Lindsay Corporation Case Study

The Challenge

The Lindsay corporation’s challenges with integrating disparate systems into Databricks and putting logic and reporting in the hands of decision makers were multi-faceted.

Lindsay’s HR and payroll teams had several key challenges, in their day-to-day operations, adding up to dozens of manual administrative hours per week. Here’s a short list of issues they had before connecting their systems with DLH.io:

Reports on payroll data, such as paid data are run by pay group and pay period, making it impossible to generate one report for an entire month, quarter, or year.
Users primarily relying on Dayforce's "canned reports" which are not distributed and often new reports are created and confuse the team as to which report is the correct report to use.
To get a comprehensive report, a general ledger (GL) account holder has to pull multiple reports by pay group and pay week. For a month with four paychecks (four pay groups, one weekly, three bi-weekly), this can result in about 16 reports and hours of work each time.
Basic tasks, like running a report to find out who does not have holiday pay, are described as a "nightmare".
The time reporting, even for basic time functions, is very complicated in Dayforce, in contrast to the simpler Kronos plug-in they used previously with ADP Workforce Now.
The organization has over 400 hourly employees and uses Dayforce's workforce management system for time tracking but requires better reporting and visibility to integrate with other business logic to get an enterprise view of how the business operates end-to-end.

How DLH.io Solves Addresses These Challenges

DLH has worked with both Ceridian Dayforce and Databricks systems for years, proving the capability of the DLH platform to seamlessly integrate these and other systems in a reliable and automated manner. Our customer service team works with customer executive teams and department heads and they love the outputs and seamless integration DLH.io provides. The best data and analytics engineers appreciate the reliability that allows them to focus on the value that only they can bring as stewards of data for their organization. They know that if the try to build a similar solution they will have to maintain it and the time to develop even a remotely similar solution is spending time and money they should use to focus on other tasks:

Function: DLH.io acts as a middle-man system for data synchronization from Dayforce. Reliably DLH.io does what your data engineer team should not be doing - integrating APIs, Change Data Capture, and reliable transmission of data from Dayforce; otherwise your team is attempting to become a product development team instead of a shared services group using their expertise to build data models and analytics for exactly how your organization operates.
Interface and Entities: The DLH.io interface allows configuration to connect to a Dayforce instance via Dayforce’s API access. DLH also offers more than 80 Dayforce entities/tables for extraction, including HR incidents, payroll, payroll tax, pay adjustments, pay summary, punch labor, punch metrics, and transfers.
On-going Updates: DLH.io keeps up with Dayforce and updates its system every quarter to include additional entities that come with new Dayforce versions.
Custom Report Pull: DLH.io has the unique ability to pull a custom report built in Dayforce as a data set/structure, making it available for use elsewhere in the organization, such as Databricks.
Historical Load: The system offers a "historical load" concept to pull a large amount of past Dayforce information (e.g., 13 to 15 years worth). The first full historical run of data, such as all of 2024 data, could take up to 20-24 hours. After that, it runs incrementally, picking up only changes.
Synchronization Speed: The synchronization can be scheduled to run every 24 hours, but the maximum recommended speed for Dayforce is one hour.
Automated Retries: DLH.io has automatic retry options for sync failures, which typically occur due to Dayforce's throttle limit.
Data Staging: The system uses an ephemeral (temporary) staging concept for synchronizing data to the target system. Users can also configure DLH.io to use their own ephemeral object storage buckets (like in Azure or AWS) to ensure PII, HIPPA, and other secure compliance requirements.
Compute: All compute for the data synchronization is included in the pricing and scales as needed just like you modern data stack data warehousing.

If you have questions about how DLH.io can integrate your Dayforce or other operational systems and databases into Databricks or your other downstream warehouse or medallion architecture, please contact us for a demo and pricing.