Data Analyst Interview Questions : Data Analysts deliver value to their companies by taking data, using it to answer questions, and communicating the results to help make business decisions. Common tasks done by data analysts include data cleaning, performing analysis and creating data visualizations. Companies in nearly every industry hire data analyst, from healthcare providers to retail stores to fast food chains. The insights that data analysts bring to an organization can be valuable to employers who want to know more about the needs of their consumer or end user. Regardless of which industry they work in, data analysts can expect to spend their time developing systems for collecting data and compiling their findings into reports that can help improve their company.
The main tasks of data analysts are to collect, manipulate and analyze data. They prepare reports, which may be in the form of visualizations such as graphs, charts and dashboards, detailing the significant results they deduced. Data analysts guard and protect the organization’s data, making sure that the data repositories produce consistent, reusable data. They go about doing all these tasks in a technical and systematic way, using the standard formulas and methods as are common in the industry and relevant to the current data. For example, data analysts might perform basic statistics such as variations and averages. They also might predict yields or create and interpret histograms. They use standard methods in all stages including collection, analysis and reporting.
Data analysis is a highly transferable skill and can open the door to many interesting jobs across the private and public sector, from banks to utility companies, and councils to the police.
These are some common tools in a data analyst’s tool belt:
- Excel
- SQL
- Google Analytics
- Visual Website Optimizer
- Google Tag Manager
- Tableau
- Google AdWords and more.
Read :Datascience Interview Questions and Answers Read :Machine Learning Interview Questions and AnswersWhat are responsibilities of Data Analyst?
What are the skills needed to become a data analyst?
What are the various steps in an analytics project?
In how many ways can we perform Data Cleansing?
Can you define Data Profiling?
Can you define logistic regression?
How will you handle the QA process when developing a predictive model to forecast customer churn?
Can you define K-mean Algorithm?
What are the important steps in data validation process?
What are the general problems in the work of Data Analyst?
What are the missing patterns that are generally observed while working on a data sheet?
What is the criteria for a good data model?
What are hash table collisions? How is it avoided?
Can you define time series analysis?
Can you define correlogram analysis?
Can you define collaborative filtering?
How to deal the multi-source problems?
Can you explain Design of experiments?
What is KNN imputation method?
What is regression imputation?
What are some best tools that can be useful for data-analysis?