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How CIS Credentials Can Launch Your AI Development Career

Smart Data Collective

Ryan Ayers 10 Min Read christina wocintechchat com 6dv3pe jnsg unsplash SHARE Something that we like talking about on Smart Data Collective is how people can turn their computer information systems (CIS) background into real careers in artificial intelligence. There are over 1,897,100 software engineers in the U.S.

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Optimizing vector search using Amazon S3 Vectors and Amazon OpenSearch Service

AWS Big Data

Vector search has become essential for modern applications such as generative AI and agentic AI, but managing vector data at scale presents significant challenges. Organizations often struggle with the trade-offs between latency, cost, and accuracy when storing and searching through millions or billions of vector embeddings.

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Turning Data Into Decisions: How Analytics Improves Transportation Strategy

Smart Data Collective

SmartData Collective > Analytics > Turning Data Into Decisions: How Analytics Improves Transportation Strategy Analytics Big Data Exclusive Turning Data Into Decisions: How Analytics Improves Transportation Strategy Why 89% of top fleets now rely on data analytics - and how you can too.

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Scaling Data Reliability: The Definitive Guide to Test Coverage for Data Engineers

DataKitchen

Scaling Data Reliability: The Definitive Guide to Test Coverage for Data Engineers The parallels between software development and data analytics have never been more apparent. Let us show you how to implement full-coverage automatic data checks on every table, column, tool, and step in your delivery process.

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Amazon EMR streamlines big data processing with simplified Amazon S3 Glacier access

AWS Big Data

Amazon S3 Glacier serves several important audit use cases, particularly for organizations that need to retain data for extended periods due to regulatory compliance, legal requirements, or internal policies. Its low-cost storage model makes it economically feasible to store vast amounts of historical data for extended periods of time.

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Cloud analytics migration: how to exceed expectations

CIO Business Intelligence

A cloud analytics migration project is a heavy lift for enterprises that dive in without adequate preparation. If expectations around the cost and speed of deployment are unrealistically high, milestones are missed, and doubt over potential benefits soon takes root. But this scenario is avoidable.

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6 data risks CIOs should be paranoid about

CIO Business Intelligence

CIOs looking for cost-reduction opportunities should conduct a cost-benefit audit of third-party data sources, review utilization, and quantify risks. Observability in dataops includes monitoring data pipelines, automating responses, and tracking performance.