Streamlining HR data management: Transforming a major financial organisation’s HR platform
A prominent Australian financial services group faced issues in managing its HR and recruitment data, leading to inefficiencies and delayed feedback to candidates. Cevo successfully transitioned the organisation by building a data lakehouse using Iceberg and a data warehouse with Amazon Redshift, streamlining analytics and automating processes. This transformation improved access to insights, streamlined operations and enhanced data security, ultimately empowering data-driven decision-making and a more efficient recruitment process.
Data-driven insights
Via streamlined HR operations
Weeks to hours
Daily report generation
Financial Services
Industry
The customer is a prominent Australian financial services group, offering banking, superannuation, wealth management and advisory services globally.
Business challenge
The financial organisation’s HR department struggled with data management as the company expanded. Traditionally relying on an SQL server for data storage and CSV files from different external systems, the data management process became disorganised, inefficient and difficult to scale.
As the organisation grew, data volumes increased, resulting in extended data extraction times and delayed access to insights. Scalability also became a critical issue, prompting the need for a new HR platform that could accommodate expanding data needs.
The initial data model created within PowerBI was disconnected from the data platform, making it inefficient and complicated to extract information. The complexity of the systems led to a heavy dependence on the organisation’s data platform team for various manual tasks, which consumed valuable time.
The organisation also faced challenges in recruitment due to the unreliability of data. The existing system was often slow and fragmented, with inconsistent access to accurate analytics and frequent reliance on manual interventions. This caused confusion among candidates, as identifying the right contacts was challenging. Disparities in information across the business occasionally led to the loss of potential candidates during the recruitment process.
Solution
Cevo helped the financial organisation transition from an on-premises SQL Server and CSV files to a modern in-house data lakehouse solution on Iceberg and a data warehouse on Redshift. The aim was to streamline the organisation’s various HR data sources and systems into one simple and accessible solution.
Our team conducted an extensive analysis of the organisation’s data platforms to ensure the new solution could effectively cater to their unique business requirements. The process commenced with a pilot phase that validated the approach’s effectiveness, followed by the production phase using an existing Cloudera cluster.
Cevo consolidated the existing SQL and legacy databases into a unified HR platform, enabling on-demand analytics capabilities.
The solution leverages a combination of technologies, including Apache Spark, Iceberg, Amazon RedShift, PowerBI, and Apache Airflow. These technologies were instrumental in executing ETL (extract, transform, load) processes, streamlining operations and improving data accuracy and efficiency.
Our team also automated several processes for the financial organisation, reducing the manual intervention previously required by different teams.
A robust data security framework was also established to protect sensitive HR information, ensuring data privacy and regulatory compliance.
Outcomes
In partnership with Cevo, the financial organisation was able to streamline operations and improve HR processes, increasing the potential for data-driven decision-making and improving the candidate experience. Other benefits include:
- Improved data access – The new data lakehouse empowers the organisation to access reliable analytics and insights for better HR data management.
- Efficient data retrieval – Historical data was migrated and streamlined, allowing quicker access to essential records.
- Data lakehouse structure – Four layers were built in the data lakehouse for improved data organisation and retrieval.
- Faster reporting – Integration with PowerBI enables daily report generation, reducing a previously weeks-long analysis to just hours.
- Increased data accuracy – Automation has improved the accuracy and reliability of data, ensuring consistent, real-time insights into recruitment activities.
- Improved recruitment process – With easy access to background checks and verification data, the recruitment process has become more seamless and efficient.
- Stronger data security – The platform has enhanced data governance, offering better control over access to sensitive HR information.
- Automated regression scripts – Six reusable patterns were created for data quality checks and ETL logic accuracy, improving overall system reliability.
- Upskilling and knowledge transfer – The internal team gained hands-on experience, learning to expand ETL scripts and apply the solution to future projects, ensuring long-term and sustainable growth.
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