Edureka

FEBRUARY 9, 2023

Data Ingestion and Transformation: Candidates should have experience with data ingestion techniques, such as bulk and incremental loading, as well as experience with data transformation using Azure Data Factory. SQL is also an essential skill for Azure Data Engineers.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

FEBRUARY 8, 2023

In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses. In 2023, more than 5140 businesses worldwide have started using AWS Glue as a big data tool. Why Use AWS Glue?

AWS 98

AWS Scala Metadata Data Lake 98

ProjectPro

JULY 27, 2021

Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on big data fundamentals, big data tools/technologies, and big data cloud computing platforms.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Databand.ai

DECEMBER 13, 2022

Deepanshu’s skills include SQL, data engineering, Apache Spark, ETL, pipelining, Python, and NoSQL, and he has worked on all three major cloud platforms (Google Cloud Platform, Azure, and AWS). He also shares thoughts and advice regularly on LinkedIn, centered around topics like SQL, data engineering, careers, and interviews.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Structured data is modeled to be easily searchable and occupy minimal storage space.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40