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What are Common Data Warehouse Interview Questions?

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  • Written By: Patrick Roland
  • Edited By: R. Halprin
  • Last Modified Date: 05 November 2016
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Data warehousing is the technological act of storing massive amounts of data for use in running reports. Many different industries utilize this technology and warehouses are often set up similarly. Because warehousing is similar across the board, data warehouse interview questions are very direct. Interviewees can expect to be quizzed about a general understanding of data warehousing, level of expertise, understanding of various processes, and questions that unveil the interviewee's personality.

Attaining a better understanding of an interviewee's general warehousing knowledge is a big portion of data warehouse interview questions. These questions will involve general terms and practices to ensure the person being interviewed has the appropriate level of experience to handle the job. Interviewers often ask what the difference is between online analytical processing (OLAP) and online transaction processing (OLTP); these two processes are key elements of warehousing data. Another general knowledge question is to ask what a lookup table is used for or what an operational database store (ODS) does.

Data warehousing is a complex process; data warehouse interview questions frequently probe the interviewee to determine what level of complexity they understand. A question asking why data and dimensional modeling are important is common because these processes are essential to proper informational storage. Asking why an OLTP database design is not a good idea is another complicated question designed to test the interviewee's knowledge of the entire process.

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Since data mining is a major part of warehousing, an interviewee should expect to be asked many data warehouse interview questions on this process. Asking about the advantages of data mining over more traditional methods is one likely question. Interviewers are also frequently curious about specific processes involving data mining. A prospective job candidate might have to give an example of when data mining was used in a work situation and the result of the project. Interview questions can also be turned around; instead of asking for a positive experience, a candidate might be asked what her or she dislikes about mining and how it could be changed.

Personal information is another likely topic of data warehouse interview questions. In most situations, these will not involve questions about work and family life, but rather how an interviewee's personality fits with the team. Questions such how the individual handles stress and pressure are common and usually require examples. Asking the interviewee to list strong skills and weaknesses is another common personality related question.

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MrMoody
Post 4

@nony - I’m surprised that ETL data warehouse questions are not thrown into the mix. ETL is extract, transform and load. It’s the process from beginning to end of getting the data, massaging it and putting it in the warehouse for user consumption.

I can’t say I know how the process works. I am sure there are many pieces to the puzzle. But I would certainly expect a data warehouse job candidate to get asked about it.

nony
Post 3

@miriam98 - Well I can tell you what a lookup table is. I don’t think that concept is unique to date warehousing although it might have a certain application in that context. A lookup table is basically a reference table. We use them a lot in Microsoft Access.

miriam98
Post 2

@NathanG - It’s seems that the answers to most of these IT interview questions could easily be looked up online. They don’t prove anything by themselves.

What matters is how you used a certain concept in your work, not how well you know the buzz words. I can’t emphasize this point too much.

I’ve come across too many IT job candidates where I work who can roll out the latest catch phrases but when we ask for concrete real life examples, they give us that dear in the headlights look.

Experience is what matters, whether the position is for data warehouse or programmer or analyst. Everything is else is mere book learning.

NathanG
Post 1

I’m not a data warehouse architect myself, but I have worked in that environment. I mainly worked in the reporting section so I didn’t have to mess with distinctions about OLAP vs OLTP (although I know what they are).

The biggest concept that we encountered are what are called cubes. Cubes in data warehousing are basically three dimensional models of data, similar to pivot tables in Excel except that the data is more than two dimensions like I said.

The purpose of the cubes in the dimensional data warehouse is so that people can track data as it changes over a time interval in most cases.

For example we may want to know per store sales by month and by year. That’s three categories right there. A cube will let you handle that. I would expect that a data warehouse person would be asked about this in their interview.

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