ProjectPro

NOVEMBER 5, 2014

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. For organizations to keep the load off MongoDB in the production database, data processing is offloaded to Apache Hadoop.

MongoDB 40

MongoDB Hadoop NoSQL Big Data 40

Knowledge Hut

APRIL 25, 2024

However, advances in technology have now made it possible to store, process, and analyze big data quickly and effectively. There are a variety of big data processing technologies available, including Apache Hadoop, Apache Spark, and MongoDB. The most popular NoSQL database systems include MongoDB, Cassandra, and HBase.

Big Data 98

Big Data Technology Hadoop NoSQL 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

Knowledge Hut

DECEMBER 26, 2023

Data Architects design, create and maintain database systems according to the business model requirements. In other words, they develop, maintain, and test Big Data solutions. They also make use of ETL tools, messaging systems like Kafka, and Big Data Tool kits such as SparkML and Mahout.

Data Science 97

Data Science BI Machine Learning Business Intelligence 97

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.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

SEPTEMBER 26, 2023

We as Azure Data Engineers should have extensive knowledge of data modelling and ETL (extract, transform, load) procedures in addition to extensive expertise in creating and managing data pipelines, data lakes, and data warehouses. Find out what makes on-premises and cloud data solutions different.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

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