* Data Analysis: Proficiency in analyzing large datasets, identifying patterns, and extracting meaningful insights using tools like SQL, Excel, or other data analysis software. * Data Visualization: Ability to create visually appealing and informative dashboards, reports, and charts using data visualization tools such as Tableau. * Database Management: Knowledge of database concepts, including data modeling, data warehousing, and SQL querying to extract and manipulate data from relational databases. * Business Intelligence Tools: Familiarity with business intelligence tools like Cognos to develop and maintain reports, queries, and data cubes. * Data Mining: Knowledge of data mining techniques to discover patterns, correlations, and trends in large datasets. * Data Quality Assurance: Understanding of data quality concepts and experience in data cleansing, data profiling, and data validation to ensure accuracy and reliability of data. * Data Governance: Familiarity with data governance principles and practices to ensure data integrity, security, and compliance with regulations. * Programming Skills: Basic programming skills in languages like Python can be beneficial for automating tasks, building data pipelines, or developing custom analytics solutions.