ETL refers to the overall process of moving data from many sources to a centralized data warehouse. These three database functionalities have been combined into a single application that allows you to extract data from one database and store it in another.
When applying for a position with ETL responsibilities, it may be advantageous to be familiar with the types of questions an interviewer may ask and the best ways to respond. This article will cover the top 25 Scenario-Based ETL interview questions along with sample answers to assist you in preparing for your upcoming interview.
1. Explain What ETL Is In Your Own Words.
The Extract, Transfer, and Load (ETL) process is essential for data engineers because it allows them to collect and change data into a valid format. ETL provides developers with an interface for designing source-to-target mappings, job management parameters, and transformations.
Data Integration Process comprises three fundamental components, which include the following:
- Extraction: Transfer data from an external source to the database of the warehouse pre-processor.
- Transformation: The Transform data job permits data point-to-point generation, modification, and conversion.
- Loading: The loading procedure moves data into the target system.
2. Why Do You Believe ETL Testing Is Useful?
One of the most significant advantages of ETL tests is that this procedure maintains data quality. It achieves this by examining records for truncated or missing data throughout the load process from the source system to the data warehouse. In my previous organization, this was incredibly useful for transferring significant amounts of data into target systems. The data transfer would be reliable and done within rigorous deadlines, leading to more simplified methods for maintaining client data.
3. What Steps Are Involved In The ETL Testing Process?
When conducting ETL testing, I adhere to the steps below:
- Performing a Requirement Analysis: I take the time to comprehend the business’s organizational structure and requirements in this step.
- Validation and Estimation of Tests: I perform a time and skill estimation at this stage.
- Test Environment preparation and design: Validation and test estimation are what we use to determine the value. In this stage, I plan the ETL environment based on the inputs used in the test estimation and then work accordingly.
- Preparation and Execution of Test Data I prepare and execute data according to the test’s specifications.
- After the test run, I create a summary report to draw conclusions and make adjustments.
4. Can ETL Be Used For Data Warehousing? If Yes, Then How?
Typically, we can utilize ETL in Data Warehousing. The user retrieves historical and current data for the data warehouse development. The data warehouse contains both transactional and historical data. The Data Source of a data warehouse may vary. We must retrieve data from many systems and load it into a single destination system, commonly known as a data warehouse.
5. What Are The Three Layers Of An ETL Cycle’s Architecture?
The three ETL tiers consist of the following:
- Staging Layer: The staging layer holds data extracted from various data source systems.
- Access Layer: End-users retrieve data for analytical reports via the Access Layer.
- Data Integration Layer: The integration layer transforms and transports data from the staging layer to a database. The database organizes its data into hierarchical categories, sometimes known as dimensions, facts, and aggregate facts. A schema combines fact and dimension tables in a data warehouse system.
6. What Are The Various Sorts Of Facts Utilized In ETL?
Facts are quantifiable facts about a company, such as account balances, number of employees, and expenditures.
They are contained in a table of facts. There are three distinct classifications of facts:
- Additive: Not all dimensions in a fact table can be totaled for semi-additive facts, such as a headcount.
- Sales figures, for example, can be totaled over all dimensions of the fact table.
- Non-additive facts, such as percentages, cannot be computed to any extent in a fact table.
7. What Do You Know About The Different Kinds Of ETL Testing?
There are a variety of ETL testing methodologies, each of which serves a distinct role at various stages of the ETL process. The following are some of the most prevalent types of ETL testing that I am aware of:
- Performance evaluation: The loading procedure is examined to ensure that it occurs within the anticipated time constraints.
- Testing data transformation: Data in the target system is examined to ensure that it has been transformed correctly per business requirements.
- Production validation: Data in the target system are compared to their sources to ensure validity.
- Source-to-target count testing: The number of loaded records in the data warehouse is compared to the predicted number of forms.
8. What Do You Consider An Operational Data Store To Be?
An ODS is a central database that provides a snapshot of the most recent business data from different sources. The data is for processing activities such as real-time analysis and operational reporting. It provides corporate intelligence tools for strategic decision-making and contains the most current information.
In contrast to ETL systems, an operational data store receives unprocessed data from production systems and stores it in its native format. It is unnecessary to convert the data before it can be studied or used to make operational decisions for a firm.
9. What, In Your Opinion, Is The Primary Difference Between ETL And ELT?
ELT changes data within the data warehouse, whereas ETL alters data before loading it into the target system. ETL is an older method that is excellent for complex transformations on smaller data sets. It is also advantageous for those that prioritize data security. ELT, on the other hand, is a more recent technology that offers analysts greater flexibility and is ideal for processing both structured and unstructured data. Your choice between ETL and ELT will impact your data’s storage, analysis, and processing.
10. How Would You Describe A Staging Area In ETL?
A landing zone is another name for a staging area, a temporary storage location for data coming from various sources. Before being put into the data warehouse or data mart, all data should be made available in a single place, making the staging area an essential component. It stores the data and cleans it before forwarding it to the database utilized for its final destination.
11. When Is The Staging Area Required In The ETL Process?
The staging area is between the data sources and the data warehouse/data marts systems. It is where we temporarily keep data throughout the data integration process. Area data is cleansed and checked for duplication in the staging phase. The staging area provides numerous advantages, but its primary purpose is for utilization. It enhances productivity, guarantees data integrity, and promotes data quality processes.
12. What Are The Top ETL Features That You Would Recommend Our Business Utilize?
A reliable ETL tool makes the data integration process more effective and user-friendly. Among the most useful ETL functionalities are the following:
- Automated code creation to eliminate human error risks and accelerate the development
- User-friendly interface to facilitate navigating
- Advanced debugging tools that minimize disruptions to data flows.
- Compatibility with the cloud, enabling increased flexibility and improved management of big datasets.
- Integrations from third parties with ERP platforms and BI tools
13. In ETL, What Is The Difference Between Connected And Unconnected Lookups?
The mapping technique known as connected lookup can return multiple values at once. In addition to producing a value, we can couple it with another transformation. Unconnected lookup is a type of lookup utilized in situations where the lookup is not available in the main flow and only provides one output. It is also impossible to connect it to another transformation, but we can reuse it.
14. How Does Impact Analysis Function Within The ETL System?
Typically, impact analysis examines the information associated with an object and determines what is impacted by a change in its content or structure. Changes to data-staging objects may jeopardize crucial data warehouse loading activities.
Permitting ad hoc adjustments to data staging objects is detrimental to your project’s success. Before making any changes to a table generated in the staging area, an effect study must be performed. Most ETL tool manufacturers promote impact analysis capabilities. Still, this capability is typically overlooked during the ETL object proof-of-concept process because it is a back-office activity that is truly relevant once the data warehouse is up and operating and growing.
15. Kindly Explain How ETL Testing Is Applied To The Management Of Third-Party Data.
Diverse vendors develop a variety of software for huge organizations. In consequence, only some providers are accountable for the entire process. Imagine a company where one department handles billing, and another handles client relationship management. CRMs can now receive data feeds from other firms, for instance, if a CRM requires billing information from another company. We may utilize ETL to load data from the feed.
16. What Are The Steps That You Follow When Choosing The ETL Process Tools?
It is a challenging process to select ETL solutions, as we must consider various project-specific aspects.
The following are some of the factors that I examine when selecting ETL tools:
- Data Interconnection: To select an ETL tool, I consider how it should interface with any data source, regardless of its origin.
- Performance: To transfer and modify the data demands considerable processing power. I now evaluate the performance component.
- Transformational Modularity: Data Merging, Matching, and Modification are crucial. All of these Merging, Matching, and Changing procedures, as well as other transformation packages, should be supported by ETL tools. It enables drag-and-drop modifications to the data throughout the transformation step.
- Data Quality: I only utilize the data when they are accurate and consistent.
- Flexible data action option: When the ETL is complete, I ensure that it is compatible with both existing and incoming data.
- Committed ETL vendor: We deal with the organization’s data during the ETL process. Therefore, I must select a provider with industry expertise and whose help will be advantageous.
17. In The Context Of An ETL System, What Exactly Is Data Profiling?
To construct an ETL system, one must first do data profiling, which is a comprehensive analysis of a data source’s quality, breadth, and context. At one extreme, a clean data source that has been meticulously maintained before it arrives at the data warehouse requires fewer transformations and human involvement to load straight into final dimension tables and fact tables. It is because such a data source can load directly into these tables.
18. What Role Does ETL Testing Play In The Big Picture?
ETL testing has several substantial benefits, including the following:
- Ensure data is transmitted quickly and effectively from one system to another.
- During ETL operations, ETL testing can also discover and prevent data quality issues such as duplicate data and data loss.
- Ensures the ETL process is unimpeded and operating smoothly.
- It ensures that we implement all data per customer requirements and guarantees accurate output.
- To ensure a flawless and error-free transfer.
19. Describe The Role Of ETL In Data Migration Efforts.
ETL tools are often used in data migration initiatives. The data must be migrated from Source to Target, for instance, if the firm previously maintained the data in Oracle 10g and now want to switch to a SQL Server cloud database. ETL tools might be of great assistance for this type of conversion. The user must devote a significant amount of time to writing ETL code. Therefore, ETL tools are highly useful because they make coding easier than P-SQL or T-SQL. Therefore, ETL is a highly beneficial procedure for data migration operations.
20. Explain What A Bus Schema Is In Your Own Words.
The Bus Schema is mostly responsible for dimension identification, an essential aspect of ETL. A BUS schema consists of a collection of validated dimensions and uniform definitions. A bus scheme manages dimension identification across all organizations. Similar to identifying conforming dimensions, the bus schema identifies the common dimensions and facts across an organization’s data marts. ETL provides information in a uniform format with accurate dimensions using the Bus schema.
21. When It Comes To Data Mining, What Part Does ETL Play?
The Extract, Transform, and Load (ETL) step of the data mining process is an essential early step. Following discovering data sources and formulating business objectives, we carry out ETL operations to consolidate all previous data into a unified database management system. Using BI tools, data analysis and modeling may now occur. We can then draw judgment about the business decisions from the data.
22. What Do You Think Are The Various Stages Of Data Mining?
A step of data mining is a procedure for going through large amounts of information to locate relevant facts.
- Exploration: Exploration requires exploration and data preparation. The objective of the exploration phase is to identify and characterize significant factors.
- Pattern Identification: The significant action at this stage is searching for patterns and selecting the one that permits the most excellent forecast.
- Deployment stage: This stage can only be reached once a consistent pattern is identified in stage 2, which is highly predictive. We can use the pattern we discover in stage 2 to determine whether the desired effect has been attained.
23. What Exactly Is Meant By “Data Cleaning”?
Data cleaning is often referred to as data cleansing. It removes incomplete, duplicate, corrupt, or inaccurate data from a dataset. As the necessity to combine multiple data sources, such as in data warehouses or federated database systems, becomes increasingly evident, the need for data cleansing grows substantially because the particular steps of a data cleaning process will vary based on the dataset, building a template guarantees that the process is followed correctly and consistently.
24. What Is Partitioning In ETL, And What Type Is It?
Partitioning is the technique of splitting a data storage region to increase performance. It is useful for organizing your work. Having all your data in a single location without structure makes it harder for digital technologies to locate and evaluate it. When your data warehouse is partitioned, finding and analyzing data is simpler and quicker. The following factors make partitioning crucial:
- Facilitate data management and improve efficiency.
- Ensures that all system needs are in harmony.
- Backups and recoveries are simplified.
- Streamlines administration and optimizes hardware performance.
25. What’s The Distinction Between Olap And ETL Tools?
ETL is intended for data extraction, transformation, and aggregation. The ETL tool’s output serves as the input for the OLAP tool. The initial step in data warehousing is ETL.
It is time-consuming for the data warehouse to generate cross-tab reports from source tables. These tables are turned into cubes for efficiency and stored on an OLAP server. In contrast, OLAP technologies are primarily employed for reporting purposes. It puts the collected data into the OLAP repository. Then it makes the necessary modifications to provide an end-user-accessible report.
Our article about the top 25 Scenario-based ETL interview questions and answers for 2023 is complete. As you can see from the preceding questions, ETL questions are complex. They require knowledge to answer correctly. Therefore, prepare for your interview questions and answers to acquire the ETL-required position. I hope these ETL interview questions and answers will assist you in preparing for and passing your interviews.