ProjectPro

JANUARY 19, 2022

Ability to demonstrate expertise in database management systems. Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Good communication skills as a data engineer directly works with the different teams. You may skip chapters 11 and 12 as they are less useful for a database engineer.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

SEPTEMBER 6, 2023

Problem-Solving Abilities: Many certification courses provide projects and assessments which require hands-on practice of big data tools which enhances your problem solving capabilities. Networking Opportunities: While pursuing big data certification course you are likely to interact with trainers and other data professionals.

Big Data 52

Big Data Certification Hadoop Scala 52

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 has adept knowledge of coding in Python, R, SQL, and using big data tools such as Spark.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more. No wonder only 0.5

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

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. There is a large amount of data involved.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

AUGUST 21, 2015

Differentiate between Structured and Unstructured data. Data that can be stored in traditional database systems in the form of rows and columns, for example, the online purchase transactions can be referred to as Structured Data. are all examples of unstructured data. RowKey is internally regarded as a byte array.

Hadoop 40

Hadoop Big Data Metadata Java 40