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

phData: Data Engineering

Cost reduction by minimizing data redundancy, improving data storage efficiency, and reducing the risk of errors and data-related issues. Data Governance and Security By defining data models, organizations can establish policies, access controls, and security measures to protect sensitive data.

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

AltexSoft

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

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Data Lakehouse: Concept, Key Features, and Architecture Layers

AltexSoft

In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store.

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What is Data Fabric: Architecture, Principles, Advantages, and Ways to Implement

AltexSoft

What is data fabric? A data fabric is an architecture design presented as an integration and orchestration layer built on top of multiple disjointed data sources like relational databases , data warehouses , data lakes, data marts , IoT , legacy systems, etc., How data fabric works.

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Data Collection for Machine Learning: Steps, Methods, and Best Practices

AltexSoft

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Note, though, that not any type of web scraping is legal.

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What is Data Hub: Purpose, Architecture Patterns, and Existing Solutions Overview

AltexSoft

A data hub serves as a single point of access for all data consumers, whether it be an application, a data scientist, or a business user. So, it also allows for managing data for various tasks, providing centralized governance and data flow control capabilities. Data hub architecture.

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

Rockset

For one, the company decided to invest in an API Insights Lab where customers and partners across suppliers, carriers, governments and insurance companies could use maritime data as part of their internal systems and workflows. As a result, Windward wanted an underlying data stack that took an API first approach.