DareData

JULY 5, 2023

The Data Lake acts as the central repository for aggregating data from diverse sources in its raw format. Typically, it is advisable to retain the data in its original, unaltered format when transferring it from any source to the data lake layer.

Data Lake 52

Data Lake Building Raw Data ETL Tools 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. 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

ProjectPro

DECEMBER 7, 2021

The second step for building etl pipelines is data transformation, which entails converting the raw data into the format required by the end-application. The transformed data is then placed into the destination data warehouse or data lake. What is a Big Data Pipeline?

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. 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

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 scenario involves three main characters — publishers, subscribers, and a message or event broker. A subscriber is a receiving program such as an end-user app or business intelligence tool.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

ProjectPro

JULY 27, 2021

You may add new data regularly, but once you add the data, it does not change very frequently. Data is regularly updated. Data warehouses are optimized to handle complex queries, which can access multiple rows across many tables. There is a large amount of data involved. The amount of data is usually less.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40