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What Are the Best Data Modeling Methodologies & Processes for My Data Lake?

phData: Data Engineering

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

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Top Data Lake Vendors (Quick Reference Guide)

Monte Carlo

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.

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Tips to Build a Robust Data Lake Infrastructure

DareData

Learn how we build data lake infrastructures and help organizations all around the world achieving their data goals. In today's data-driven world, organizations are faced with the challenge of managing and processing large volumes of data efficiently.

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What is Real-time Data Ingestion? Use cases, Tools, Infrastructure

Knowledge Hut

This is where real-time data ingestion comes into the picture. Data is collected from various sources such as social media feeds, website interactions, log files and processing. This refers to Real-time data ingestion. To achieve this goal, pursuing Data Engineer certification can be highly beneficial.

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How to learn data engineering

Christophe Blefari

The main difference between both is the fact that your computation resides in your warehouse with SQL rather than outside with a programming language loading data in memory. In this category I recommend also to have a look at data ingestion (Airbyte, Fivetran, etc.), workflows (Airflow, Prefect, Dagster, etc.)

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Data News — Week 23.09

Christophe Blefari

In a nutshell AI should be use as a tool to empower members and augment their success, while prioritising trust, privacy, security, and fairness, providing transparency in AI usage, and the right governance should be put in place to maintain accountability over AI algorithms. Not related, they also announced Snowpipe Streaming this week.