Background image source Unsplash.com. Citco logo is a trademark belonging to Citco Group of Companies and Curaçao International Trust Co.
Citco, also known as Citco Group of Companies and Curaçao International Trust Co., is a privately-owned global hedge fund administration company headquartered in the British Virgin Islands, established in 1948. It is the world's largest hedge fund administrator, overseeing more than 2 trillion U.S. dollars in managed assets. Our experience working with Citco includes the creation and implementation of a data lake, as well as data science and data processing. We are currently defining the next phase of the project, where the created unified data model is being implemented at various organizational levels, continuing their digital transformation.
Citco faced challenges in managing its generated data, which led to inefficiencies in storage, processing, and timely decision-making. These challenges included difficulties in scaling data infrastructure and developing data-driven products, all of which were compounded by the limitations of existing systems and the absence of a centralized data repository.
The company faced challenges in managing large amounts of varied data, including structured, semi-structured, and unstructured formats, leading to storage and processing inefficiencies.
Existing systems caused delays and complexities in data access and analysis due to fragmented data sources, hindering timely decision-making.
The need to utilize advanced analytics and AI was constrained by the limitations of the current data infrastructure, impeding the extraction of valuable insights.
The business's growth was hampered by an inability to scale data storage and processing capabilities efficiently to meet increasing data demands.
The lack of real-time data processing capability delayed critical business decisions, impacting operational effectiveness.
The management of data across multiple systems was becoming increasingly costly, necessitating a more cost-effective centralized solution.
The lack of a single source of truth led to inconsistencies in reporting and decision-making, necessitating a centralized data repository.
The slow pace of developing data-driven products due to existing data infrastructure limitations was a significant impediment to market responsiveness.
In the process of implementing an operational data lake at Citco, several technical challenges were addressed. These challenges spanned from integration issues with existing systems to ensuring data security compliance. Efficient handling and processing of large volumes of data, cost management, skill set acquisition, and user adoption were also critical areas that required careful consideration. The following points highlight these challenges in detail:
Integrating with existing legacy systems and databases, ensuring compatibility and minimal operational disruption.
Safely migrating existing data while maintaining integrity, quality, and consistency.
Designing a scalable and high-performing system capable of handling large data volumes efficiently.
Setting up real-time or near-real-time data processing for timely analytics and decision-making.
Balancing costs related to implementation, computing power, and storage requirements.
Acquiring or developing the necessary skill set among staff for effective operation and management.
Establishing robust data governance practices, including access, quality control, retention, and deletion policies.
Providing ongoing technical support and maintenance to ensure smooth operation.
Managing user adoption and change from existing systems to a new, integrated setup.
We built an operational data lake as a centralised repository to capture data from all relevant legacy systems that generate data. On top of that DataBricks was integrated to allow data scientists and business intelligence analysts build their bronze - silver - gold datasets. This allowed timely use of cleaned and structured datasets in operational reporting, which was the primary business need to be addressed.
Set up and configured the necessary infrastructure for the data lake.
Integrated various legacy systems with the data lake to establish continuous data flow.
Cleaned and transformed ingested data to ensure quality and usability.
Implemented Databricks, configuring it for optimal performance and connectivity to the data lake.
Structured data into bronze, silver, and gold datasets for different analytical needs.
DataBricks team provided the initiative and trained staff, including data scientists and analysts, on using the new system.
Conducted rigorous testing for data integrity and system performance.
Implemented security measures like access controls.
Managed change effectively to facilitate smooth transition and user adoption of the new system.
As a result of this engagement, Citco as a company gained new capabilities in data management, access to data, scalability & real time use of data to drive decision making process. It became easier to utilise data sources and obtain reliable and accurate datasets, that in turn can be used for reporting or building advanced analytics and AI driven tools. Here is a breakdown of results that we achieved:
Streamlined data management with reduced inefficiencies in storing and processing diverse data.
Quicker and more effective data access and analysis, leading to timely decision-making.
Enhanced capabilities in advanced analytics and AI, enabling deeper insights and smarter strategies.
Improved scalability to meet growing data demands, supporting business growth.
Real-time data processing, enhancing operational effectiveness and timely decisions.
Cost savings through centralized data management, replacing multiple costly systems.
More consistent and reliable reporting, with a unified source of truth.
Accelerated development of data-driven products, boosting market responsiveness.