Data engineering Interview questions: Accenture


Q1.Which Integration Runtime (IR) should be used for copying data from an on-premise database to Azure?

Q2.Explain the differences between a Scheduled Trigger and a Tumbling Window Trigger in Azure Data Factory. When would you use each?

Q3. What is Azure Data Factory (ADF), and how does it enable ETL and ELT processes in a cloud environment?

Q4.Describe Azure Data Lake and its role in a data architecture. How does it differ from Azure Blob Storage?

Q5. What is an index in a database table? Discuss different types of indexes and their impact on query performance.

Q6.Given two datasets, explain how the number of records will vary for each type of join (Inner Join, Left Join, Right Join, Full Outer Join).

Q7.What are the Control Flow activities in the Azure Data Factory? Explain how they differ from Data Flow activities and their typical use cases.

Q8. Discuss key concepts in data modeling, including normalization and denormalization. How do security concerns influence your choice of Synapse table types in a given scenario? Provide an example of a scenario-based ADF pipeline.

Q9. What are the different types of Integration Runtimes (IR) in Azure Data Factory? Discuss their use cases and limitations.

Q10.How can you mask sensitive data in the Azure SQL Database? What are the different masking techniques available?

Q11.What is Azure Integration Runtime (IR), and how does it support data movement across different networks?

Q12.Explain Slowly Changing Dimension (SCD) Type 1 in a data warehouse. How does it differ from SCD Type 2?

Q13.SQL questions on window functions - rolling sum and lag/lead based. How do window functions differ from traditional aggregate functions?

Date: 15-02-2025
Company name: Ikea
Role: Data Scientist

01. What is the meaning of term weight initialization in neural networks?

Answer-  In neural networking, weight initialization is one of the essential factors. A bad weight initialization prevents a network from learning. On the other side, a good weight initialization helps in giving a quicker convergence and a better overall error. Biases can be initialized to zero. The standard rule for setting the weights is to be close to zero without being too small.

02. What is the usage of the NVL() function?

Answer- The NVL() function is used to convert the NULL value to the other value. The function returns the value of the second parameter if the first parameter is NULL. If the first parameter is anything other than NULL, it is left unchanged. This function is used in Oracle, not in SQL and MySQL. Instead of NVL() function, MySQL have IFNULL() and SQL Server have ISNULL() function.

03.  How to create a dictionary in Python?

Answer- In Python, a dictionary can be created by placing a sequence of elements within curly {} braces, separated by ‘comma’. Dictionary holds pairs of values, one being the Key and the other corresponding pair element being its Key:value. Values in a dictionary can be of any data type and can be duplicated, whereas keys can’t be repeated and must be immutable.

04. What is matplotlib and some of the basic plots in Matplotlib?

Answer-  Matplotlib comes with a wide variety of plots. Plots help to understand trends, patterns, and to make correlations. They’re typically instruments for reasoning about quantitative information. Some of the basic plots are line plot, bar plot, scatter plot, etc.

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Stay Safe & Happy Learning 💙

Date: 26-02-2025
Company name: Adecco
Role: Data Scientist

01. What is a stored procedure?

Answer-  Stored Procedure is a function consists of many SQL statements to access the database system. Several SQL statements are consolidated into a stored procedure and execute them whenever and wherever required.

02. What is Dimensionality Reduction?

Answer- In the real world, Machine Learning models are built on top of features and parameters. These features can be multidimensional and large in number. Sometimes, the features may be irrelevant and it becomes a difficult task to visualize them. This is where dimensionality reduction is used to cut down irrelevant and redundant features with the help of principal variables. These principal variables conserve the features, and are a subgroup, of the parent variables.

03.  What are Autoencoders?

Answer- An autoencoder is a kind of artificial neural network. It is used to learn efficient data codings in an unsupervised manner. It is utilised for learning a representation (encoding) for a set of data, mostly for dimensionality reduction, by training the network to ignore signal “noise”. Autoencoder also tries to generate a representation as close as possible to its original input from the reduced encoding.

04. What are some common Data Preparation Operations you would use for Time Series Data?

Answer-

a. Parsing time series information from various sources and formats.

b. Generating sequences of fixed-frequency dates and time spans.

c. Manipulating and converting date times with time zone information.

d. Resampling or converting a time series to a particular frequency.

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Stay Safe & Happy Learning 💙

Cisco Kafka interview questions for Data Engineers 2024.

➤ How do you create a topic in Kafka using the Confluent CLI?
➤ Explain the role of the Schema Registry in Kafka.
➤ How do you register a new schema in the Schema Registry?
➤ What is the importance of key-value messages in Kafka?
➤ Describe a scenario where using a random key for messages is beneficial.
➤ Provide an example where using a constant key for messages is necessary.
➤ Write a simple Kafka producer code that sends JSON messages to a topic.
➤ How do you serialize a custom object before sending it to a Kafka topic?
➤ Describe how you can handle serialization errors in Kafka producers.
➤ Write a Kafka consumer code that reads messages from a topic and deserializes them from JSON.
➤ How do you handle deserialization errors in Kafka consumers?
➤ Explain the process of deserializing messages into custom objects.
➤ What is a consumer group in Kafka, and why is it important?
➤ Describe a scenario where multiple consumer groups are used for a single topic.
➤ How does Kafka ensure load balancing among consumers in a group?
➤ How do you send JSON data to a Kafka topic and ensure it is properly serialized?
➤ Describe the process of consuming JSON data from a Kafka topic and converting it to a usable format.
➤ Explain how you can work with CSV data in Kafka, including serialization and deserialization.
➤ Write a Kafka producer code snippet that sends CSV data to a topic.
➤ Write a Kafka consumer code snippet that reads and processes CSV data from a topic.

All the best 👍👍

Date: 04-03-2025
Company name: Capgemini
Role: Data Scientist

01. What is the meaning of KPI in statistics?

Answer-  KPI is an acronym for a key performance indicator. It can be defined as a quantifiable measure to understand whether the goal is being achieved or not. KPI is a reliable metric to measure the performance level of an organization or individual with respect to the objectives. An example of KPI in an organization is the expense ratio.

02.What is the concept of graph neural networks in deep learning?

Answer- Graph neural networks are designed to operate on structured data represented as
graphs. They can capture relational dependencies and propagate information across
nodes and edges in a graph. Graph neural networks have been successfully applied to
tasks such as social network analysis, recommendation systems, and molecular chemistry.

03.  What is the concept of autoencoders in deep learning?

Answer- Autoencoders are neural networks trained to reconstruct their input data. They consist of
an encoder network that maps the input data to a lower-dimensional representation
(latent space) and a decoder network that reconstructs the input from the latent space.
Autoencoders are used for dimensionality reduction, feature learning, and anomaly
Detection.


04.What is the concept of learning rate in deep learning?

Answer- The learning rate determines the step size at which the weights are updated during
training. Choosing an appropriate learning rate is important, as a small value may result
in slow convergence, while a large value may cause unstable training or overshooting
the optimal solution.

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Stay Safe & Happy Learning 💙

Date: 06-03-2025
Company name: IBM
Role: Data Scientist

01. How to create empty tables with the same structure as another table?

Answer-  To create empty tables: Using the INTO operator to fetch the records of one table into a new table while setting a WHERE clause to false for all entries, it is possible to create empty tables with the same structure. As a result, SQL creates a new table with a duplicate structure to accept the fetched entries, but nothing is stored into the new table since the WHERE clause is active.

02.Explain Correlation and Covariance?

Answer- Correlation is used for measuring and also for estimating the quantitative relationship between two variables. Correlation measures how strongly two variables are related. Examples like, income and expenditure, demand and supply, etc.

Covariance is a simple way to measure the correlation between two variables. The problem with covariance is that they are hard to compare without normalization.

03.  What’s the difference between a generative and discriminative model?

Answer-  A generative model will learn categories of data while a discriminative model will simply learn the distinction between different categories of data. Discriminative models will generally outperform generative models on classification tasks.

04.When does regularization become necessary in Machine Learning?

Answer- Regularization is necessary whenever the model begins to overfit/ underfit. It is a cost term for bringing in more features with the objective function. Hence, it tries to push the coefficients for many variables to zero and reduce cost term. It helps to reduce model complexity so that the model can become better at predicting (generalizing).

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COMMON TERMINOLOGIES IN PYTHON - PART 1

Have you ever gotten into a discussion with a programmer before? Did you find some of the Terminologies mentioned strange or you didn't fully understand them?

In this series, we would be looking at the common Terminologies in python.

It is important to know these Terminologies to be able to professionally/properly explain your codes to people and/or to be able to understand what people say in an instant when these codes are mentioned. Below are a few:

IDLE (Integrated Development and Learning Environment) - this is an environment that allows you to easily write Python code. IDLE can be used to execute a single statements and create, modify, and execute Python scripts.

Python Shell - This is the interactive environment that allows you to type in python code and execute them immediately

System Python - This is the version of python that comes with your operating system

Prompt - usually represented by the symbol ">>>" and it simply means that python is waiting for you to give it some instructions

REPL (Read-Evaluate-Print-Loop) - this refers to the sequence of events in your interactive window in form of a loop (python reads the code inputted>the code is evaluated>output is printed)

Argument - this is a value that is passed to a function when called eg print("Hello World")... "Hello World" is the argument that is being passed.

Function - this is a code that takes some input, known as arguments, processes that input and produces an output called a return value. E.g print("Hello World")... print is the function

Return Value - this is the value that a function returns to the calling script or function when it completes its task (in other words, Output). E.g.
>>> print("Hello World")
Hello World
Where Hello World is your return value.

Note: A return value can be any of these variable types: handle, integer, object, or string

Script - This is a file where you store your python code in a text file and execute all of the code with a single command

Script files - this is a file containing a group of python scripts

How long are coding interviews?
The phone screen portion of the coding interview typically lasts up to one hour. The second, more technical part of the interview can take multiple hours.

Where can I practice coding?
There are many ways to practice coding and prepare for your coding interview. LeetCode provides practice opportunities in more than 14 languages and more than 1,500 sample problems. Applicants can also practice their coding skills and interview prep with HackerRank.

How do I know if my coding interview went well?
There are a variety of indicators that your coding interview went well. These may include going over the allotted time, being introduced to additional team members, and receiving a quick response to your thank you email.

In class, there are some students who are really good at coding from the start, and seeing them can make us feel quite demotivated, especially since they often appear overconfident.

But it's not important how much someone already knows. If you start and practice consistently, it's not that tough to match their level or even surpass them.

And often, these overconfident people don’t perform as well as you can because you have the desire to learn, while they think they already know everything.

So, my friend, don’t get demotivated—just give it time!

When you're studying DSA, you probably think, "This won't be directly used in the actual work of a company, so why am I even doing this?"

And in life, where will this even come in handy? Well, it won't be useful directly, but the hard work you're putting in—sitting day and night solving questions—that habit of working hard will pay off.

It's not really about DSA, but about the effort you're willing to give that will decide which company you land your internship or placement in ❤️

DSA question by understanding patterns

If the input array is sorted then
- Binary search
- Two pointers

If asked for all permutations/subsets then
- Backtracking

If given a tree then
- DFS
- BFS

If given a graph then
- DFS
- BFS

If given a linked list then
- Two pointers

If recursion is banned then
- Stack

If must solve in-place then
- Swap corresponding values
- Store one or more different values in the same pointer

If asked for maximum/minimum subarray/ subset/options then
- Dynamic programming

If asked for top/least K items then
- Heap
- QuickSelect

If asked for common strings then
- Map
- Trie

Else
- Map/Set for O(1) time & O(n) space
- Sort input for O(nlogn) time and O(1) space

List of most asked Programming Interview Questions.

Are you preparing for a coding interview? This tweet is for you. It contains a list of the most asked interview questions from each topic.

Arrays

- How is an array sorted using quicksort?
- How do you reverse an array?
- How do you remove duplicates from an array?
- How do you find the 2nd largest number in an unsorted integer array?

Linked Lists

- How do you find the length of a linked list?
- How do you reverse a linked list?
- How do you find the third node from the end?
- How are duplicate nodes removed in an unsorted linked list?

Strings

- How do you check if a string contains only digits?
- How can a given string be reversed?
- How do you find the first non-repeated character?
- How do you find duplicate characters in strings?

Binary Trees

- How are all leaves of a binary tree printed?
- How do you check if a tree is a binary search tree?
- How is a binary search tree implemented?
- Find the lowest common ancestor in a binary tree?

Graph

- How to detect a cycle in a directed graph?
- How to detect a cycle in an undirected graph?
- Find the total number of strongly connected components?
- Find whether a path exists between two nodes of a graph?
- Find the minimum number of swaps required to sort an array.

Dynamic Programming

1. Find the longest common subsequence?
2. Find the longest common substring?
3. Coin change problem?
4. Box stacking problem?
5. Count the number of ways to cover a distance?

20 recently asked 𝗞𝗔𝗙𝗞𝗔 interview questions.

- How do you create a topic in Kafka using the Confluent CLI?
- Explain the role of the Schema Registry in Kafka.
- How do you register a new schema in the Schema Registry?
- What is the importance of key-value messages in Kafka?
- Describe a scenario where using a random key for messages is beneficial.
- Provide an example where using a constant key for messages is necessary.
- Write a simple Kafka producer code that sends JSON messages to a topic.
- How do you serialize a custom object before sending it to a Kafka topic?
- Describe how you can handle serialization errors in Kafka producers.
- Write a Kafka consumer code that reads messages from a topic and deserializes them from JSON.
- How do you handle deserialization errors in Kafka consumers?
- Explain the process of deserializing messages into custom objects.
- What is a consumer group in Kafka, and why is it important?
- Describe a scenario where multiple consumer groups are used for a single topic.
- How does Kafka ensure load balancing among consumers in a group?
- How do you send JSON data to a Kafka topic and ensure it is properly serialized?
- Describe the process of consuming JSON data from a Kafka topic and converting it to a usable format.
- Explain how you can work with CSV data in Kafka, including serialization and deserialization.
- Write a Kafka producer code snippet that sends CSV data to a topic.
- Write a Kafka consumer code snippet that reads and processes CSV data from a topic.


All the best 👍🏻👍🏻