Centralized Data Warehouse for Faster Deal Analysis

Client overview

The client is an asset appraisal and liquidation firm managing large volumes of deal-related data across multiple files, worksheets, and historical records. As the business scaled, the leadership team needed a more reliable way to manage information, strengthen data integrity, and convert historical deal data into actionable insights.

Problem statement

The client’s data environment was fragmented and heavily dependent on manual processing. Large Excel-based datasets, ranging from approximately 0.5 million to 2 million rows daily, created bottlenecks in data handling and analysis.

Key challenges included:

• Inconsistent and inaccurate data that limited confidence in decision-making
• High-volume Excel files that slowed processing and increased operational effort
• Difficulty navigating multiple files and worksheets to extract critical information
• Limited use of historical data for long-term trend analysis and strategic planning

For senior leadership, this created a clear operational risk: growing data volumes were slowing analysis, increasing manual dependency, and limiting visibility into business performance.

Solution provided

Decimal Point Analytics designed and implemented a centralized data warehouse to help the client manage large datasets with greater accuracy, consistency, and efficiency.

The solution included:

• Development of a structured information repository and archive for deal-related data
• Independent deal-processing workflows to reduce manual dependency
• Data quality checks to improve consistency and reliability across datasets
• Management dashboards to support faster, insight-led decision-making
• Better access to historical data for trend analysis and operational planning

By consolidating scattered information into a centralized architecture, DPA enabled the client to move from file-based processing to a more scalable and insight-driven data environment.

Outcome

The engagement delivered measurable operational improvements across data management, reporting, and infrastructure efficiency.

Key outcomes included:

• Creation of a centralized data warehouse for streamlined information management
• Improved operational efficiency through reduced manual processing effort
• Cost savings through optimized infrastructure and lower resource dependency
• Faster access to structured historical data for deeper analysis
• Simplified data processing while maintaining performance and reliability

The client was able to strengthen its data foundation while improving the speed and quality of decision-making.

Key takeaway

For CXO teams, data warehousing is not just an IT improvement. It is a strategic operating capability. A centralized and quality-controlled data environment enables faster decisions, reduces operational friction, and creates a stronger foundation for analytics-led growth.

Is fragmented data slowing your business decisions?

Decimal Point Analytics helps financial services firms build scalable data warehouses, improve data quality, and convert complex datasets into actionable insights.

Speak to our data engineering experts to assess how a centralized data warehouse can improve your operational efficiency.