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

AltexSoft

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. This article explains what a data lake is, its architecture, and diverse use cases. What is a data lake?

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Moving Past ETL and ELT: Understanding the EtLT Approach

Ascend.io

Modern Cloud Data Platforms The native capabilities of the cloud providers have been joined by third-party services to offload that data into separate less costly systems that are optimized for analysis of that data. Source : A stream of sensor data represented as a directed acyclic graph.

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Data Engineering Zoomcamp – Data Ingestion (Week 2)

Hepta Analytics

We already had a script that downloaded a csv file, processed the data and pushed the data to postgres database. This week, we got to think about our data ingestion design. When the business intelligence needs change, they can go query the raw data again. The purpose of the data is not determined.

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How Windward Built Real-Time Logistics Tracking and AI Insights for the Maritime Industry

Rockset

All of these assessments go back to the AI insights initiative that led Windward to re-examine its data stack. The steps Windward takes to create proprietary data and AI insights As Windward operated in a batch-based data stack, they stored raw data in S3.

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Data Warehouse vs Data Lake vs Data Lakehouse: Definitions, Similarities, and Differences

Monte Carlo

Typically, data warehouses work best with structured data defined by specific schemas that organize your data into neat, well-labeled boxes. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

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What is Data Enrichment? Best Practices and Use Cases

Precisely

According to the 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, 77% of data and analytics professionals say data-driven decision-making is the top goal of their data programs. That’s where data enrichment comes in.

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Data Vault on Snowflake: Feature Engineering and Business Vault

Snowflake

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse?