Knowledge Hut

APRIL 25, 2024

There are a variety of big data processing technologies available, including Apache Hadoop, Apache Spark, and MongoDB. Each of these technologies has its own strengths and weaknesses, but all of them can be used to gain insights from large data sets. The most popular NoSQL database systems include MongoDB, Cassandra, and HBase.

Big Data 98

Big Data Technology NoSQL Hadoop 98

Knowledge Hut

NOVEMBER 17, 2023

Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Storage, Azure Data Lake, Azure Blob Storage, Azure Cosmos DB, Azure Stream Analytics, Azure HDInsight, and other Azure data services are just a few of the many Azure data services that Azure data engineers deal with.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

NOVEMBER 5, 2014

Hadoop is the way to go for organizations that do not want to add load to their primary storage system and want to write distributed jobs that perform well. MongoDB NoSQL database is used in the big data stack for storing and retrieving one item at a time from large datasets whereas Hadoop is used for processing these large data sets.

MongoDB 40

MongoDB Hadoop NoSQL Big Data 40

Edureka

FEBRUARY 9, 2023

The following are some of the fundamental foundational skills required of data engineers: A data engineer should be aware of changes in the data landscape. They should also consider how data systems have evolved and how they have benefited data professionals.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

Cloud Academy

JANUARY 27, 2022

Some good options are Python (because of its flexibility and being able to handle many data types), as well as Java, Scala, and Go. Soft skills for data engineering Problem solving using data-driven methods It’s key to have a data-driven approach to problem-solving. Rely on the real information to guide you.

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

ProjectPro

JANUARY 19, 2022

A data engineer should be aware of how the data landscape is changing. They should also be mindful of how data systems have evolved and benefited data professionals. Explore the distinctions between on-premises and cloud data solutions. Different methods are used to store different types of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

JUNE 23, 2023

Other Competencies You should have proficiency in coding languages like SQL, NoSQL, Python, Java, R, and Scala. You should be thorough with technicalities related to relational and non-relational databases, Data security, ETL (extract, transform, and load) systems, Data storage, automation and scripting, big data tools, and machine learning.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52