Cambridge Technology Enterprises Interview Questions, Process, and Tips

Q1. What was your experience with performance optimization and data modeling scenario-based questions in relation to the Data Architect role?
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Q2. How do we construct a client's data model into a Low-Level Design (LLD) using data structures?
Ans. 
Constructing a client's data model into LLD involves defining data structures and their relationships for implementation.
• Identify key entities: Determine the main objects in the client's domain, e.g., 'Patient', 'Appointment'.

• Define attributes: Specify the properties of each entity, e.g., 'Patient' may have 'Name', 'DOB', 'MedicalHistory'.

• Establish relationships: Determine how entities interact, e.g., 'Patient' has man...read more
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Q3. How we can optimize DB Performance by using complex SQL Queries ?
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Optimizing DB performance with complex SQL involves efficient query design, indexing, and leveraging database features.
• Use indexing to speed up data retrieval. For example, create an index on columns frequently used in WHERE clauses.

• Optimize JOIN operations by ensuring that the joined columns are indexed. For instance, use INNER JOIN instead of OUTER JOIN when possible.

• Utilize subqueries and Common Table Expressions (C...read more
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Q4. How about defining Appraisal Process among your team members or what is the process of of same please elaborate ?
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Q1. What is your flexibility regarding the start date for the role you are applying for?
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Q2. What is your expected CTC and other salary components?
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Mostly aptitude and logical reasoning question were asked they were easy if you have little bit knowledge in these subjects.

It was also easy they give a random topic and we just have to speak even though you are nowhere right they just see how confident you are in front of other people what various points you can make.

Q1. Explain your final year project what is logistic regression and explain this on detail?
Ans. 
My final year project was on logistic regression.
• Logistic regression is a statistical model used to predict binary outcomes.

• It is a type of regression analysis where the dependent variable is categorical.

• The model estimates the probability of the outcome based on the input variables.

• It uses a logistic function to map the predicted values to probabilities.

• The model is commonly used in various fields like finance, market...read more
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Q2. What do you mean by hypothesis testing and p value?
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Hypothesis testing is a statistical method to test a hypothesis about a population parameter. P-value is the probability of observing a test statistic as extreme as the one computed from the sample data, assuming the null hypothesis is true.
• Hypothesis testing involves formulating a null hypothesis and an alternative hypothesis

• A test statistic is computed from the sample data and compared with a critical value or p-valu...read more
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Q3. Difference between bias and variance?
Ans. 
Bias is the difference between predicted values and actual values, while variance is the variability of model predictions.
• Bias is the error caused by oversimplification of the model, while variance is the error caused by overcomplication of the model.

• High bias leads to underfitting, while high variance leads to overfitting.

• Bias and variance are inversely proportional, meaning reducing one increases the other.

• An example...read more
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Q4. Difference between Machine Learning and deep learning?
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Machine learning is a subset of AI that involves training machines to learn from data. Deep learning is a subset of machine learning that uses neural networks to learn from large amounts of data.
• Machine learning involves training machines to learn from data and make predictions or decisions based on that data.

• Deep learning is a subset of machine learning that uses neural networks to learn from large amounts of data.

• Dee...read more
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Q5. Why we use sample over population?
Ans. 
We use sample over population to save time, money and resources.
• Sampling is less time-consuming and cost-effective than studying the entire population.

• Sampling helps to reduce errors and biases that may occur in studying the entire population.

• Sampling is useful when the population is too large to study in its entirety.

• Sampling can provide accurate results if the sample is representative of the population.
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Q1. How data is shared in components
Ans. 
Data is shared between components through props and state in React.
• In React, data is passed down from parent components to child components through props.

• Components can also have their own state which can be updated and passed down to child components.

• Redux can also be used for managing global state and sharing data between components.

• In Angular, data can be shared between components through services or by using @Input...read more
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Q2. Tell me about storages
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Storages are devices used to store data and information.
• Storages can be internal or external to a device

• Examples of internal storages are hard disk drives and solid-state drives

• Examples of external storages are USB flash drives and external hard drives

• Cloud storage is a type of external storage that allows data to be stored remotely

• Storages can have different capacities and speeds
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Q1. Explain the Oops concepts by giving examples of you current automation framework Explain difference between getwindowHandle() and getWindowhandles()
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Oops concepts are fundamental principles of object-oriented programming. getWindowHandle() returns the handle of the current window, while getWindowHandles() returns the handles of all open windows.
• Oops concepts include inheritance, polymorphism, encapsulation, and abstraction.

• Inheritance: Reusing code from a parent class in a child class.

• Polymorphism: Objects of different classes can be treated as objects of a common ...read more
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Q2. Basic questions
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Q1. In dept java questions Given an scenario and asked to write the java code
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Q2. Technical round
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Q1. How soon can you join and all basic HR releated questions
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