In the world of investment management, data plays a crucial role in making informed decisions and achieving optimal results.
As the underlying source of truth for all your outputs, it is essential that the data is accurate and compliant at all times.
From data loading to data integrity, there are commonly encountered issues that have a significant impact on the accuracy and reliability of both reporting (e.g. client reports, fund factsheets, regulatory reports, sales reports) and digital collateral such as fund centres, fund product pages or client portals.
In this article, I will explore the top ten data issues that we encounter when setting up data models and how to tackle them effectively.
1
Use flat files instead of report-based files
Flat files (e.g., CSV, JSON, XML, XLSX) are better for data loading than report-based formats. Flat files are machine-readable and easier to fix, reducing complexity and operational costs.
2
Check for missing data early
Always verify the data source early to ensure all necessary data is available to avoid missing data in documents or reports, which may delay analysis and impact decision-making. This may seem obvious in theory, but in practice this is a very common roadblock.
3
Standardise naming conventions
Use a standardised regex (regular expressions) naming system to ensure ETL (Extract, Transform, Load) tools can reliably locate and process data, reducing errors and confusion. Consistent file and sheet names are essential for smooth data processing.
4
Ensure consistent value formats
Formatting mismatches (like inconsistent dates or symbols) can cause data rejections, leading to delays and inaccuracies. The effort required to then investigate, identify and rectify offending records is costly, often resulting in report delivery delays or even the delivery of inaccurate reports. Implement validation checks to catch these issues early.
5
Validate data for blank or NULL values
Check for missing values before processing to prevent validation errors and ensure all essential values are provided for aggregation and analysis.
6
Streamline new fund launches
Set up fund entities in the system first and conduct a UAT (User Acceptance Testing)soft launch to identify data gaps, ensuring a smoother production rollout.
7
Communicate primary key changes
Assess the impact of primary key changes and keep teams informed to maintain data consistency across all datasets.
8
Manage data dependencies and integrity
Investment data is complex, often involving dependencies and mappings that must be considered before loading it into the system. For instance, fund and benchmark data might be supplied separately but stored as a unified dataset in the system. It is therefore important to keep all datasets and caches up-to-date to prevent errors due to dependency and mapping issues when loading data.
9
Retain context during personnel changes
When key personnel in the team move on, valuable context about data sources, mappings, and other important details can be lost. Document data mappings, schedules, and handling procedures to safeguard knowledge and ensure seamless transitions when staff changes occur.
10
Eliminate duplicate data records regularly
Implement deduplication processes to keep data clean and reliable, enhancing decision-making accuracy.
By addressing these challenges with best practices and solutions, investment managers can enhance operational efficiency, reduce the risk of errors, and deliver more accurate and timely reports to their clients. Ultimately, the successful management of these data issues empowers investment managers to provide their clients with accurate and dependable reports, enabling more informed investment decisions and better outcomes in the ever-evolving world of investment management.
Dayaan Abdul
Data Delivery Manager
With over 7 years of diverse experience within our organisation, Dayaan serves as an accomplished Data Delivery Manager at Kurtosys, leading a team of data engineers. Prior to joining us, Dayaan devoted 8 years to various roles in the realm of data.
We can help you with your data requirements
Whether you use data files, APIs or data warehouses like Snowflake, you can efficiently manage and utilise your investment data within the Kurtosys platform.
If you are ready to automate your reporting needs, we have the right team to advise on your data requirements. Please reach out to us to find out more.
