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<div style="display: none; max-height: 0px; overflow: hidden;">Fivetran’s acquisition of dbt, following recent integrations with Tobiko Data and Census, marks a significant consolidation </div>
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Georgetown University's <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fscs.georgetown.edu%2Fprograms%2F423%2Fonline%2Fonline-masters-in-applied-intelligence%2F%3F%26utm_source=tldr%26utm_medium=newsletter%26utm_campaign=fy26-encora-ai-en-tldr-data-gen-text-onlhp-20251016/1/01000199ec853e13-2912c0c3-3eb7-4d04-829c-cb6df397501c-000000/tWjRz448mafaFcuPIVruVROQ2G1Z81ZmBbxTend9E8s=427" rel="noopener noreferrer nofollow" target="_blank"><span>Online Master of Professional Studies in Applied Intelligence</span></a> gives you the skills needed to excel as an analyst in both the public and private sectors. Develop the critical thinking, analytical, and technical competencies to analyze complex phenomena, identify trends, and deliver actionable intelligence in fast-paced, threat-rich environments. <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fscs.georgetown.edu%2Fnews-and-events%2Fevent%2F10080%2Fapplied-intelligence-sample-class-virtual-2025-10-28%3F%26utm_source=tldr%26utm_medium=newsletter%26utm_campaign=fy26-encora-ai-en-tldr-data-event-text-vsc-20251016/2/01000199ec853e13-2912c0c3-3eb7-4d04-829c-cb6df397501c-000000/Z5UM0CRc2xhd_SQtCY_V-t2YrzPz5rKaDBhBkMLR8VA=427" rel="noopener noreferrer nofollow" target="_blank"><span>Attend a free sample class.</span></a>
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<strong>The Era of Open Data Infrastructure (6 minute read)</strong>
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Fivetran and dbt Labs are merging to create an open data infrastructure platform, anchored by Apache Iceberg as the industry-standard, engine-agnostic table format. This unified approach enables standardized, reliable data ingestion, transformation, and activation, delivering SLAs, complete lineage, and seamless portability across compute engines. The combination addresses enterprise data utilization bottlenecks, dramatically improving model trustworthiness, governance, and operational agility in analytics and AI workflows.
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<strong>Visualize Data Lineage Using Amazon SageMaker Catalog for Amazon EMR, AWS Glue, and Amazon Redshift (5 minute read)</strong>
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Amazon SageMaker Unified Studio now offers automated, end-to-end data lineage visualization across AWS Glue, Amazon Redshift, and Amazon EMR. The OpenLineage-compatible SageMaker Catalog captures and versions lineage events, enabling in-depth traceability, auditability, and historical comparisons of data transformations and asset evolution.
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<strong>Cross-Cloud Data Replication Over Private Networks with Confluent (13 minute read)</strong>
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Confluent Cloud introduces cross-cloud data replication over private networks, enabling secure, offset-preserving Kafka topic and schema mirroring across AWS, Azure, and Google Cloud using Cluster Linking and Schema Linking. This fully managed solution eliminates complex VPN setups, reduces egress costs, and ensures compliance via local data residency, supporting seamless disaster recovery with near-zero RPO and RTO.
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<div style="text-align: center;"><strong><h1>Miscellaneous</h1></strong></div>
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<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.infoq.com%2Fpresentations%2Fsystems-thinking-multi-agent-architectures%2F%3Futm_source=tldrdata/1/01000199ec853e13-2912c0c3-3eb7-4d04-829c-cb6df397501c-000000/ZfkU7BkDCgt43ZxRZwLl3acqJZKdVchPg2kZKg-Kpd8=427">
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<strong>Systems Thinking for Scaling Responsible Multi-Agent Architectures (50 minute video)</strong>
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Rapidly scaling multi-agent AI systems introduces complex, often unintended risks and feedback loops, underscoring the need for responsible engineering practices. Applying systems thinking, specifically Causal Flow Diagrams and frameworks like Cynefin, enables teams to anticipate emergent behaviors, balance efficiency vs. human impact, and dynamically adjust reward functions or guardrails. Tools such as LIME, SHAP, Arize, and telemetry can enhance observability and explainability, while architectural patterns (orchestrated, decentralized, and human-in-the-loop) should be adapted to context and risk.
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<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fcloud.google.com%2Fblog%2Fproducts%2Fstorage-data-transfer%2Fmake-your-unstructured-data-smart-with-cloud-storage%2F%3Futm_source=tldrdata/1/01000199ec853e13-2912c0c3-3eb7-4d04-829c-cb6df397501c-000000/QD1-UQ7pC2Og1KSj4WpaxfDSfwEFX8N2RaWW3DybIJE=427">
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<strong>From Dark Data to Bright Insights: The Dawn of Smart Storage (6 minute read)</strong>
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Google Cloud has unveiled auto annotate and object contexts for Cloud Storage, leveraging AI to automatically generate metadata and semantic insights for unstructured data. Auto annotate, now in experimental release, delivers object-level metadata (labels, detections, and PII flags) at scale, while object contexts provide native, flexible tagging and metadata lineage, fully integrated with Cloud Storage, IAM, and BigQuery. It is currently in a limited experimental release.
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<div style="text-align: center;"><span style="font-size: 36px;">⚡</span></div></div>
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<h1><strong>Quick Links</strong></h1>
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<strong>SQL Shader (Tool)</strong>
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DuckDB-WASM SQL Shader is a browser tool that turns SQL queries into real-time procedural graphics to explore database engine performance.
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<strong>Fact Graph (GitHub Repo)</strong>
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<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Fact Graph is a production-ready knowledge graph of US tax law for JavaScript and JVM languages.
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