ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment. then you are on the right page.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

DECEMBER 7, 2021

Data sources may include relational databases or data from SaaS (software-as-a-service) tools like Salesforce and HubSpot. Airflow also allows you to utilize any BI tool, connect to any data warehouse, and work with unlimited data sources. In most cases, data is synchronized in real-time at scheduled intervals.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 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

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

Edureka

FEBRUARY 7, 2023

It is possible to use Azure SQL Database, Azure SQL Managed Instance and Azure Synapse Analytics. It can be set up as a security policy on all SQL Databases in an Azure subscription. Data entry into PDW is optimized by Polybase, which also supports T-SQL. 5) What does Azure’s reserved capacity mean?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 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

ProjectPro

JANUARY 19, 2022

Relational and non-relational databases are among the most common data storage methods. Learning SQL is essential to comprehend the database and its structures. ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

JUNE 23, 2016

Hadoop job interview is a tough road to cross with many pitfalls, that can make good opportunities fall off the edge. One, often over-looked part of Hadoop job interview is - thorough preparation. Needless to say, you are confident that you are going to nail this Hadoop job interview. directly into HDFS or Hive or HBase.

Hadoop 40

Hadoop MySQL Relational Database Java 40

ProjectPro

JULY 27, 2021

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language).

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40