Oracle Top Data Analytics Interview Questions and Answers

Oracle, a global leader in database technology, is at the forefront of leveraging data science and analytics to drive business innovation. Aspiring data scientists and analysts aiming to join Oracle or advance their careers within the company must be well-prepared for the interview process. In this blog, we’ll delve into some common data science and analytics interview questions specific to Oracle, along with insightful answers to help candidates succeed in their endeavors.

Technical Interview Questions

Question: Explain PEFT in the Finetuning of LLM

Answer: PEFT, or Pretraining-Encouraging Fine-Tuning, is a technique in the fine-tuning of Large Language Models (LLMs). It involves adding a penalty to the loss function during fine-tuning to retain the knowledge from pretraining. This helps prevent forgetting of learned information while adapting the model to new tasks, enhancing overall performance.

Question: Explain the various types of backups available in Oracle.

Answer: Full Backup: Copies the entire database, including data, logs, and control files.

Incremental Backup: Backs up only changed data since the last backup, saving time and storage.

Archive Log Backup: Essential for point-in-time recovery, capturing all committed transactions up to a specific time. These options allow for flexibility in backup strategies to meet different recovery needs in Oracle databases.

Question: What is an Oracle table?

Answer: An Oracle table is a basic structure in an Oracle database used to store data in rows and columns. It consists of columns, each defining a specific data type, and rows containing the actual data entries. Tables are fundamental to organizing and managing data in Oracle databases, providing a structured way to store, retrieve, and manipulate information. Each table has a unique name and can hold related data about a specific entity or concept, such as customers, products, or orders.

Question: What are PL/SQL Blocks, and How Many Different Types Are There?

Answer: PL/SQL (Procedural Language/Structured Query Language) blocks are sections of code in Oracle’s PL/SQL programming language. They consist of one or more statements that perform a specific task or set of tasks. There are three main types of PL/SQL blocks:

Anonymous Blocks:

• Are unnamed and can be executed directly.
• Used for ad-hoc tasks or quick scripts.

Named Blocks:

• Have a name and are stored in the database.
• Can be called or executed by other programs or scripts.

Nested Blocks:

• Contain one or more inner blocks within an outer block.
• Used to organize and modularize code, improving readability and maintainability.

Question: What is The Difference Between Syntax and Runtime Errors?

Answer:

Syntax Errors:

• Occur due to mistakes in code structure or grammar, like missing semicolons or typos.
• Detected by the compiler or interpreter during code compilation.
• Code cannot run until syntax errors are fixed.

Runtime Errors:

• Occur during code execution due to issues like dividing by zero or type mismatches.
• Detected while the program is running.
• Code compiles successfully but may crash or produce unexpected results if runtime errors are not handled.

Question: Explain the Aggregate and Scalar functions in SQL.

Answer:

Aggregate Functions:

• Operate on a group of rows and return a single result for the entire group.
• Common examples include SUM(), AVG(), COUNT(), MAX(), and MIN().
• Used with the GROUP BY clause to calculate values for groups of rows.
• Helpful for generating summary statistics or performing calculations across multiple rows.

Scalar Functions:

• Operate on a single value and return a single result.
• Applied to each row individually within a query.
• Examples include UPPER(), LOWER(), CONCAT(), and SUBSTRING().
• Useful for manipulating data, converting formats, or extracting parts of values within a row.

Question: What is word embedding and why is it used?

Answer: Word embedding is a technique in natural language processing (NLP) to represent words as vectors in a continuous vector space.

It captures semantic and syntactic relationships between words, allowing machines to understand the context and meaning of words.

Word embeddings are used to improve the performance of NLP tasks like text classification, sentiment analysis, and machine translation by providing dense and meaningful representations of words.

Question: What is machine learning?

Answer: Machine learning is a branch of artificial intelligence focused on developing algorithms that allow computers to learn and make predictions or decisions based on data. It involves training models on datasets to recognize patterns and make informed decisions without explicit programming. These models are used in various fields, including healthcare, finance, marketing, and autonomous systems, to solve complex problems and make accurate predictions.

Question: Describe logistic regression.

Answer: Logistic regression is a type of regression analysis used for binary classification tasks.

It models the relationship between a binary outcome variable and one or more predictor variables by estimating probabilities using a logistic function.

The output is transformed into a probability between 0 and 1, with a threshold used to classify the outcome into one of the two classes.

Question: Explain the various forms of normalization.

Answer:

• Min-Max Normalization: Scales data to a fixed range (usually 0 to 1) by subtracting the minimum value and dividing by the range.
• Z-Score Normalization (Standardization): Standardizes data to have a mean of 0 and a standard deviation of 1 by subtracting the mean and dividing by the standard deviation.
• Robust Normalization: Scales data based on quartiles to reduce the effect of outliers, often using the interquartile range (IQR).

Question: Explain the process of Pattern Matching in SQL.

Answer: Pattern matching in SQL involves searching for specific patterns or substrings within text data using the LIKE operator and wildcard characters such as % and _. For example, % matches zero or more characters, while _ matches a single character. Additionally, the REGEXP_LIKE() function allows for more complex pattern matching using regular expressions. This functionality is useful for tasks like searching for email addresses or phone numbers within a database.

Question: What is a random forest? Is random walk stationary or not, why?

Answer:

Random Forest: Random Forest is an ensemble learning method that combines multiple decision trees to improve prediction accuracy and handle complex datasets effectively.

Random Walk Stationarity: A random walk is generally not stationary because it lacks a constant mean or variance, following an unpredictable path. However, a “simple random walk” with mean zero and constant variance is weakly stationary, as its statistical properties remain constant over time intervals.

Question: Which technique would you use to solve a time series problem?

Answer: Time Series Analysis:

Time series analysis involves studying data collected over some time to identify patterns, and trends, and make forecasts.

Techniques such as moving averages, exponential smoothing, ARIMA models, and seasonal decomposition are commonly used.

It helps in understanding the underlying patterns, seasonality, and trends, and making predictions for future time points based on historical data.

Question: How is PL/SQL Different From SQL?

Answer: SQL (Structured Query Language):

SQL is a standard language used to interact with relational databases.

It is focused on querying, updating, and managing data within a database.

SQL commands include SELECT, INSERT, UPDATE, and DELETE for data manipulation, and CREATE, ALTER, and DROP for database schema operations.

PL/SQL (Procedural Language/Structured Query Language):

PL/SQL is an extension of SQL that adds procedural capabilities to the language.

It allows for writing procedural logic like loops, conditional statements, and exception handling within SQL statements.

PL/SQL is used for creating stored procedures, functions, triggers, and packages, providing more advanced and flexible database programming capabilities compared to SQL alone.

Question: What are the assumptions of linear regression?

Answer:

• Linearity: Assumes a linear relationship between the independent and dependent variables.
• Independence of Errors: Errors (residuals) are independent of each other, with no correlation.
• Homoscedasticity: Residuals have constant variance across all levels of predictors.
• Normality of Errors: Residuals follow a normal distribution around zero for valid statistical inference.

Question: Describe Exception Handling in PL/SQL.

Answer: PL/SQL exception handling allows for the detection and handling of errors during code execution.

Using keywords like BEGIN, EXCEPTION, and END, developers can define blocks of code to handle specific errors.

Actions within exception handlers can include logging errors, rolling back transactions, or displaying custom error messages for better user interaction and error management.

Question: Explain the concept of database normalization.

Answer: Database normalization is the process of structuring a relational database to reduce redundancy and dependency.

It aims to organize data into separate tables to eliminate data duplication and improve data integrity.

The normalization process follows specific rules (normal forms) to ensure efficient storage, reduce anomalies, and facilitate easier data management and updates.

Question: What is SQL?

Answer: SQL is a standard language for interacting with relational databases.

It enables users to query, update, and manage data within a database.

SQL commands include SELECT, INSERT, UPDATE, and DELETE for data manipulation, and CREATE, ALTER, and DROP for database schema operations.

Question: What Are PL/SQL Cursors?

Answer: PL/SQL cursors are pointers or handles used to retrieve rows from the result set of a query.

They allow developers to process individual rows returned by a SELECT statement within PL/SQL code.

Cursors can be used to fetch and manipulate data row by row, enabling better control over data processing and manipulation in PL/SQL programs.

Question: Name Three PL/SQL Exceptions.

Answer:

• NO_DATA_FOUND: Raised when a SELECT INTO statement returns no rows.
• TOO_MANY_ROWS: Raised when a SELECT INTO statement returns more than one row.
• ZERO_DIVIDE: Raised when attempting to divide by zero.

These exceptions allow for specific error handling and custom actions based on different error scenarios in PL/SQL programs.

Question: What is the difference between a correlated subquery and a non-correlated subquery?

Answer:

Correlated Subquery:

• Correlated subqueries depend on the outer query for their execution.
• The subquery is executed for each row of the outer query, using values from the outer query in its execution.
• Typically used when the inner query needs to reference columns from the outer query.

Non-Correlated Subquery:

• Non-correlated subqueries can be executed independently of the outer query.
• The subquery is executed only once, and its result is used by the outer query.
• Used when the subquery does not rely on the outer query for its execution.

Other Technical Topics

• Statistical questions and some data pre-processing questions
• Data structures and object-oriented programming.
• Python, SQL, and Machine Learning

Other Technical Questions

Que: When do you use a certain programming language over another?

Que: How to frame ML framework?

Que: What kind of method do you know for time series problems?

General Interview Questions

Que: Why do you choose Oracle?

Que: Do you know anyone who might fit the role?

Que: How would you describe a random forest to an older person?

Que: How can you cut a pie into pieces with three cuts?

Conclusion

Preparing for a data science and analytics interview at Oracle requires a solid understanding of the company’s data-centric approach and technologies. By familiarizing oneself with these common interview questions and crafting thoughtful responses, candidates can showcase their skills in data mining, SQL optimization, machine learning, and data handling within Oracle environments. Oracle continues to pave the way in harnessing the power of data, offering exciting opportunities for professionals to contribute to cutting-edge projects and drive business growth.

Best of luck with your Oracle data science and analytics interview!