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

phData: Data Engineering

With many data modeling methodologies and processes available, choosing the right approach can be daunting. This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake?

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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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4 Ways Automation Helps Data Engineering Teams

Monte Carlo

In this article, we will explore how automation can help data engineering teams overcome these challenges and provide a more seamless and effective data management process. Automated processes scan all data stores and discover data, including semi-structured data such as JSON on a continual basis.

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Top Data Lake Vendors (Quick Reference Guide)

Monte Carlo

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. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

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Data Governance: Concept, Models, Framework, Tools, and Implementation Best Practices

AltexSoft

As the amount of enterprise data continues to surge, businesses are increasingly recognizing the importance of data governance — the framework for managing an organization’s data assets for accuracy, consistency, security, and effective use. What is data governance? billion in 2020 to $5.28

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

Monte Carlo

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

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Data Mesh Implementation: Your Blueprint for a Successful Launch

Ascend.io

Process: Building Robust Systems from Data Governance to Product Publishing Just as a well-oiled machine needs precise processes, a successful data mesh needs to establish and adhere to processes regarding data governance, data curation, and data product publishing.