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. Need for Apache Sqoop How Apache Sqoop works? Need for Flume How Apache Flume works?

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

Ascend.io

OCTOBER 28, 2024

Intermediate Data Transformation Techniques Data engineers often find themselves in the thick of transforming data into formats that are not only usable but also insightful. Intermediate data transformation techniques are where the magic truly begins.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

ProjectPro

JANUARY 24, 2023

A survey by Data Warehousing Institute TDWI found that AWS Glue and Azure Data Factory are the most popular cloud ETL tools with 69% and 67% of the survey respondents mentioning that they have been using them. Both platforms are designed for data transformation and preparation.

AWS 52

AWS Cloud Amazon Web Services ETL Tools 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

Monte Carlo

FEBRUARY 15, 2023

A company’s production data, third-party ads data, click stream data, CRM data, and other data are hosted on various systems. An ETL tool or API-based batch processing/streaming is used to pump all of this data into a data warehouse. The following diagram explains how integrations work.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

AltexSoft

AUGUST 4, 2021

The step involving data transfer, filtering, and loading into either a data warehouse or data mart is called the extract-transform-load (ELT) process. When dealing with dependent data marts, the central data warehouse already keeps data formatted and cleansed, so ETL tools will do little job.

Data Lake 64

Data Lake Data Warehouse ETL Tools Database 64

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 Big Data ETL Tools 93