Data is being created at a blistering pace.
There will be more data generated over the next three years than all the data generated from the past 30 years, per a recent report from International Data Corporation (IDC). The same report projects over three times the amount of data will be created in the next five years than in the past five.
The ongoing challenge organizations face is ensuring all that data remains accurate, clean and up to date. According to Gartner, organizations estimate that poor data quality costs them an average of $12.9 million a year, while a 2016 IBM study revealed the U.S. economy loses $3.1 trillion annually because of inadequate data quality.
If your company wants to get the most out of the data it creates now and in the future, you must place a greater emphasis on preserving optimal data quality. Here are two components that organizations need to maintain data integrity.
1. Strong lifecycle policies
Is your data valid? Does that data still need to be maintained? If not, are you only keeping it for as long as you need it?
Knowing the answers to these questions – among others – is imperative for data integrity, and without them, there’s a strong likelihood that your data will be compromised. You find these answers in your lifecycle policies.
These will vary from organization to organization based on personal needs, but all companies should establish strong lifecycle policies. For example, you may have a backup policy in place, but how long does your organization actually need those backups? This is something you should determine from the start.
Your lifecycle policies should be fluid, adaptable and agile enough to evolve as newer data is created or introduced – especially data that’s more vital to your business. Understanding what the data is, the purpose it serves and what it needs to do while it exists in your company will allow you to create lifecycle policies that suit your requirements.
Additionally, since not all data holds the same value and credibility, multiple policies are needed, as one policy can’t – and shouldn’t – oversee all your data. For instance, if data contains personal identifiable information (PII), financial information or information that’s regulated by compliance requirements, it needs a stronger policy than an old image file that holds no value to your organization.
2. Robust chain of custody
Chain of custody is equally important to ensuring data integrity.
As data is transmitted through the business to the various stakeholders and applications that need to reference it, you should have a reliable log of that data’s journey – as well as a clean path for the data to take that journey.
Each time data deviates from an established path, its chances of being corrupted, compromised, manipulated or lost increases. Once that happens, the data loses all credibility.
Chain of custody is really about security, resilience and infrastructure planning, and making sure that only the right people have access to certain data. This is the basis for enacting a zero trust security model, where least-privileged access is applied and users – both inside and outside your network – must be verified before they’re granted access to specific applications. This typically involves some combination of mandatory access controls, discretionary access controls and role-based access controls.
Building a blueprint for data integrity
Data is only as effective as its legitimacy. Right now, only 20% of healthcare executives completely trust their data. Not exactly inspiring.
As more data is created, organizations must prioritize data integrity like never before. So, how can you keep your data clean and trustworthy?
Establish a zero trust framework, set up tools to document information so you can monitor, audit and control chain of custody, and know how your business processes work so you don’t store the data longer than necessary. This blueprint will limit poor data quality and improve data security, limiting sensitive data to select individuals.