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Here’s Why Automation For Data Lakes Could Be Important

Smart Data Collective

Data Lakes are among the most complex and sophisticated data storage and processing facilities we have available to us today as human beings. Analytics Magazine notes that data lakes are among the most useful tools that an enterprise may have at its disposal when aiming to compete with competitors via innovation.

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Agentic AI and AI‑ready data: Transforming consumer‑facing applications

Dataconomy

If another customer arrives with a different goal (say, browsing a category), the agent can just as easily shift to a curated, magazine-like shopping experience tailored to that individuals tastes. In short, its analytics-grade data prepared for AI. This is a radical departure from todays static UX.

AI 70
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Top Technical Skills You Must Have as a Developer in 2025

Flipboard

Data Pipelines and Orchestration : Familiarity with tools like Airflow (workflow orchestration), Kafka (real-time data processing), and ETL pipelines is critical for creating efficient data workflows. Database Management : It is crucial to have knowledge of both relational (e.g., MongoDB, Cassandra) databases.

Python 50