Knowledge Hut

NOVEMBER 28, 2023

Kafka Kafka is one of the most desired open-source messaging and streaming systems that allows you to publish, distribute, and consume data streams. Kafka, which is written in Scala and Java, helps you scale your performance in today’s data-driven and disruptive enterprises.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

NOVEMBER 19, 2023

Open Source Support: Many Azure services support popular open-source frameworks like Apache Spark, Kafka, and Hadoop, providing flexibility for data engineering tasks. Top 10 Azure Data Engineer Tools I have compiled a list of the most useful Azure Data Engineer Tools here, please find them below.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

Knowledge Hut

NOVEMBER 17, 2023

To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases. Big Data Technologies You must explore big data technologies such as Apache Spark, Hadoop, and related Azure services like Azure HDInsight.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Edureka

FEBRUARY 9, 2023

In this blog on “Azure data engineer skills”, you will discover the secrets to success in Azure data engineering with expert tips, tricks, and best practices Furthermore, a solid understanding of big data technologies such as Hadoop, Spark, and SQL Server is required.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

OCTOBER 15, 2014

Pig and Hive are the two key components of the Hadoop ecosystem. What does pig hadoop or hive hadoop solve? Pig hadoop and Hive hadoop have a similar goal- they are tools that ease the complexity of writing complex java MapReduce programs. Table of contents Hive vs Pig What is Big Data and Hadoop?

Hadoop 52

Hadoop Unstructured Data Java SQL 52

AltexSoft

OCTOBER 8, 2021

The tool supports all sorts of data loading and processing: real-time, batch, streaming (using Spark), etc. ODI has a wide array of connections to integrate with relational database management systems ( RDBMS) , cloud data warehouses, Hadoop, Spark , CRMs, B2B systems, while also supporting flat files, JSON, and XML formats.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

Knowledge Hut

SEPTEMBER 26, 2023

Relational databases, nonrelational databases, data streams, and file stores are examples of data systems. 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.

Certification 52

Certification Data Engineering Data Engineer Engineering 52