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I applied via Approached by Company and was interviewed before Oct 2022. There were 5 interview rounds.
It was a 10 question test regarding formulas and logics
posted on 27 Feb 2025
I appeared for an interview before Feb 2024.
Business Analysts analyze business processes, gather requirements, and recommend solutions to improve efficiency and productivity.
Analyzing business processes to identify areas for improvement
Gathering and documenting business requirements from stakeholders
Creating and maintaining project documentation such as requirements documents, use cases, and process flows
Collaborating with stakeholders to prioritize requirements...
I have 5 years of experience as a Business Analyst, where I led various projects and implemented process improvements.
Led cross-functional teams to analyze business processes and identify areas for improvement
Implemented new software systems to streamline operations and increase efficiency
Developed and presented reports to senior management with actionable insights
Collaborated with stakeholders to gather requirements a
I-Exceed offers innovative solutions tailored to meet the unique needs of businesses, driving efficiency and growth.
I-Exceed provides cutting-edge technology solutions for businesses to streamline operations and enhance productivity.
Their focus on customization ensures that each client receives a solution that fits their specific requirements.
I-Exceed's track record of successful implementations and satisfied clients s
Designing a data warehouse involves identifying data sources, defining data models, creating ETL processes, and implementing data governance.
Identify data sources and determine what data needs to be stored
Define data models to structure the data in a way that supports reporting and analysis
Create ETL (Extract, Transform, Load) processes to move data from source systems to the data warehouse
Implement data governance to ...
posted on 16 Jul 2021
I appeared for an interview in Dec 2021.
Round duration - 90 Minutes
Round difficulty - Easy
Problem solving using SQL questions
Round duration - 90 Minutes
Round difficulty - Easy
A marketing campaign is run, how will you decide metrics to be tracked. Techincaly a KPI round
Metrics selection based on campaign objectives, target audience, and key performance indicators.
Identify campaign objectives and goals
Consider target audience and their behavior
Select key performance indicators (KPIs) relevant to the campaign
Track metrics such as conversion rate, click-through rate, ROI, customer acquisition cost
Analyze data to measure success and make data-driven decisions
Round duration - 30 Minutes
Round difficulty - Easy
Social empathatic fit round
Tip 1 : SQL logics to be understood completely
Tip 2 : A good running working logic of Python
Tip 3 : Basics of Dashboarding
Tip 1 : One pager , single column resume which shows all your skills
Tip 2 : Mention all things that make you relevant for the job
I applied via Referral and was interviewed before May 2023. There was 1 interview round.
Window functions are used in SQL to perform calculations across a set of table rows related to the current row.
Types include ROW_NUMBER(), RANK(), DENSE_RANK(), NTILE(), LAG(), LEAD(), FIRST_VALUE(), LAST_VALUE(), etc.
They allow for calculations to be performed on a specific subset of rows within a query result set.
Window functions are commonly used for running totals, moving averages, and ranking data.
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:
Hackerrank test mostly on python and sql
posted on 29 Mar 2024
I applied via Referral and was interviewed before Mar 2023. There were 2 interview rounds.
Intermediate level coding round
Developed a predictive analytics model to forecast customer churn for a telecommunications company.
Collected and cleaned customer data from various sources
Performed exploratory data analysis to identify patterns and trends
Built a machine learning model using logistic regression to predict customer churn
Evaluated the model's performance using metrics such as accuracy, precision, and recall
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