Remove Data Lakes Remove Data Observability Remove Data Science
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5 Fast-Growing Data Management Trends in 2023

ODSC - Open Data Science

Data Mesh More data management systems in 2023 will also shift toward a data mesh architecture. This decentralized architecture breaks data lakes into smaller domains specific to a given team or department. Automation and artificial intelligence (AI) will see particular growth in the realm of observability.

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Highlights from the Data Engineering Summit Now Available On Demand

ODSC - Open Data Science

It also addresses the strategies and best practices for implementing a data mesh. Applying Engineering Best Practices in Data Lakes Architectures Einat Orr | Ceo and Co-Founder | Treeverse This talk examines why agile methodology, continuous integration, and continuous deployment and production monitoring are essential for data lakes.

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Popular Machine Learning Libraries, Ethical Interactions Between Humans and AI, and 10 AI Startups…

ODSC - Open Data Science

Automating Remediation Processes for Data Security Posture Management Before we look into how we can automate it, it is important to understand how data security posture management helps you achieve your goals.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

With built-in components and integration with Google Cloud services, Vertex AI simplifies the end-to-end machine learning process, making it easier for data science teams to build and deploy models at scale. Metaflow Metaflow helps data scientists and machine learning engineers build, manage, and deploy data science projects.

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Build Data Pipelines: Comprehensive Step-by-Step Guide

Pickl AI

Common options include: Relational Databases: Structured storage supporting ACID transactions, suitable for structured data. NoSQL Databases: Flexible, scalable solutions for unstructured or semi-structured data. Data Warehouses : Centralised repositories optimised for analytics and reporting.