
Data Analyst interview questions for Wipro are as follows :Â
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A Data Analyst collects, processes, and performs statistical analysis of data to help companies make informed decisions. The role involves interpreting data, analyzing trends, generating reports, and presenting findings using visualization tools.
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Common tools include:
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I handle missing data by:
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SQL (Structured Query Language) is used to query, manage, and manipulate data in relational databases. Data Analysts use SQL to retrieve and aggregate data, perform joins, and filter datasets for analysis.
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Outliers are data points that significantly differ from others. Handling outliers involves:
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Data cleaning involves correcting inaccuracies, inconsistencies, and missing values in datasets. It’s crucial because poor data quality can lead to misleading analysis and incorrect decision-making.
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I ensure accuracy by:
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Normalization organizes data to reduce redundancy and improve data integrity by breaking tables into smaller related tables, making data storage and retrieval more efficient.
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A Pivot Table is a data summarization tool in Excel that allows you to aggregate, analyze, and compare data, transforming large datasets into concise summaries for reporting and analysis.
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I prioritize based on business objectives, complexity, and deadlines. I break tasks into smaller chunks, tackle high-priority items first, and maintain open communication with stakeholders to adjust priorities as needed.
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Data Analysts typically work with:
This is the updated list with the 12th question removed. Let me know if you need anything else!
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A data warehouse is a centralized repository that stores large amounts of structured data from various sources, making it easier to perform complex queries and analysis. It is typically used for reporting and business intelligence.
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ETL stands for Extract, Transform, and Load. It refers to the process of extracting data from various sources, transforming it into a usable format, and then loading it into a data warehouse or database. ETL is essential for integrating and preparing data for analysis.
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A data model is a conceptual framework used to organize and structure data. The common types are:
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A/B testing involves comparing two versions (A and B) of a product, webpage, or feature to determine which performs better. It’s often used in marketing or product development to make data-driven decisions.
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A p-value helps determine the statistical significance of results. It represents the probability that the observed results occurred by chance. A p-value below 0.05 is typically considered statistically significant, indicating strong evidence against the null hypothesis.
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Data normalization involves scaling data values to a standard range, typically between 0 and 1, to ensure consistency and improve the performance of certain machine learning algorithms. It helps in comparing data with different scales.
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A Key Performance Indicator (KPI) is a measurable value that indicates how effectively a company or project is achieving its key objectives. KPIs help analysts track progress and provide insights for decision-making.
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A Data Analyst helps businesses make data-driven decisions by collecting, analyzing, and interpreting data. The role includes identifying trends, generating reports, and providing actionable insights to improve business processes and outcomes.
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When handling large datasets, I use techniques like:
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Regression analysis is a statistical technique used to model the relationship between a dependent variable and one or more independent variables. It helps predict outcomes and understand the strength of relationships in data.
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Data visualization helps to represent data in graphical formats, making complex datasets easier to understand and analyze. It enables better insights, easier communication of results, and more informed decision-making.
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Time series analysis involves analyzing data points collected or recorded at specific time intervals to identify trends, cycles, and patterns over time. It is often used for forecasting and trend analysis.
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To ensure data privacy and security, I follow best practices like: