Personalizing Talent Acquisition with IoT: A Case Study of 104 Corporation
Technology Category
- Analytics & Modeling - Machine Learning
- Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries
- Cement
- Education
Applicable Functions
- Maintenance
- Warehouse & Inventory Management
Use Cases
- Construction Management
- Infrastructure Inspection
Services
- Cloud Planning, Design & Implementation Services
- Training
About The Customer
104 Corporation is Taiwan’s leading online recruitment solutions provider. The company uses cloud computing and machine learning to help hiring companies and millions of job seekers improve their recruitment results and experiences. They have an extensive network of job advertisers and customers, and have access to terabytes of highly valuable, private data, including personal information, engagement details, and transaction information. Millions of job seekers and hundreds of thousands of recruiters depend on 104 Corporation’s current and accurate recommendations, using the insights gleaned to make effective recruitment solutions and deliver personalized recommendations and more relevant job opportunities.
The Challenge
104 Corporation, Taiwan’s leading online recruitment solutions provider, was facing challenges due to their legacy cloud tooling and the need for a modern data infrastructure. Despite having access to terabytes of highly valuable, private data, including personal information, engagement details, and transaction information, the company struggled to scale pipeline costs effectively and spent significant resources on maintenance operations. This was slowing their ability to be truly data-driven. Their existing systems were siloed, preventing data teams from gaining relevant, timely insights for informed decision-making. The company was hampered by specialty ETL tooling like EMR and a legacy data warehouse in SAP Sybase that were disparate and complex to scale. As the company continued to expand, the increasing quantity of data became significantly more challenging to manage and utilize.
The Solution
104 Corporation modernized their infrastructure on the Databricks Lakehouse Platform to address these limitations. This helped to unify all their data into a standard view for downstream analytics and ensured real-time availability of insights for different groups across the organization. The company utilized Databricks Lakehouse and Delta Lake to accelerate ETL for BI workloads that power executive dashboards on key performance indicators and insights into the overall user journey. The new platform also allowed the company to build high-performance ETL pipelines that support training new ML models to better summarize company and job postings, maximizing the volume of user impressions. To further drive AI democratization and reduce developing time, 104 Corporation also deployed MLflow, which brought together the various teams across the company into one unified ecosystem that enabled seamless, efficient knowledge-sharing.
Operational Impact
Quantitative Benefit
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