Top Informatica Interview Questions (With Example Answers)

By Indeed Editorial Team

Updated February 10, 2021 | Published December 12, 2019

Updated February 10, 2021

Published December 12, 2019

Related: Top Interview Tips: Common Questions, Body Language & More

In this video, we dissect an entire job interview from start to finish. We analyze everything from common interview questions to etiquette and how to follow up.

If you’re interviewing to be a data scientist, data architect or developer, you might come across questions about an important tool in data management: Informatical Powercenter ETL/Data Integration. For companies that rely on data to stay competitive, Informatica software could be an essential part of the overall infrastructure. To stay ahead in a dynamic ecosystem for technology professionals, it could be a good idea to refresh your knowledge of Informatica and related systems. In this article, we list common Informatica interview questions and provide sample answers.

What is Informatica?

Informatica is a software company that specializes in data analysis and management. They offer solutions for ETL, data masking, data quality, data virtualization, replication and more. The most common suite of tools provided by Informatica is the Powercenter ETL/Data Integration. When people say “Informatica,” oftentimes they are referring to this specific tool and not the company.

Related: Learn About Being a Data Architect

What can you expect from Informatica interview questions?

Informatica interview questions are likely to come up when Informatica is an integral part of a company’s technology infrastructure. Questions about Informatica might apply to data-specific roles like data analyst or data architect, or broader roles like systems administrator or software developer. If you’re applying for a job that requires knowledge of Informatica as part of the job description, there’s a strong likelihood you will come across some of these common Informatica interview questions.

Informatica interview questions and example answers

Informatica interview questions are likely highly technical and will only make up a portion of the overall interview process. If you’re interviewing for a data architect position, for example, you can expect a mix of questions that test your knowledge of various systems like Informatica to analyze your behavior. However, since Informatica is a small part of the overall interview, you should expect questions about the tool to be focused on using it and your overall experience with the product.

With that in mind, consider using the STAR method for answering interview questions where possible. STAR stands for situation, task, action, and result. Below we are offering five sample interview questions and example answers, some of which apply the STAR technique so you can see how it’s done:

  • What’s the difference between source qualifier and filter transformation?

  • What is Lookup transformation and how do you use it

  • What is an ETL process?

  • What’s your experience with Informatica Powercenter ETL/data integration?

  • What types of caches are in Lookup feature?

What’s the difference between source qualifier and filter transformation?

On a surface level, this is a technical question that tests your knowledge of basic functions in Informatica. However, questions that ask you to tell the difference between two things allow you to show an in-depth understanding of more than one function as you compare and contrast the similarities and differences. That’s two times the opportunity to impress the interviewer in a single question.

Answering it astutely means providing a thoroughly thought-out, detailed answer that addresses the unique qualities of both functions. There are lots of opportunities for interviewers to ask you to highlight differences in an interview. Here are some of the things that you might be asked to compare and contrast:

  • Powercenter vs. Powermart

  • Connected ETL vs. unconnected ETL

  • Joiner vs. Lookup transformation

Example: “The source qualifier filters rows of data that it reads from a single source. It can filter row data from relational sources but has overall limitations. The benefit of using source qualifier is that it gives you a performance boost because it limits the rows of data that can be mapped. The Filter Transformation tool does not have limitations regarding the source system from which it can filter rows of data. It enhances performance by filtering out data that isn’t useful.”

Explain Lookup transformation. How do you use it?

This question asks for an answer in two parts. First, is a basic explanation of how to use Lookup transfer. One strategy to consider when explaining technical concepts is to avoid jargon and use clear, simple language. Every answer to a technical question like this is an opportunity to show you can explain the subject matter in a way that’s easily relatable for a lot of people.

Once you’ve explained a Lookup transformation, consider how you’ve used it, personally. Any question that asks how you do something gives you the chance to talk about your experience. The example below uses this STAR method of answering interview questions.

Example: “A Lookup transformation is a processing Informatica used to find and return data from a file, relational table or other sources. There are four types of Lookup transformations: relational or flat file, pipeline, connected or unconnected, and cached or uncached.

In my experience with Lookup transformation, I was tasked with finding the dates of all the most recent order numbers for existing customers. I used a connected Lookup transformation, which is one that is already connected to a data source, and was able to quickly import the dates I was looking for within a few steps, which included some mapping on my part. The result allowed stakeholders to see which customers needed to be part of an upcoming email blast.”

What is an ETL process?

This basic question tests your knowledge of a foundational concept in data processing: ETL. To answer this question, use clear and concise language to define ETL, including both an explanation of what the acronym stands for and its essential functions.

Example: “ETL stands for Extract, Transform and Load. It’s a process in which data is first extracted from a specific source, transformed into a format that can be included in the company’s data infrastructure and then loaded into the data warehouse, where it will await use by data analysts and scientists within the company.”

Related: Technical Skills: Definitions and Examples

What’s your experience with Informatica Powercenter ETL/Data Integration?

This question allows you to describe your experience level. If you get a question asking you to outline your experience, give a brief overview of the depth of your experience, including details like how many years you’ve used the software and in what roles. Then offer a specific example of how you used the software to solve a problem.

Example: “In my previous work as a data scientist, I was familiar with Powercenter ETL/Data Integration. I used several features over my five-year tenure there. In one example, my team was tasked with extracting data from thousands of flat files. I decided a bulk-processing session in real-time would be the right process to meet the needs of the organization. We configured Powercenter to processes continuously until relevant data had been extracted from all the files. That saved us time that was then spent providing a thorough analysis instead of working through data extractions.”

What types of caches are in Lookup feature?

If a particular feature of Informatica is vital to the role you will be working in, you may get one or multiple feature-specific questions. In this case, the interviewer is asking you to list caches, but many questions like this could be present in an Informatica interview, such as:

  • What are the steps of an ETL process?

  • What are OLTP and OLAP?

  • What are the schemas in data modeling?

Example: “There are two types of caches in the Lookup feature: cached and uncached lookups. A cached lookup is one where the original lookup was configured to create a cache, and all subsequent lookups save time and resources by returning to the cache for data instead of the source. An uncached lookup returns to the source file and is more resource-intensive.”

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