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Cognizant
Proud winner of ABECA 2024 - AmbitionBox Employee Choice Awards
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I was interviewed in Aug 2021.
Big Data refers to large volumes of data that cannot be processed using traditional methods.
Big Data involves processing and analyzing large volumes of data
It includes structured, unstructured, and semi-structured data
Examples include social media data, sensor data, and financial transactions
I applied via Company Website and was interviewed in Jun 2024. There was 1 interview round.
Data migration is the process of transferring data from one system to another.
Data migration involves transferring data from one storage system to another.
It can also involve moving data from one format to another.
Data migration is often necessary when upgrading systems or consolidating data.
Examples include migrating data from an old CRM system to a new one, or moving data from on-premises servers to the cloud.
Agile methodologies within data migration involve iterative and incremental processes to efficiently move data from one system to another.
Scrum: Breaks down the data migration process into smaller tasks called sprints, with regular meetings to track progress.
Kanban: Visualizes the data migration workflow on a board, allowing for continuous delivery of data.
Lean: Focuses on minimizing waste and maximizing value during t...
I applied via Walk-in and was interviewed in May 2024. There were 2 interview rounds.
It was good,Who will pass the test they will get into interview otherwise they are not selected for next round.
I cleared my Aptitude test.
Forecasting problem - Predict daily sku level sales
Bias is error due to overly simplistic assumptions, variance is error due to overly complex models.
Bias is the error introduced by approximating a real-world problem, leading to underfitting.
Variance is the error introduced by modeling the noise in the training data, leading to overfitting.
High bias can cause a model to miss relevant relationships between features and target variable.
High variance can cause a model to ...
Parametric models make strong assumptions about the form of the underlying data distribution, while non-parametric models do not.
Parametric models have a fixed number of parameters, while non-parametric models have a flexible number of parameters.
Parametric models are simpler and easier to interpret, while non-parametric models are more flexible and can capture complex patterns in data.
Examples of parametric models inc...
I applied via Naukri.com and was interviewed in Sep 2024. There was 1 interview round.
SCD type 2 is a method used in data warehousing to track historical changes by creating a new record for each change.
SCD type 2 stands for Slowly Changing Dimension type 2
It involves creating a new record in the dimension table whenever there is a change in the data
The old record is marked as inactive and the new record is marked as current
It allows for historical tracking of changes in data over time
Example: If a cust...
posted on 19 Nov 2024
I applied via Naukri.com and was interviewed in May 2024. There was 1 interview round.
1. Questions on spark basica
2. Sql coding questions
3. Java or scala basics
I applied via Job Portal and was interviewed in Apr 2023. There were 2 interview rounds.
I am a detail-oriented individual with strong data entry skills and experience in various industries.
I have worked as a data entry operator for 2 years at XYZ company
I am proficient in Microsoft Excel and have experience in data analysis
I have excellent typing speed and accuracy
I am a quick learner and can adapt to new software and systems easily
I applied via Naukri.com and was interviewed in Nov 2022. There were 3 interview rounds.
TF-IDF is a statistical measure used to evaluate the importance of a word in a document.
TF-IDF stands for Term Frequency-Inverse Document Frequency
It is used to weigh a word's importance in a document by considering its frequency in the document and across all documents
The formula for TF-IDF is: TF-IDF = TF * IDF
TF (Term Frequency) measures how frequently a term appears in a document
IDF (Inverse Document Frequency) mea...
Group by is used to group data based on a column while window function is used to perform calculations on a specific window of data.
Group by is used to aggregate data based on a specific column
Window function is used to perform calculations on a specific window of data
Group by is used with aggregate functions like sum, count, avg, etc.
Window function is used with analytical functions like rank, lead, lag, etc.
Group by ...
Developed a predictive model to forecast customer churn for a telecom company.
Used machine learning algorithms like logistic regression and random forest.
Preprocessed and cleaned the dataset by handling missing values and outliers.
Performed feature engineering to create new variables for better model performance.
Evaluated model performance using metrics like accuracy, precision, and recall.
Implemented the model in prod
Seeking new challenges and opportunities for growth.
Looking for a more challenging role that aligns with my career goals.
Seeking a company that values innovation and encourages professional development.
Want to work in a more collaborative and diverse team environment.
Desire to explore new technologies and industries.
Current company lacks opportunities for advancement or career growth.
posted on 6 Apr 2023
I applied via Naukri.com and was interviewed in Oct 2022. There were 3 interview rounds.
Quants, logic and English including puzzles and some gk based puzzles as well
I applied via Company Website and was interviewed in Jul 2022. There were 5 interview rounds.
The test will be conducted in a interview process
Group discussion is a communicate in a people
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