Unit4, a leader in enterprise cloud applications for people-centric organisations, today announced Data Hub, a managed, high-volume extraction layer built into Unit4 ERPx. This service eliminates the complexity of extracting data and managing connections between analytics tools and core ERP systems, enabling organisations to access real-time insights and respond faster in an increasingly competitive environment.
Data Hub delivers finance, project and HR data directly to Power BI, Microsoft Fabric, Snowflake, BigQuery and any platform supporting the open Delta Sharing protocol. With no API ceilings or rate limits, file transfers or manual refresh jobs, organisations can access up-to-date data more easily. Data Hub is maintained alongside every Unit4 ERPx release and data connections remain intact through platform updates, eliminating the need for costly rework. This reduces hidden maintenance costs and enables analytics teams to focus on delivering insights rather than managing integrations.
Data Hub addresses two key limitations of traditional ERP data analysis, which typically relies on IT teams to manually schedule data exports before reformatting and loading the data into business intelligence (BI) tools. If problems are encountered with the export, the report will be erroneous. If the schema changes, the pipeline breaks. The alternative relies on extracting data through APIs, which are subject to rate limits, pagination constraints and payload size restrictions. As data becomes more complex, for example a General Ledger table, extractions become harder to complete reliably and require ongoing maintenance whenever the schema changes.
"In the automation era, an organisation’s data is its competitive advantage,” said Jennifer Sherman, Chief Product Officer, Unit4. “Unit4 is proud to be in a position to help our clients take advantage of their wealth of knowledge and insights. Data Hub makes the extraction and management of data connectivity Unit4’s challenge, not yours, so you can devote time to what really matters to your organisation."
This approach ensures:
High-volume data access, without API limits: purpose-built for bulk, analytical workloads rather transaction-by-transaction API calls.
Focus is on analysis, not export menus: Data and analytics teams get governed access to Unit4 ERPx data in the platforms they already use. No IT tickets, no waiting for manual extracts.
Data stays current automatically: Automated refresh happens on a daily, weekly or monthly basis depending on subscription rather having to maintain scheduled export jobs. Also uses incremental loading to ensure only changed records transfer, not full file dumps.
Pipeline does not break when Unit4 ERPx updates: Data Hub schema versioning is maintained by Unit4 with each Unit4 ERPx release, so data connections are designed to survive platform updates. No emergency fixes or silent failures.
ERP performance is unaffected: Analytical workloads run on a separate data layer, independent from Unit4 ERPx transaction processing to ensure heavy loads do not slow down operational users.
It works with existing and future tech stack: As Data Hub is built on Delta Sharing if a customer moves from Power BI to Fabric, or from Snowflake to BigQuery the data connection does not need to be rebuilt.
“Data Hub was easy to set up and provided us with the tools to feed the data into our reporting models,” said Chris Dixon, Finance Systems Manager, Butlins. “This improved our productivity as we no longer had to download data from the system into Excel to feed manually into our reporting models. All the reporting objects we need to report against are available in the tool.”
There are several possible use cases for Data Hub, including enterprise analytics and BI at scale as it provides bulk, scheduled access without API constraints allowing the data warehouse to stay current and BI dashboards to reflect the real state of the business. Finance teams in multi-entity organisations who want to analyse and consolidate historical General Ledger data for management reporting can use Data Hub. It allows them to connect actuals, cost centre budgets, and variance data directly into a BI platform to enable live performance rather than historical analysis.
Data Hub also enables faster onboarding and lower operational complexity compared to API-based ETL approaches, for organisations requiring bulk, scheduled ERP data for analytics. Being based on Delta Sharing avoids lock-in with a single analytics vendor as well as reducing ETL complications. The technology can also be used by Data science and AI teams who need large, historical ERP data for model training and experimentation. Data Hub provides repeatable, scheduled bulk access running on a separate data layer from the ERP to ensure analytics workloads do not compete with operational users.
