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

Knowledge Hut

NOVEMBER 17, 2023

Here is a step-by-step guide on how to become an Azure Data Engineer: 1. Understanding SQL You must be able to write and optimize SQL queries because you will be dealing with enormous datasets as an Azure Data Engineer. You should also be able to create indexes and create effective data structures to optimize queries.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

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. into HBase, Hive or HDFS.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

Monte Carlo

FEBRUARY 15, 2023

On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems. What is a data warehouse? Let’s imagine a scenario where you’re collecting orders information.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

AltexSoft

JANUARY 26, 2022

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. Here’s the video explaining how data engineers work. As the number of technological know-how increases, the data roles get changed and mixed.

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