Knowledge Hut

DECEMBER 26, 2023

They use technologies like Storm or Spark, HDFS, MapReduce, Query Tools like Pig, Hive, and Impala, and NoSQL Databases like MongoDB, Cassandra, and HBase. 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 Business Intelligence Data Mining 97

Knowledge Hut

SEPTEMBER 26, 2023

Data is transferred into a central hub, such as a data warehouse, using ETL (extract, transform, and load) processes. Learn about well-known ETL tools such as Xplenty, Stitch, Alooma, etc. Popular Big Data tools and technologies that a data engineer has to be familiar with include Hadoop, MongoDB, and Kafka.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

NOVEMBER 17, 2023

ETL Processes : Knowledge of ETL (Extract, Transform, Load) processes and familiarity with ETL tools like Xplenty, Stitch, and Alooma is essential for efficiently moving and processing data. Data engineers should have a solid understanding of SQL for querying and managing data in relational databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

DECEMBER 7, 2021

In addition, to extract data from the eCommerce website, you need experts familiar with databases like MongoDB that store reviews of customers. You can use big-data processing tools like Apache Spark , Kafka , and more to create such pipelines. However, it is not straightforward to create data pipelines.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

AltexSoft

OCTOBER 21, 2022

Kafka can continue the list of brand names that became generic terms for the entire type of technology. In this article, we’ll explain why businesses choose Kafka and what problems they face when using it. In this article, we’ll explain why businesses choose Kafka and what problems they face when using it. What is Kafka?

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Rockset

OCTOBER 11, 2022

Introduction Managing streaming data from a source system, like PostgreSQL, MongoDB or DynamoDB, into a downstream system for real-time analytics is a challenge for many teams. The connector does require installing and managing additional tooling, Kafka Connect.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Edureka

FEBRUARY 9, 2023

Data is moved from databases and other systems into a single hub, such as a data warehouse, using ETL (extract, transform, and load) techniques. Learn about popular ETL tools such as Xplenty, Stitch, Alooma, and others. Understanding the database and its structures requires knowledge of SQL.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52