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When it comes to the interview part there are a lot of questions which are generally asked. The data analyst technical interview questions differ from one angle to another. I have sorted from a bundle of questions and will share with you some of the most important data analyst technical interview quRead more
When it comes to the interview part there are a lot of questions which are generally asked. The data analyst technical interview questions differ from one angle to another. I have sorted from a bundle of questions and will share with you some of the most important data analyst technical interview questions. you will get a rough idea of what type of data analyst technical interview questions will be asked for your interview.
1. Name the best tool for data analysis? Candidates with good practical knowledge are the only ones to excel in this question. So make sure that you have different practice tools and analytics questions for your analyst interview and data analyst behavioral interview questions. Well! here some of the best tools for data analysis KNIME, Solver, NodeXL etc.
2.What are the different data validation methods used by data analysts? One of the frequently asked data analyst technical interview questions
Field Level Validation- It helps to correct the errors as you proceed
Form Level Validation- It checks the entire data entry form at once, validates all the fields in it, and highlights the errors so that the user can correct it.
Data Saving Validation- Usually, it is done when multiple data entry forms must be validated.
Search Criteria Validation- The main idea of this validation method is to ensure that the user’s search queries can return to the most relevant results.
3. What are the key requirements for becoming a Data Analyst? This is one of the most important data analyst technical interview questions.
You should have substantial technical knowledge in fields like database design, data mining, and segmentation techniques.
4. What is the meaning of data cleansing? Data cleansing basically means to the process of detecting and removing errors from the data to improve data quality. Although containing valuable information, an unstructured database is hard to move through and find valuable information. Data cleansing simplifies this process by modifying unorganized data to keep it intact, precise, and useful.
5. What is time series analysis? This brings the structure to how the analysts record the data, instead of going ahead observing the data points randomly, they observe data over set intervals of time. It is used for nonstationary data, data that is dynamic and constantly moving. It has applications in various industries such as finance, retail, economics, etc.
These are some of the frequently asked data analyst technical interview questions.
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