Best TCS Data Analyst Interview Questions and Answers for 2023

Introductionย 

Data Analytics is an extremely important field in today’s business world, and it will only become more so as time goes on. TCS has long been a leader in this area for a very long time. By 2023, Data Analytics is projected to be worth USD 240.56 billion worldwide, according to the market research report.ย 

TCS Interview Questions and Answersย 

When it comes to Data Analytics, TCS prefers to hire Data Analyst candidates who have had at least some exposure to what this field entails. Since there are many aspects of the job that need to be covered, you must know how they fit together. Some of these TCS Data Analyst interview questions will require some basic knowledge about how different processes work and what their results mean for your business.ย 

The Data Analyst interview questions are very competitive and difficult. If you want to become a Data Analyst, you need to prepare well and practice answering all possible TCS Data Analyst Interview Questions.ย 

TCS Basic Interview Questionsย 

Listed below are some of the top basic Data Analyst TCS technical interview questions:ย 

  1. What is the role of a Data Analyst?

Data Analysts’ responsibility is to analyze data using statistical techniques, implement databases, gather primary and secondary sources of data, and identify, analyze, and interpret trends.ย 

  1. Why do you want to work for TCS?

The work environment at TCS is very good, and employees receive a lot of respect from their managers. Furthermore, TCS is one of the top IT companies in the world.ย 

  1. How to track changes in databases?

Change data capture, and change tracking are two features of SQL Server that track changes to data. An application can use these features to identify DML changes (inserts, updates, and deletions) made to user tables.ย 

  1. What are the basic skills needed to become a Data Analyst?

Most Data Analysts do not require a deep understanding of complex mathematics, even though they should have a foundational knowledge of statistics and mathematics. Statistics, linear algebra, and calculus are generally required for Data Analysts.ย 

  1. Why is MS Access important in Data Analytics?

Your data can be more structured with Access since you can control what type of information is entered, what values are entered, and how one table relates to another.ย 

  1. What is data extraction?

Taking data from sources and storing or processing it is known as data extraction.ย 

  1. Define Data Wrangling

The process of data wrangling involves cleaning, structuring, and enriching raw data to make it more useful for decision-making. Data is discovered, structured, cleaned, enriched, validated, and analyzed.ย 

  1. What is an Outlier?

Values significantly out of a dataset’s mean are considered outliers. Outliers provide information on either measurement variability or experimental error.ย 

  1. What is data visualization?

Visualization of data is the process of presenting information graphically. Visual elements such as charts, graphs, and maps facilitate understanding data trends, outliers, and patterns.ย 

  1. Why do you need data visualization?

Charts and graphs make complex data easy to view and understand, and thus, data visualization has exploded in popularity. Moreover, data visualization highlights trends and outliers in an easier-to-understand format.ย 

10 TCS Intermediate Interview Questionsย 

Listed below are some of the intermediate-level TCS Data Analyst interview questions:ย 

  1. What is data mining?

Machine learning, statistics, and database systems are used in data mining to extract and uncover patterns in large data sets.ย 

  1. Define what Root Cause Analysis is?

In root cause analysis, faults or problems are identified by studying their root causes.ย 

  1. What Is the Goal of the A/B Testing?

A/B testing determines which version of a webpage or app performs better by comparing two versions against each other.ย 

  1. What is OLAP?

OLAP refers to a method that provides fast answers to multidimensional analytical queries in computing. Data mining, report writing, and relational databases are also part of business intelligence, which includes OLAP.ย 

  1. Give examples of python libraries used for data analysis?

  • NumPyย 
  • Pandasย 
  • Bokehย 
  • Matplotlibย 
  1. What is a hash table?

The term “hash table” refers to a data structure that stores data associatively.ย 

  1. Define Collaborative Filtering?

Collaboration filtering (CF) creates recommendations based on user behavior. In order to filter out information from the system, it analyzes data from other users and their interactions with the system.ย 

  1. What are some of the most popular tools used in big data?

  • Hadoopย 
  • Scalaย 
  • Sparkย 
  • Flumeย 
  1. Define N-gram.

An N-gram consists of n items in a text or speech.ย  As its name suggests, it consists primarily of adjacent words or letters of the same length that were found in the original text.ย 

  1. Define logistic regression?

Based on a single or more independent variable, a logistic regression model can be used to study datasets with a particular outcome. Models predict dependent variables by studying the relationships between multiple independent variables.ย 

10 TCS Advanced Interview Questionsย 

Listed below are some of the most advanced level TCS data scientist interview questions:ย 

  1. What is data governance?

Data governance describes how data is collected, stored, processed, and disposed of according to internal standards. Governance determines who has access to what types of data and what kinds of data are governed.ย 

  1. What is data lineage analysis?

In data lineage, data is understood, recorded, and visualized as it flows from data sources to consumers.ย 

  1. What is data profiling?

Reviewing source data, interpreting structure, content, and interconnections, and finding potential for data projects are all steps in the data profiling process.ย 

  1. What is data modeling?

In software engineering, data modeling involves applying formal techniques to create a data model for an information system.ย 

  1. What is dimensional modeling?

Dimensional modeling refers to the use of fact and dimension tables to keep a record of historical data in data warehouses. The database is optimized so that data can be retrieved more quickly. In dimensional modeling, the data is structured and arranged in a particular way to produce reports that provide better performance.ย 

  1. What is the KNN method of imputation?

Using KNN, several nearest neighbors are selected together with a distance metric. In addition to predicting discrete attributes, it can also predict continuous attributes.ย 

  1. How does a Data Analysis project work?

  • Problem statementย 
  • Data cleaning/preprocessingย 
  • Modelingย 
  • Data explorationย 
  • Data validationย 
  • Implementationย 
  • Verificationย 
  1. What statistical methodologies do Data Analysts use?

  • Cluster analysisย 
  • Bayesian methodologiesย 
  • Markov processย 
  • Rank statisticsย 
  1. Clustering algorithms possess what properties?

  • Flat or hierarchicalย 
  • Disjunctiveย 
  • Iterativeย 
  1. What does ‘naive’ mean in Naive Bayes?

As a general rule, naive assumptions assume that all the present data are equally important and unrelated.ย 

Conclusionย 

TCS is one of the top IT companies in India, and its Data Analyst Program is competitive. If you are planning to apply for this program, then you must prepare well for the TCS Data Analyst Interview Questions. These questions will help you understand what kind of problems are asked during an interview and how much preparation is required to crack them. UNext’s Integrated Program In Business Analytics can help you secure a promising career in the Data Analytics domain.ย 

Related Articles

loader
Please wait while your application is being created.
Request Callback