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Data Lake Architecture: A New Repository for Data Engineer

机译:数据湖架构:数据工程师的新存储库

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摘要

Data is the biggest asset after people for businesses, and it is a new driver of the world economy. The volume of data that enterprises gather every day is growing rapidly. This kind of rapid growth of data in terms of volume, variety, and velocity is known as Big Data. Big Data is a challenge for enterprises, and the biggest challenge is how to store Big Data. In the past and some organizations currently, data warehouses are used to store Big Data. Enterprise data warehouses work on the concept of schema-on-write but Big Data analytics want data storage which works on the schema-on-read concept. To fulfill market demand, researchers are working on a new data repository system for Big Data storage known as a data lake. The data lake is defined as a data landing area for raw data from many sources. There is some confusion and questions which must be answered about data lakes. The objective of this article is to reduce the confusion and address some question about data lakes with the help of architecture.
机译:数据是企业人员之后最大的资产,这是世界经济的新司机。企业每天聚集的数据量迅速增长。在体积,品种和速度方面,这种数据的快速增长称为大数据。大数据是企业的挑战,最大的挑战是如何存储大数据。在过去和某些组织目前,数据仓库用于存储大数据。企业数据仓库在架构上写入的概念上,但大数据分析希望数据存储在读取的概念上工作。为了满足市场需求,研究人员正在研究一种新的数据存储库系统,用于称为数据湖的大数据存储。数据湖被定义为来自许多来源的原始数据的数据着陆区域。有一些困惑和问题必须得到关于数据湖泊的回答。本文的目标是减少混淆,并在建筑的帮助下解决有关数据湖的一些问题。

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