Case Study: Efficient Portfolio Analysis & Reporting

Asset Management

Efficient Portfolio Analysis & Reporting

The Challenge: Drowning in Data, Starving for Insights

An established asset management firm, responsible for managing diverse portfolios across multiple asset classes, found its growth hampered by increasingly inefficient internal processes. Portfolio managers and analysts spent an inordinate amount of time manually aggregating data from disparate sources – including market data feeds, custodian banks, internal accounting systems, and spreadsheets. This manual effort was not only time-consuming but also highly susceptible to errors, leading to delays in analysis and reporting. Generating standard client reports, performance attribution analyses, and risk assessments often took days, hindering timely decision-making and impacting client service levels. The lack of a unified data view made it difficult to gain holistic portfolio insights or respond quickly to market changes.

Our Solution: Unified Analytics Platform with Databricks and Tableau

Lydatum implemented a modern, cloud-based analytics platform on AWS, designed to centralize data, automate workflows, and empower analysts with self-service capabilities. The solution centered around:

• Centralized Data Lakehouse with Databricks: We leveraged Databricks on AWS to build a scalable data lakehouse architecture. This unified platform allowed the firm to ingest and store structured, semi-structured, and unstructured data from all relevant sources in one place (using Amazon S3 for underlying storage). Databricks provided the processing power for data transformation, cleansing, and enrichment.
• Automated Data Pipelines: Robust, automated data pipelines were built using Databricks Delta Live Tables and scheduled jobs. These pipelines handled the ingestion, validation, and transformation of data from various sources, ensuring that clean, reliable, and up-to-date information was consistently available in the lakehouse for analysis and reporting, eliminating manual aggregation tasks.
• Interactive Visualization and Reporting with Tableau: We connected Tableau directly to the Databricks lakehouse. Lydatum developed a suite of interactive dashboards tailored to the needs of portfolio managers, analysts, and client reporting teams. These dashboards provided real-time insights into portfolio performance, risk exposure, asset allocation, and attribution analysis. The self-service nature of Tableau allowed users to easily drill down into data, create custom views, and generate standardized reports automatically.

The Impact: Speed, Accuracy, and Actionable Insights

The new analytics platform transformed the firm's operational efficiency and analytical capabilities:

The automation of data pipelines and reporting drastically reduced the time spent on manual tasks, freeing up analysts to focus on higher-value activities like strategy development and alpha generation. Data accuracy improved significantly due to the elimination of manual aggregation errors and the implementation of automated data quality checks. Portfolio managers gained access to near real-time, interactive dashboards, enabling faster, data-driven decision-making. Client reporting became more timely, consistent, and visually engaging, enhancing client satisfaction and trust. The scalable Databricks platform on AWS also provided a foundation for future advanced analytics initiatives, such as incorporating alternative data or building predictive models.

Technologies Used: Databricks (on AWS), Tableau, Amazon S3, AWS Glue (for cataloging/metadata), Python/SQL