10+ Crescent Engineers Interview Questions and Answers

I was responsible for data cleaning, transformation, and visualization to create interactive dashboards for stakeholders.

• Performed data cleaning and transformation to ensure accuracy and consistency of data

• Utilized tools like SQL, Python, and Tableau to manipulate and visualize data

• Collaborated with stakeholders to understand their requirements and design interactive dashboards

• Generated insights from data analysis to drive decision-making processes

I optimize and manage large datasets by using tools like SQL, Python, and Excel. I utilize various data sources such as databases, APIs, and web scraping.

• Utilize SQL queries to efficiently extract and manipulate data from databases

• Use Python for data cleaning, analysis, and visualization tasks

• Leverage Excel for organizing and summarizing data in a user-friendly format

• Obtain data from sources like internal databases, external APIs, and web scraping techniques

There are approximately 500-600 traffic signals in Noida.

• Estimate based on the size and population of Noida

• Consider the number of major intersections and roads in the city

• Take into account the traffic density and need for traffic management

• Consult local traffic authorities for more accurate data

I would handle missing values by imputing them using methods like mean, median, mode, or predictive modeling.

• Identify the extent of missing data in the dataset

• Consider the type of missing values (completely at random, missing at random, or not missing at random)

• Impute missing values using mean, median, mode, predictive modeling, or other statistical methods

• Evaluate the impact of imputation on the dataset's integrity and analysis results

I would analyze sales data by identifying trends, customer behavior, and market opportunities to increase revenue.

• Identify key performance indicators (KPIs) such as average order value, conversion rate, and customer acquisition cost.

• Segment customers based on demographics, purchase history, and behavior to target specific groups with personalized marketing strategies.

• Analyze sales channels to determine which ones are most effective in driving revenue and allocate resources ac...read more

There are two types of Vlookup: Exact Match and Approximate Match.

• Exact Match Vlookup searches for an exact match of the lookup value in the first column of the table array.

• Approximate Match Vlookup searches for an approximate match of the lookup value in the first column of the table array.

• Exact Match Vlookup is denoted by 0 or FALSE in the formula, while Approximate Match Vlookup is denoted by 1 or TRUE in the formula.

Vlookup is a function in Excel used to search for a value in a table and return a corresponding value from another column.

• Vlookup stands for vertical lookup.

• It is commonly used to find and retrieve data from large datasets.

• The function requires a lookup value, a table range, and the column index number.

• Vlookup can be used to perform approximate or exact matches.

• It is often used for data analysis, data validation, and data reconciliation.

• Example: =VLOOKUP(A2, B2:D10, 3, FALSE)...read more

A pivot table is a data summarization tool used in spreadsheet programs like Excel.

• It allows users to quickly summarize and analyze large amounts of data.

• Users can easily group data by different categories and perform calculations on them.

• Pivot tables are useful for creating reports and visualizations.

• They can help identify trends and patterns in data.

• Example: A pivot table can be used to summarize sales data by product, region, and time period.

Filters can be applied to rows in a table to display specific data.

• Select the row(s) you want to filter

• Click on the filter icon in the toolbar

• Choose the filter criteria and apply

• The table will display only the rows that meet the filter criteria

Joins are used to combine rows from two or more tables based on a related column between them.

• Inner Join: Returns rows when there is a match in both tables.

• Left Join: Returns all rows from the left table and the matched rows from the right table.

• Right Join: Returns all rows from the right table and the matched rows from the left table.

• Full Outer Join: Returns rows when there is a match in one of the tables.

• Cross Join: Returns the Cartesian product of the two tables.