Abzooba India Infotech Big Data Engineer Interview Questions and Answers

Technologies related to big data include Hadoop, Spark, Kafka, and NoSQL databases.

• Hadoop - Distributed storage and processing framework for big data

• Spark - In-memory data processing engine for big data analytics

• Kafka - Distributed streaming platform for handling real-time data feeds

• NoSQL databases - Non-relational databases for storing and retrieving large volumes of data

Cloud in big data refers to using cloud computing services to store, manage, and analyze large volumes of data.

• Cloud computing allows for scalable and flexible storage of big data

• It provides on-demand access to computing resources for processing big data

• Examples include AWS, Google Cloud, and Microsoft Azure

Data warehousing is the process of collecting, storing, and managing data from various sources for analysis and reporting.

• Data warehousing involves extracting data from multiple sources

• Data is transformed and loaded into a central repository

• Allows for complex queries and analysis to be performed on the data

• Examples include data warehouses like Amazon Redshift, Google BigQuery

Python is a versatile programming language used for various purposes including web development, data analysis, artificial intelligence, and automation.

• Python is used for web development with frameworks like Django and Flask.

• It is commonly used for data analysis and visualization with libraries like Pandas and Matplotlib.

• Python is popular in artificial intelligence and machine learning projects with libraries like TensorFlow and scikit-learn.

• It is also used for automation task...read more

Big data refers to large volumes of structured and unstructured data that is too complex for traditional data processing applications.

• Big data involves massive amounts of data that cannot be easily managed or analyzed using traditional methods

• It includes structured data (like databases) and unstructured data (like social media posts)

• Examples include analyzing customer behavior on e-commerce websites, processing sensor data in IoT devices, and analyzing social media trends