Bank of Maharashtra IT (Data Analytics) Interview Questions, Process, and Tips

A data mart is a subset of a larger data warehouse that is designed to serve a specific business unit or department.

• Contains a subset of data from a larger data warehouse

• Designed to serve a specific business unit or department

• Provides a more focused view of data for analysis

• Can be created faster and at a lower cost than a full data warehouse

• Examples: Sales data mart, Marketing data mart

OLTP is for transaction processing while OLAP is for data analysis.

• OLTP is used for day-to-day operations and focuses on processing transactions in real-time.

• OLAP is used for data analysis and focuses on querying large amounts of data to gain insights.

• OLTP databases are normalized while OLAP databases are denormalized.

• OLTP databases are optimized for write operations while OLAP databases are optimized for read operatio...read more

As a data analyst, I can contribute to the Bank's business by providing insights and recommendations based on data analysis.

• I can help identify patterns and trends in customer behavior to improve marketing strategies.

• I can analyze financial data to identify areas for cost savings and revenue growth.

• I can develop predictive models to forecast future trends and inform business decisions.

• I can create dashboards and report...read more

Data security can be maintained by implementing access controls, encryption, regular backups, and monitoring.

• Implement access controls to restrict unauthorized access to data

• Use encryption to protect data in transit and at rest

• Regularly backup data to prevent loss in case of a security breach

• Monitor data access and usage to detect and prevent unauthorized activity

• Train employees on data security best practices to preve

Data analytics in banking can be used for fraud detection, customer segmentation, risk assessment, and personalized marketing.

• Fraud detection: Analyzing transaction patterns to identify suspicious activities and prevent fraudulent transactions.

• Customer segmentation: Analyzing customer data to group customers based on their behavior, preferences, and demographics for targeted marketing campaigns.

• Risk assessment: Analyzi...read more