Batch Processing vs. Real-Time Data Quality Validation

The right data processing strategy depends on your company’s specific needs and objectives.

7 minute read

Data is the lifeblood of businesses and data quality is a top concern for 84% of CEOs. Naturally, inaccurate, inconsistent, or unreliable data can be disastrous. Untrustworthy data leads to misguided decisions. According to Gartner, poor data quality costs organizations an average of $15 million per year.

You can improve the accuracy of the data on which your organization depends in two ways-batch processing or real-time validation. Both methods have their advantages and disadvantages, and your choice about the most appropriate strategy depends on your needs and objectives.

What is Real-Time Data Quality Validation?

Real-time data quality validation allows you to assess the accuracy and reliability of your data as it’s being processed–ideally when the data first enters your organization. This validation technique ensures you can act immediately to make corrections if data isn’t as it should be. Real-time validation revolutionizes data management by ensuring the accuracy and consistency of data in the very moment it’s generated. 

Real-time data validation delivers a host of benefits:
Immediate Error Detection: With real-time validation, errors are spotted and corrected as soon as they appear. No need to wait for the next batch process to uncover mistakes. 
Enhanced Data Accuracy: Real-time processing massively improves data accuracy. It’s a vigilant watchdog constantly guarding against errors.
Improved Decision Making: Accurate data equates to sound decisions. Real-time validation ensures the data you’re using to make crucial business choices is current and correct.

Real-time data validation is essential if you will use the data at once, such as for fraud detection in banking transactions, computing shipping charges for online orders, or allowing customers to choose a shipping method based on calculated delivery dates. If you check the accuracy of a shipping address as a customer completes an online order form, you can notice critical errors such as a missing apartment number or transposed digits in a ZIP code. Your order entry system can prompt customers to correct their shipping information before finalizing the order.

Inaccurate shipping addresses are costly. According to Pitney Bowes, businesses often underestimate the delivery costs attributable to poor quality addresses. This includes the cost of wasted postage, courier-imposed fees, and labor hours spent correcting addresses and re-sending the packages. Additionally, bad shipping addresses can lead to delayed shipments, which can result in dissatisfied customers and lost sales. A survey by Convey found that 84% of consumers would not return to a retailer after just one negative delivery experience. An address not corrected when it enters your system could easily cost you a customer–along with all their potential future purchases.

But that’s not all. Real-time data quality validation isn’t just about instant gratification. It’s a powerful tool for improving your overall data management strategy, ensuring you’re always ready with accurate and reliable data. If you’re after agility, quick decision making, and high data accuracy, real-time validation is an excellent strategy. 

Drawbacks of Real-Time Data Quality Validation

Though real-time validation has lots of benefits, you should be aware of a few potentially negative aspects of this technique. 

Real-time data validation can be a resource hog for some operations, such as scanning an extensive database for duplicates before allowing new data to be accepted. You should anticipate a heightened demand for computing power. This could mean a hefty investment in IT infrastructure. 

And then there’s the challenge of managing real-time data streams. Data can flow into an organization from various sources, at different velocities, and in varied formats.

Last, there’s the question of data privacy. Real-time processing means data is often stored temporarily in memory, which could heighten security risks if not handled securely. 

Does this mean you should steer clear of real-time data quality validation? Absolutely not. But you need to weigh the pros and cons.

What is Batch Data Quality Validation?

Batch data quality validation refers to checking large amounts of data for accuracy and consistency rather than performing these functions piece by piece. 

Efficiency is the name of the game with batch processing. By handling large amounts of data at once, it optimizes system resources. Batch processing also allows for schedule flexibility. Schedule your processes to run during off-peak hours to avoid disrupting your regular business operations.

Comprehensive error and exception handling occurs during batch processing. All issues are logged and can be addressed systematically. Batch processes generally create statistics to show which data was processed and the results of the data quality procedures at work. 

Another benefit of batch processing is the opportunity to change your data all at once. Mass updates allow you to enforce uniformity and consistency standards for your data. These are essential pre-requisites for operations such as eliminating duplicates or combining data.

Drawbacks of Batch Processing for Data Quality Validation

Batch validation is a reliable procedure for many organizations. But as the saying goes, no single size fits all, and there can be certain shortfalls to this approach. 

Time Sensitivity: In a world that’s increasingly leaning towards real-time insights, batch processing can seem to be lagging. Because of its nature, batch processing can only validate data periodically. An error that occurs between batch updates won’t be caught until the next scheduled validation process.

Load Balancing: Batch processing can put a significant load on your systems. This is true if large amounts of data are being processed simultaneously, which can slow down other tasks and reduce overall system performance.

Manual Intervention: While batch processing automates many tasks, it still requires some level of manual setup. Scheduling, monitoring, and adjusting scripts can consume time and resources, which can be a drawback for some organizations.

Lack of Flexibility: Batch processing operates on a predefined schedule, which may not align with unpredictable data influxes.

Batch processing is not without its flaws. Yet, understanding these drawbacks can help guide decision-makers towards the best choice.

Choosing Between Batch and Real-Time Data Quality Validation

Most organizations support data quality with a variety of methods. No one really has to choose between batch processing and real-time data quality validation. In certain scenarios, one or the other is usually an obvious choice. Some common factors that determine the best way to correct and confirm data are:

Data Volume - If your organization is dealing with massive amounts of data, batch processing might be your champion. It’s designed to handle large volumes of data, making it an efficient choice. However, if your data stream is more of a steady trickle, real-time data quality validation may be the better path, as it provides immediate feedback and corrections. 

Speed Requirements - Are you after speed? Real-time data quality validation is swift, providing immediate results. Batch processing operates at a more leisurely pace, processing data at scheduled intervals.

Data Complexity - If your data features complex relationships, batch processing may be better equipped to handle it. Conversely, real-time data quality validation shines when your data is less complicated and can be validated on the fly. 

Operational Needs - Your operational needs may dictate your choice. If your business requires immediate data validation, then real-time is the way to go. However, if your operations can accommodate scheduled data updates, batch processing may be your best bet. 

The choice between batch processing and real-time data quality validation depends on your unique needs and circumstances. Many businesses decide they need both methods of data quality validation.

Firstlogic’s Products for Data Quality

Firstlogic’s Address IQ® products handle all the data quality processing operations. Whether running on-demand in real time or as batch jobs, the software allows companies to handle data quality tasks, making them seamless and integral parts of the data lifecycle.

Consider using Firstlogic’s Address IQ® SDK and Workflow IQ® SDK to achieve real-time data quality validation. You’ll join leading organizations who have transitioned their data management processes from good to outstanding. These Firstlogic products allow you to integrate comprehensive data quality measures into your applications and workflow-without the hassle of writing the routines yourself.

Of course, real-time data quality isn’t just about stamping out errors. It’s about making the most of your opportunities. With the Address IQ SDK and Workflow IQ SDK, you’ll have the power to make data-driven decisions on the fly, harnessing the full potential of your information arsenal operating within your own applications.

Firstlogic’s Address IQ product includes an innovative batch tool designed to maintain the accuracy and consistency of your data by scheduling automated data quality validation processes. 

Address IQ works behind the scenes, breaking the data validation operation down into manageable tasks. This approach allows your system to work with large data volumes without breaking a sweat. The result? A high level of data reliability without a major drain on your resources.