July 26, 2023

What is data integrity in database DevOps and change management?

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Change is the only constant in the world of databases and pipelines.

Perhaps add “sprawl” to that short list of database constants, because we’re only capturing and creating more data, every second.

But when it comes to having data you can rely on, extract value from, and share effectively, you can’t go about database changes without keeping a pulse on data integrity. And as data sprawl accelerates, any type of manual process for managing change and ensuring integrity is quickly going to implode — or at least bottleneck your development workflows.

What is data integrity for databases?

Data integrity makes sure every person, team, and platform that wants to interact with your database can do so with speed, accuracy, and efficacy. When your data is properly created, stored, shared, and leveraged while maintaining critical structure, accuracy, value, and form, it has integrity.

Database professionals need to consider both the logical and physical integrity of their data. Logical integrity includes:

  • Ensuring unique entries
  • Building context and relationships between datasets
  • Outlining the spectrum of acceptable values to define and limit data
  • Unique business requirements of your organization’s specific sets of data

Meanwhile, physical integrity refers to actual data storage hardware as well as pipelines, APIs, and other touchpoints. It also means protecting your database from the unexpected — hackers, natural disasters, power outages, and internal malicious activity.  

Throughout database DevOps, management, deployment, CI/CD, and the entire IT/cloud infrastructure, data integrity is a make-it-or-break-it characteristic. With data integrity ensured, database teams will see gains in consistency, security, and speed for better, faster, stronger releases.

In the bigger picture, data integrity maintained through database changes means the organization can expand at the speed of rapid application development while making the best data-driven decisions possible. Think of all the big-dollar decisions made within your organization based on dashboards, insights, and other forms of data analysis. If data was somehow damaged or transformed while the database underwent its updates and changes, suddenly the company’s future could be in the balance.

Where does database data integrity begin?

In simplest terms: at the start of database design. The guidelines and specific workflows, processes, and procedures constructed by database developers are the foundation of data integrity throughout the entire data pipeline, and thus throughout any database changes.

Those database changes are also a key component—or potential weak point—in data integrity. Watertight, bulletproof database change procedures ladder directly into a data integrity strategy. By owning data integrity within the database change protocol, database developers take ownership of and deliver to their teammates accurate, reliable, and accessible data that’s up-to-date and complete.

Imagine a database rollback without data integrity. It could undo months or years of progress if data gets lost, altered, or disorganized. It could derail the database rollback and upend the entire initiative.

Database change opens the door to data integrity threats

Since data transfer happens at massive volume and scale during CI/CD and general database changes, errors in this process are a leading cause of data integrity degradation. Typically, they’re a combination of human mistakes, misalignment of seemingly similar data tables, or a bug within the database change management procedure.

You can then arrive at the conclusion that data integrity is the top priority for DevOps. But while it might be philosophically high on the ranking, the functions and tactics that ensure data integrity may not always be top of mind. That’s why database change management systems need to streamline and automate crucial aspects like access and permissions, validation, changelogs, audits, and rollbacks.

While a smart, experienced human’s guidance is critical to setting up this kind of data integrity protection program, the ongoing execution quickly overwhelms teams when handled manually. And with so many aspects to consider in the CI/CD and other database deployment schedules, it should ideally be a given that all data — before and after deployments — maintains its integrity.

Automated Quality Checks support data integrity in the database change process

So, how can data integrity be prioritized within database management and deployment?

Quality checks support data integrity throughout database DevOps

One method involves Liquibase Quality Checks. They can help by adding an automated layer of governance that enables quality, safety, and consistency.

Quality Checks bring data integrity to the foreground of your deployment by allowing you and other database developers to check your code against the rules, rollback scripts, and taxonomies assigned by DBAs. Additionally, these Quality Checks can confirm details required by security teams to ensure critical alignment before anything is released.

This confidence-boosting data integrity layer empowers developers, reduces DBA review times, supports scalability, and obliterates procedural bottlenecks.

Quality Checks support data integrity by:

  • Auto-reviewing every line of SQL code for accuracy, completeness,  security, and more
  • Instantly providing feedback for quicker turnaround
  • Eliminating manual processes for review and removing the risk of human errors
  • Enforces DBA requirements in every aspect of data structure
  • Bringing database change reviews to earlier stages of the process

With database release automation including Quality Checks, a lot of bad scenarios can be detected before any shared database is changed, eliminating rollbacks and containing the scope of rework required further down the pipeline. Checking changes before they get close to production environments ensures that dependencies aren’t built atop faulty releases, which could trigger a domino effect of breakdowns.

More ways Liquibase supports data integrity

Quality Checks are a specific Liquibase capability directed at the protection of data integrity, but they’re not the only way the database DevOps solution supports data integrity. At its core, Liquibase equips teams with the ability to script and version control all database changes, which inherently feeds into integrity efforts. Keeping track of – and being able to easily, consistently reuse – those change scripts and centrally managing versions sets a foundation of data integrity for any and all evolutions of a company’s network of databases.

By integrating the database change management process into the CI/CD pipeline, Liquibase also prioritizes data integrity by putting every deployment through the ringer of staging and pre-production environments. The ability to test and review database changes before they’re pushed live, just like how software dev teams do in their realm, means nothing makes it live that isn’t functioning properly. Issues can be found earlier, abating any problems down the line.

Bring data integrity into the spotlight for your database teams

Likely the best and fastest way to bring the focus on data integrity to database teams throughout an organization is to focus on database release automation. You can dive into those topics with our robust Database Automation Guide, which lays out the critical elements for CI/CD, compliance, security, and general database management professionals.

You can also venture into the Liquibase product, a database change management solution that handles things like data integrity throughout database deployments, so you and your teams can focus on full-speed coding and continuous delivery.

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