Position: Data Analyst
Category: Support
English level: upper
Years of experience: 5


In my role as a Data Associate at IndexBoard, I was responsible for ensuring the accuracy and quality of data used for various purposes, including analytics and reporting. The project aimed to clean and improve the quality of our data assets.
As a key member of the data team, I played a critical role in data cleansing, data validation, and quality control processes.
Tasks Completed: Conducted data cleansing tasks to identify and rectify inaccuracies, inconsistencies, and duplicate records in our databases.
Developed and implemented data validation checks to ensure incoming data met quality standards.
Collaborated with cross-functional teams to define data quality requirements and establish data governance best practices.
Created automated scripts in Python to streamline data validation and cleansing processes.
Maintained documentation on data quality procedures and provided training to new team members.
Technologies Used: Python for scripting and automation, SQL for data querying and validation, and data quality management tools.
Challenges Faced: Dealing with large volumes of data from various sources and maintaining data quality standards while meeting tight deadlines were significant challenges. Additionally, ensuring data security and compliance with regulations was crucial.
After some time the results were seen. The data cleansing and quality improvement efforts resulted in a 30% reduction in data errors and improved data accuracy. This, in turn, led to more reliable analytics and reporting, contributing to better decision-making across the organisation.