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Data Lake or Data Warehouse- Which is Better?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Data is defined as information that has been organized in a meaningful way. Data collection is critical for businesses to make informed decisions, understand customers’ […]. The post Data Lake or Data Warehouse- Which is Better?

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Why Do We Prefer ELT Rather than ETL in the Data Lake? What is the Difference between ETL & ELT

insideBIGDATA

In this article, Ashutosh Kumar discusses the emergence of modern data solutions that have led to the development of ELT and ETL with unique features and advantages. ELT is more popular due to its ability to handle large and unstructured datasets like in data lakes.

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Data Version Control for Data Lakes: Handling the Changes in Large Scale

ODSC - Open Data Science

In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. As data lakes gain prominence as a preferred solution for storing and processing enormous datasets, the need for effective data version control mechanisms becomes increasingly evident.

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Best Practices for Data Lake Security

ODSC - Open Data Science

While databases were the traditional way to store large amounts of data, a new storage method has developed that can store even more significant and varied amounts of data. These are called data lakes. What Are Data Lakes? However, even digital information has to be stored somewhere.

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Integrating AWS Data Lake and RDS MS SQL: A Guide to Writing and Retrieving Data Securely

Dataversity

Writing data to an AWS data lake and retrieving it to populate an AWS RDS MS SQL database involves several AWS services and a sequence of steps for data transfer and transformation. This process leverages AWS S3 for the data lake storage, AWS Glue for ETL operations, and AWS Lambda for orchestration.

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The Solution to Data in Motion Is to Just Stop

insideBIGDATA

In this contributed article, Sida Shen, product marketing manager, CelerData, discusses how data lakehouse architectures promise the combined strengths of data lakes and data warehouses, but one question arises: why do we still find the need to transfer data from these lakehouses to proprietary data warehouses?

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Data Warehouse vs. Data Lake

Precisely

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. It is often used as a foundation for enterprise data lakes.