ProjectPro

OCTOBER 28, 2015

Some of the common challenges with data ingestion in Hadoop are parallel processing, data quality, machine data on a higher scale of several gigabytes per minute, multiple source ingestion, real-time ingestion and scalability. Sqoop hadoop can also be used for exporting data from HDFS into RDBMS.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

Monte Carlo

FEBRUARY 15, 2023

Cloud data warehouses solve these problems. Belonging to the category of OLAP (online analytical processing) databases, popular data warehouses like Snowflake, Redshift and Big Query can query one billion rows in less than a minute. What is a data warehouse?

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

DareData

JULY 5, 2023

The architecture of a data lake project may contain multiple components, including the Data Lake itself, one or multiple Data Warehouses or one or multiple Data Marts. The Data Lake acts as the central repository for aggregating data from diverse sources in its raw format.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

AltexSoft

AUGUST 4, 2021

Now let’s think of sweets as the data required for your company’s daily operations. Instead of combing through the vast amounts of all organizational data stored in a data warehouse, you can use a data mart — a repository that makes specific pieces of data available quickly to any given business unit.

Data Lake 64

Data Lake Data Warehouse ETL Tools Telecommunication 64

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. You should be able to create intricate queries that use subqueries, join numerous tables, and aggregate data.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

JANUARY 26, 2022

If we take the more traditional approach to data-related jobs used by larger companies, there are different specialists doing narrowly-focused tasks on different sides of the project. Data engineers build data pipelines and perform ETL — extract data from sources, transform it, and load it into a centralized repository like a data warehouse.

Engineering 59

Engineering Software Engineer Software Engineering Data Warehouse 59

AltexSoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. This enables systems using Kafka to aggregate data from many sources and to make it consistent. Instead of interfering with each other, Kafka consumers create groups and split data among themselves.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93