It enables your business, your team, and you to make insightful and educated decisions.

Checking Data Quality

Determining the quality of data can be tricky. On one hand, it can seem straightforward. On the other hand, you need to consider many variables to make an accurate assessment of the quality of data. The first step in determining the quality of data should occur before you collect it. Good quality data will help your organization or business at its core. You should keep this goal in mind and avoid collecting data that simply makes sense from an IT or technological standpoint. You should also consider what you want your data to accomplish or what you want to use the data for to accomplish.

Getting a Grip on Data Collection

Onboarding data is often the first opportunity for bad data to creep into your reports. During the collection of data, you will encounter many logistics and operations challenges. All of these come with unique opportunities for duplicative information and inaccuracies.

 

The Challenges of Data Collection:

Gathering different data from more than one source may lead to some data contradicting or overlapping with each other. Mixing data from internal and external sources can lead to many problems including incomplete data.  After your collection is complete,  often the managing a substantial amount of data may have inherent challenges to creating complete and helpful reports, even if the reporting features appear to be simple, the data behind it can be very complex and needs to be handled so as it is helpful to your business needs.

Data collection can be very prone to mistakes. However, this doesn’t mean you have to suffer from the consequences of these mistakes. During the critical phase, it is essential that you have a good understanding of the data at the most basic level. Be sure not to grab pieces of information and automatically assume that they are accurate. Double check each piece of data and ensure that they are complete and accurate. Scrutinize all of your sources to identify information that is overlapping or duplicated and eliminate them.

 

Why is High-Quality Data Collection so Important? 

With the advent of AI and Machine Learning, and the business decisions that you are trying to make from analytics reports, they all will benefit from the high-quality data that you can get. Machine Learning and AI technology relies heavily on the data that is in the system.  The latest trends for business leaders is to pull out the data to understand their processes, if the data is not high-quality stemming from a complete picture of your business or process, it will not be helpful to make decisions about the future of your business.  

As you can see, there are many things that you can do to ensure your data collected is high-quality. For more information about how to ensure the quality of your data, don’t hesitate to contact us.




Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.