Infosys Technology Analyst Interview Questions, Process, and Tips for Experienced

I am a technology analyst with a strong background in data analysis and software development.

• I have a Bachelor's degree in Computer Science from XYZ University

• I have 5 years of experience working as a technology analyst at ABC Company

• I specialize in data visualization tools such as Tableau and Power BI

• I have led successful projects in implementing new software solutions for clients

Analytic functions in SQL are used to perform calculations across a set of rows related to the current row.

• Common analytic functions include ROW_NUMBER, RANK, DENSE_RANK, LEAD, and LAG.

• They can be used to calculate running totals, moving averages, and identify duplicates in a dataset.

• Analytic functions are typically used with the OVER() clause to define the window of rows to be used in the calculation.

Rank assigns unique ranks to each distinct value, while dense rank assigns consecutive ranks to each distinct value.

• Rank leaves gaps between ranks if there are ties, while dense rank does not

• Rank function is used to assign a unique rank to each distinct row, while dense rank function is used to assign consecutive ranks to each distinct row

• Example: If we have values 10, 20, 20, 30 - Rank would assign ranks as 1, 2, 2, 4...read more

SCD 2 is a type of slowly changing dimension in data warehousing, and can be implemented in DataStage using various techniques.

• SCD 2 stands for Slowly Changing Dimension Type 2, which tracks historical changes in data over time.

• In DataStage, SCD 2 can be implemented using the Change Data Capture stage or custom SQL queries.

• To implement SCD 2 in DataStage, you need to identify the key columns for tracking changes, defin...read more

To improve performance in Datastage, optimize job design, use efficient coding practices, utilize parallel processing, and monitor job performance.

• Optimize job design by reducing unnecessary stages and transformations

• Use efficient coding practices such as avoiding unnecessary data reads and writes

• Utilize parallel processing to take advantage of multiple CPU cores

• Monitor job performance using Datastage Director or other