In SQL, Trigger acts a stored procedure which gets invoked when a triggering event occurs in a database. These triggering events can be caused due to insertion, deletion or updating of any row or column in a particular table. For example, trigger can be invoked when a NEW row is added or deleted from a table or any row is updated. The syntax to create a tigger in SQL is as below.

Syntax:

Explanation: 

1. Trigger will be created with a name as [trigger_name] whose EXECUTION is determined by [before | after].

2. {insert | update | delete} are examples of DML OPERATIONS.

3. [table_name] is the table which is associated with trigger.

4. [for each row] determines the rows for which trigger will be executed.

5. [trigger_body] determines the operations that needs to be performed after trigger is invoked.

Description: Data Engineering is very important term used in big data. It is the PROCESS of transforming the raw entity of data (data generated from various sources) into helpful information that can be used for various purposes. Data Engineering has become one of the most popular career choices today.

According to a study, it has been expected that the data engineering services and global big data will grow from USD 29.50 billion that was in 2017 to USD 77.37 billion by 2023, at a Compound Annual Growth Rate (CAGR) of 17.6% during the forecast period. 2017 is taken as the base year for this study, and the forecast period taken here is 2018–2023. Data engineer has to take up a lot of responsibilities daily, from collecting to analyzing data with the help of many tools.

If you are interested in data engineering and looking for top interview questions and answers in the field of data engineering, then these above beginner and advance level questions are best for you which keep into consideration various skills of data engineering like Python, Big data, HADOOP, SQL, Database, etc. Data analyst and data engineer jobs are increasing at a faster rate in the market and market has a lot opportunities for both freshers and experienced engineers across the world. Good conceptual knowledge and hold on logics will help you crack interviews in many reputed companies. The above questions are designed to help understand the concepts of data engineering deeply. We have tried to cover almost every topic of data engineering.

If you go through the above-mentioned, you will easily find questions from beginner to an advanced level according to your level of expertise. These questions will help you give an extra edge over the other applicants who will apply for data engineering jobs. If you want to study data engineering topics deeply, you can enroll in big data courses on KnowledgeHut that can help you to boost your basic and advanced skills.

Best of Luck.