Enterprise Data Transformation and Analytics Platform
Consolidated siloed operational data into a centralised AWS lakehouse with Glue ETL, a Redshift warehouse, and QuickSight dashboards.
~$350K
Annual cost reduction
~80%
Analysis time reduction
Meet our client
Pakuwon Group is one of Indonesia's largest real estate and mall operators, managing a nationwide portfolio of malls, offices, and high-rise residences with an annual maintenance and operations spend running into the billions of rupiah.
Context
Pakuwon Group, one of Indonesia's largest real estate and mall operators, runs a nationwide portfolio of malls, offices, and high-rise residences with annual maintenance spend north of IDR 5 billion. Management wanted to run the portfolio on data rather than instinct, and to lay the groundwork for AI, but the numbers lived in disconnected systems and manual spreadsheets.
Challenge
It was the group's first formal data transformation, and the starting point was tough:
- Operational and maintenance data fragmented across departments and individual buildings
- Records kept in siloed, manual, tabular formats with little analytical value
- No centralised data architecture or acquisition pipelines
- Tight timelines set by management's transformation agenda
- Almost no visibility into asset performance, maintenance efficiency, or cost drivers
What we did
VentureSEA acted as the end-to-end data transformation partner and delivered in disciplined phases.
- Ran an as-is assessment and gap analysis, then defined a target-state architecture aligned to business goals
- Designed a centralised lakehouse on AWS, with a Redshift warehouse, purpose-built data marts, access controls, and data lineage from source to dashboard
- Built ingestion and ETL with AWS Glue to consolidate and standardise data from multiple source systems in near real time, with schema enforcement and quality checks at each stage
- Delivered interactive QuickSight dashboards tailored to management, operations, and maintenance teams
- Stood up a data governance working group with the group's IT and operations leads, and trained internal analysts to own dashboards and data quality after handover
Outcome and impact
- Centralised, standardised enterprise data with clear ownership and lineage
- Near real-time visibility into asset and maintenance performance
- Governed data foundation ready for AI and advanced analytics
Business value
With portfolio maintenance and asset spend running into the tens of billions of rupiah a year, the lever is efficiency, not headcount. Near real-time visibility into asset performance typically removes 8 to 10% of maintenance cost by ending over-servicing and getting repair-versus-replace calls right. On an annual base of around IDR 60B, about $3.8M, that is roughly $300K to $380K saved a year. Analysis cycles that previously ran for weeks now complete in days, an 80 percent reduction in time-to-insight for asset management and maintenance decisions.
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