EY Global Delivery Services ( EY GDS) Data Governance Consultant Interview Questions, Process, and Tips

Data remediation is the process of identifying, correcting, and preventing data quality issues within an organization's data assets.

• Data remediation involves identifying incorrect, incomplete, or inconsistent data and taking steps to correct it.

• It may include data cleansing, data enrichment, data standardization, and data deduplication.

• Examples of data remediation tasks include removing duplicate records, updating outd...read more

Root cause analysis strategies are methods used to identify the underlying cause of a problem or issue.

• Identifying the problem or issue that needs to be addressed

• Collecting data and information related to the problem

• Analyzing the data to determine possible causes

• Using techniques such as the 5 Whys, Fishbone Diagram, or Pareto Analysis

• Developing and implementing solutions to address the root cause

Star schema is a data warehouse schema where a central fact table is connected to multiple dimension tables. Snowflake schema is a normalized form of star schema where dimension tables are further normalized into sub-dimension tables.

• Star schema has a central fact table connected to multiple dimension tables

• Snowflake schema is a normalized form of star schema with dimension tables further normalized into sub-dimension ...read more

Slowly changing dimensions are handled by using different types like Type 1, Type 2, or Type 3 depending on the requirements.

• Use Type 1 for overwriting existing data with new values

• Use Type 2 for creating new records for changes and maintaining history

• Use Type 3 for creating separate columns for different versions of data

• Implement effective date ranges to track changes over time

I have over 5 years of experience in implementing data governance frameworks, policies, and procedures.

• Implemented data governance policies and procedures to ensure data quality and compliance

• Developed data governance frameworks to establish roles, responsibilities, and processes

• Conducted data quality assessments and implemented data quality improvement initiatives

• Collaborated with cross-functional teams to align data