10+ TCS AST Consultant Interview Questions and Answers for Freshers

Data sparsity refers to the situation where a large portion of data is missing or empty. To handle it, techniques like data imputation or interpolation can be used. Dollar tables can be avoided in ODI loading by using appropriate mappings and transformations.

• Data sparsity occurs when there are missing or empty values in a dataset.

• To handle data sparsity, techniques like data imputation or interpolation can be used to fill in the missing values.

• Data imputation involves estimat...read more

To call two load plans in parallel and make them wait if needed, use a parallel step and a wait step.

• Create a parallel step in the load plan

• Add the two load plans as child steps to the parallel step

• Create a wait step after the parallel step

• Set the wait step to wait for completion of the parallel step

• Adjust the wait time as needed

Direct path read and write is a method of reading and writing data in Oracle without using buffer cache.

• Direct path read and write is faster than traditional read and write methods.

• It is useful for large data sets that do not fit in buffer cache.

• Direct path read and write bypasses buffer cache, reducing memory usage.

• However, it can cause increased I/O and CPU usage.

• Direct path write is commonly used for bulk inserts, while direct path read is used for full table scans.

• Direct ...read more

ODI file wait is a feature that allows ODI to wait for a file to be available before proceeding with the execution of a task.

• ODI file wait is configured in the ODI topology manager

• It can be used in scenarios where a file needs to be processed before continuing with the task

• ODI file wait can be set to wait for a specific file name or a file pattern

• It can also be configured to wait for a specific amount of time before timing out

• Once the file is available, ODI will proceed with ...read more

Complex files in ODI can be handled by using various techniques.

• Use ODI's built-in file handling capabilities

• Use custom Java code to handle complex file formats

• Use third-party tools like Apache Nifi or Talend to preprocess the files

• Use ODI's knowledge modules to transform the data into a more manageable format

• Use ODI's parallel processing capabilities to speed up the processing of large files

Large files can be loaded in ODI using various techniques such as partitioning, chunking, and parallel processing.

• Use partitioning to divide the large file into smaller chunks and load them in parallel

• Chunking involves breaking the large file into smaller pieces and loading them sequentially

• Parallel processing can be used to load multiple chunks of the file simultaneously

• ODI also supports external tables, which can be used to load data from large files stored outside the data...read more

Consistent JKM ensures uniformity in the execution of tasks and processes.

• JKM stands for Job Knowledge Management

• Consistent JKM involves documenting and sharing best practices

• It helps in reducing errors and improving efficiency

• For example, a consistent JKM approach in software development would involve using the same coding standards and tools across the team

Pivot command in SQL is used to transform rows into columns. Running total is a cumulative sum of values.

• Pivot command is used to aggregate data and display it in a more readable format

• Running total is calculated by adding the current value to the previous total

• Example of pivot command: SELECT * FROM table_name PIVOT (SUM(column_name) FOR pivot_column IN (value1, value2, value3))

• Example of running total: SELECT column_name, SUM(column_name) OVER (ORDER BY column_name) AS runn...read more

Different select queries have different purposes and syntax.

• SELECT retrieves data from one or more tables

• DISTINCT removes duplicates from the result set

• WHERE filters the result set based on a condition

• GROUP BY groups the result set by one or more columns

• HAVING filters the result set based on a condition after grouping

• ORDER BY sorts the result set by one or more columns

• LIMIT limits the number of rows returned

• JOIN combines rows from two or more tables based on a related column

Collection in PL SQL is a data structure that can hold multiple values of the same data type.

• Collections can be nested within each other.

• PL/SQL provides three types of collections: associative arrays, nested tables, and VARRAYs.

• Collections can be used to pass multiple values to a stored procedure or function.

• Collections can be used to simplify SQL statements by allowing multiple rows to be returned as a single result set.