How to ensure data integrity

16/12/2024 7 minutes to read

Andreas Kozachenko

Head of Technology Strategy and Solutions

Imagine just one tiny mistake in data sending ripples of chaos across half of your business operations. Data access gets messy, decisions go sideways, and customers are left annoyed and frustrated. Or picture a single, unnoticed error sitting silently in your database for months, only to trigger a storm in a critical request. These are scenarios no business wants to face.

So, how to ensure data integrity in such a complex environment as ecommerce with 1 mln requests per sec? In this article, we’re going to talk about 5 data integrity best practices, coming from Expert Soft’s experience, on how to deal with data integrity with SAP Commerce Cloud on the checkout process example.

Quick Tips for Busy People

Keeping data integrity intact can be a lot to handle. However, a few data integrity best practices can help out. Here’s a quick rundown of what you should remember to protect integrity of data and keep your ecommerce game strong.

When data can lose integrity. Problems in data integrity largely stem from human error, system failures, security breaches, and concurrency conflicts. Any of these issues can break crucial operation processes, e.g. checkout.
Data integrity within checkout. If you aim to improve the data integrity of the checkout process, treating it as a single process can help avoid unnecessary changes in the database. And implementing transient data states and applying validation at various steps can help avoid inconsistencies during the process.
Additional measures. To achieve data integrity, regularly back up data, use encryption, and follow security best practices to ensure data resilience against sudden failures or breaches.

Now it’s time to take the first step in creating more resilient systems — getting a grip on common errors that can disrupt data integrity.

When Data Can Lose the Integrity

88% of American companies claimed a negative impact of bad data on their operations, with the average organization losing about 12% of its total revenue. The result of inconsistent data can pop up unexpectedly in almost any operational aspect, from analytics errors to incorrect items in the users’ orders. In fact, among the top 3 reasons why users return goods is the inconsistency between the actual product’s appearance and what is shown on the website.

These figures point out how important it is to maintain data integrity for ecommerce. And here is how data integrity can break down.

Human error

The more complex the system and its operational flow and sources of data, the higher the chances of human error. That’s why within our SAP Commerce development services, we often solve automation challenges, such as uniting several operations into a single workflow, to minimize the need for manual intervention. The result can be a 50% reduction in human error.
System failures

When servers go down or there are integration or access issues between the ecommerce platforms and third-party systems, it can grind operations and data consistency to a halt. For example, if your inventory management tool isn't syncing with your platform, you might end up overselling or missing out on orders.
Security breaches

The average cost of a data breach has reached $4.88 million. The biggest threats are coming from cyber-attacks or unauthorized access to sensitive data, leading to data leakage or complete deletion.
Concurrency issues

During peak hours, numerous users are accessing the same information. Without the concurrency controls in place, this would result in stock conflicts, for example, when two buyers purchase the same last item.

To tackle these issues, we need solid practices in place. Since the data integrity aspect within ecommerce is too wide and we can talk about it for hours, let’s focus on the checkout process and break down how to ensure data integrity based on its example.

Data Integrity Within Checkout

With the checkout process including several steps, below we’ll provide some data integrity best practices as the flow goes, helping you achieve more streamlined data integrity and safety controls.

Transaction management

Here we’re talking about databases. And yes, while databases may not be directly involved in the checkout steps, they form the foundation where all data flows originate. As such, we can’t overlook their critical role when answering the question of how to maintain data integrity.

The core best practice to improve data integrity is to follow ACID principles when adding data to the database.

Atomicity
Transactions are all-or-nothing. If one part of a transaction fails, the entire operation is rolled back.
Consistency
Data adheres to predefined rules and constraints before and after a transaction.
Isolation
Transactions must execute independently of one another. The result of a transaction must not be visible to others until it is completed.
Durability
Once a transaction is committed, its changes must be permanent, even in the event of system crashes, power failures, or other interruptions.

Checkout consistency

From a data integrity standpoint, you have to look at the entire checkout process as a single transaction, where each step is properly connected and executed. This approach, especially with SAP Commerce Cloud, prioritizes consistency and ensures data integrity.

It’s only after the checkout process has been successfully completed that the system should update the inventory and trigger order fulfillment. This will ensure smooth operations and accurate customer order handling without data loss or duplication.

While treating each step of a transaction as an independent action that modifies system data is theoretically possible, it largely depends on the business model. However, this is not the common practice, and we haven’t encountered such scenarios in our projects.

Support for transient data state

So, since data only changes once an order is done, it would be really important to have a middle state for data and some extra checks to prevent potential conflicts and ensure data integrity. For example, when several people are trying to buy that last item in stock at the same time. Here’s how you can bring these data integrity best practices to life.

Reserve items when adding to the cart

As soon as the user adds something to their cart, make sure to hold that amount for them. This means those items are set aside for that user, and their availability is temporarily reduced for other users.
Synchronize reservations across users

Make sure these reservations are being updated in real time. If someone reserves the last item, everyone else instantly sees it as sold out when they go to add it to their cart.
Re-validate stock at checkout completion

This is where we recommend checking the real stock availability one more time and if everything is correct, update the information as the checkout is completed.

Data validation

We can name it as a common best practice at Expert Soft projects to implement real-time front-end checks of user input during checkout together with more robust back-end validation and contextual accuracy to achieve data integrity:

Front-end validation

Let users know immediately if they make a mistake entering data. For example, a user needs to input a tax code during checkout that consists only of numbers. Any non-numeric characters in the input? Error! Throw a message to notify the user about it and ask to enter the valid code. This step enhances user experience by providing instant feedback and reducing submission errors.
Back-end validation

Once the data is submitted by the user, we recommend implementing additional checks on the back-end side to improve the integrity of the data. Going back to the tax example, the back-end can send a request to the third-party system specialized in tax codes and cross-check to validate whether that entered code exists and is valid.
Contextual validation

Even valid data can be incorrect in certain situations. For example, a tax code can look good and be found in third-party systems, but it might not align with the organization or jurisdiction of the user in business internal systems. So, you can catch the error early and notify the user about it, before going ahead and starting the business processes.

Correct logging and monitoring

In SAP Commerce Cloud, logs are useful for monitoring and audit of business processes, such as order fulfillment, which starts on the business side when checkout is completed. You can view logs through the back-office, diagnose issues, and even restart operations directly within the system during the checkout and fulfillment process. This is how it works.

Tracking each step
Logs provide you with insight into all parts of the order fulfillment process, so you can check up on the progress. This keeps everything clear and helps you track down any hold-ups or mistakes.
Detecting and fixing issues
In case a process fails at any step, logs can show the problem itself and its context. This makes it easier to understand what went wrong and pinpoint the root of the problem, enabling a quick resolution.
Restarting failed processes
Once the problem is sorted out, it’s often possible to resume the process straight away from where it failed within the back-office. This avoids resubmitting the entire workflow, saving time and reducing interruption.

What else to remember

To ensure data integrity and fully secure your ecommerce platform, we offer some more strategies to help build a safety net.

Regular backups

Regular backups are necessary for data security and data integrity in case something goes wrong unexpectedly. With SAP Commerce Cloud, backups ensure you can recover essential data after system crashes or database corruption or restore accidentally deleted or overwritten data.

If you do have current backups and a well-tested recovery plan, then you can ensure continuity of business with very little downtime in the event of any unforeseen situations.

Data encryption

Encryption of data, both in transit and at rest, helps to ensure data integrity by safeguarding sensitive information. As encrypted data is unreadable without the correct decryption key, if the data is altered, it will fail decryption or integrity checks, signaling unauthorized modifications.

For data in transit, protocols like SSL/TLS are vital. They encrypt communications, ensuring the data remains secure and intact during transfer. Additionally, many encryption protocols include hashing or digital signatures, which validate that the data has not been modified.

Platform security best practices

To maintain data integrity in ecommerce, you have to be proactive about security. Check out these key practices to shield your systems and data:

Regulate user access. Access controls should be strict and allow only authorized staff to change or view sensitive data. This would ensure the minimal chance of human error or unauthorized changes hurting data integrity.
Use data loss prevention (DLP) tools. DLP tools will monitor and protect sensitive information from loss, misuse, or access by unauthorized users to secure the integrity of data.
Manage cookies responsibly. Ensure that all cookies are properly configured and managed to be secure and meet data protection regulations. In this way, the possibility of user data being accessed or exploited by malicious actors is eliminated, ensuring the integrity of data.

By adopting these and some more security practices, you can protect your data, reduce vulnerabilities and ensure data integrity within your ecommerce platform, maintaining compliance with the industry regulations.

Data Integrity Challenges

Beyond ensuring data integrity during checkout, it’s important to address broader challenges that can impact data integrity and your ecommerce operations. Here are some key hurdles organizations must overcome to protect data accuracy and consistency.

Data complexity

Managing diverse data formats and sources is a challenging task that involves strong systems that can manage structured and unstructured data while ensuring accuracy and consistency across all platforms and applications.
Integration issues

Try to maintain data integrity while integrating different systems and platforms, which is vital to prevent any mismatches, duplicates, or loss, since that can disrupt workflows and compromise data integrity and quality.
Scalability

As the volume of data grows, so do the systems, while there’s a strong need to maintain data integrity. Hence, efficient mechanisms for storage, processing, and validation are needed to handle growing demands without errors.

To Sum Up

For businesses, control of data integrity within ecommerce software means being accurate, consistent, and reliable to win over customers and ensure operations running without a hitch. This also means transparency within the company and the ability to make data-driven decisions.

However, with data constantly flowing and being updated across the entire system, even data integrity best practices can’t always ensure immediate solutions to your challenges. But an experienced partner can.

Relying on our expertise with 40+ completed ecommerce projects, we at Expert Soft know how to make your operations more secure and efficient. Reach out to explore how we can support your goals.

FAQ

What is data integrity?

Data integrity is all about keeping the data accurate, consistent, and reliable from start to finish. In ecommerce, for example, data integrity keeps controls of inventory records spot on as products get added to carts and bought.
What is data quality?

Data quality refers to the accuracy of data and whether it fits the purpose you need it for. For instance, in customer relationship management, ensuring better data quality means having accurate and timely contact information, which supports improved communication and more effective personalized marketing.
How to define data integrity within the system?

To define data integrity within a system, you should establish processes, rules, and mechanisms that ensure data remains accurate, consistent, and reliable throughout its lifecycle. Some practices include regular data audits, error handling, recovery mechanisms, and real-time monitoring.
What are automated tools for determining data integrity?

Tools that help protect integrity of data include data validation tools, automated testing frameworks, completeness verification tools, and data consistency checkers. Analytics platforms and customizable systems can also be great in the automatic identification and flagging of inconsistencies, errors, or missing data to keep your dataset accurate and reliable.