Your company probably sends, receives and creates a significant amount of data on any given day. In many cases, that data is used to make marketing decisions, develop products or otherwise plan for the future. Therefore, it’s critical that data is reliable so that you’re able to make decisions based on what’s actually going on in the world today.
What Is Data Reliability?
Data reliability is the process of evaluating whether or not information is valid and complete. There are several variables that you’ll want to review when determining the reliability of your data. For example, you’ll need to know whether there is any duplicate information within a given dataset.
If there is, it will create an overrepresentation or otherwise skew the information. Ultimately, you won’t be able to make any decisions or draw any conclusions from it. You also wouldn’t want to highlight it as part of a case study or otherwise distribute it to other parties.
You also want to make sure that information is properly formatted and that it can be used in a number of different contexts. Corrupt datasets or information that you can’t use in a broad manner is often useless or can cause other issues if relied upon.
What to Know About Data Reliability Today
There are a number of reasons why you want to ensure data reliability across your organization. First, if you don’t have great data, you could run into regulatory issues. This is because federal regulations require companies in most fields to have robust data governance policies.
If you can’t ensure the reliability of your data, you can’t necessarily be sure that you have a quality data governance policy. Ultimately, your firm could face fines, lawsuits and other actions that can harm profit margins and have negative consequences for your brand.
Data reliability is also critical if you implement machine learning or use AI in any capacity. These tools rely on data to make decisions and to teach themselves the skills that matter to your business. Using faulty data means that your AI tools won’t work like you want or need them to.
Data Reliability Challenges
Many reliability challenges are caused by the way that companies create and store data. For instance, if your company keeps data siloed, it can be hard to use it across departments effectively.
You may also struggle to get good results from outdated data as it may not be relevant to your business or to what is actually happening in the world today. Finally, you’ll need to be cognizant of human errors such as putting in the wrong information, relying on inaccurate data or making other mistakes that can corrupt a dataset.
Ensuring data reliability should be one of the top priorities for your firm both now and into the future. Ideally, you’ll have a team that is responsible for ensuring data reliability standards are upheld as technology evolves and other changes occur. Doing so can help ensure the long-term stability and profitability of your brand.
