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This week’s issue

Wednesday, Sep 30, 2026 · 13 items · new issue every Wednesday, 8am ET
The Feed is our editor’s pick across the whole data-work space this week. For news focused on your tools — including items that don’t make this general Feed — set up Personalize →
Agentic AI, MCP & the context layer 2 items
Product launchAgentic AI, MCP & the context layer
Introducing GPT-6.1 Sol
OpenAI Blog · Read source ↗

OpenAI has unveiled GPT-6.1 Sol, a new language model designed to offer near-Astra level intelligence for coding and professional tasks, but at a significantly reduced cost compared to Astra's standard API token pricing.

MyDataWork POV — The introduction of GPT-6.1 Sol at a fraction of Astra's cost might seem like a boon for budget-conscious teams, but there's a catch. The lower price point could lead to a surge in usage without the necessary guardrails, potentially overwhelming systems and amplifying errors. The risk lies in the temptation to replace human oversight with a cheaper AI solution, which could degrade the quality of work and decision-making if not managed carefully.
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Product launchAgentic AI, MCP & the context layerOpenAI
Introducing dots
OpenAI Blog · Read source ↗

OpenAI has introduced 'dots', proactive assistants designed to function across a range of complex projects and everyday tasks. These assistants aim to enhance user control and streamline workflow management.

MyDataWork POV — OpenAI's introduction of 'dots' could be a boon for those juggling multifaceted projects, where the complexity often swamps traditional task management tools. However, for organizations with streamlined operations or clear-cut tasks, 'dots' might add unnecessary complexity. The real intrigue lies in how effectively these assistants can integrate with existing workflows without creating more noise than signal. It's a tool that demands a certain operational chaos to truly shine.
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MyDataWork users could leverage AI-powered Use Case Recommendations to assess if 'dots' align with their existing workflows, especially in environments dealing with complex project management. Explore MyDataWork ↗
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Data engineering & the warehouse/lakehouse 3 items
NewsData engineering & the warehouse/lakehouseAmazon
Building an LLM-powered DAG failure analysis plugin for Amazon MWAA
AWS Big Data Blog · Read source ↗

Amazon MWAA users can now build a custom plugin to automatically analyze DAG task failures using Amazon Bedrock. This integration is designed to speed up the debugging process of Apache Airflow DAG failures across services like AWS Glue, Amazon EMR, and Amazon Athena.

MyDataWork POV — There's a lot of promise packed into the idea of an LLM-powered plugin for DAG failure analysis on Amazon MWAA. However, the unspoken truth is that automatic root cause analysis sounds deceptively easy on paper. Without clear evidence that this integration can handle the complexity of real-world data pipelines, this remains more of a theoretical solution. The burden of proof is on Amazon to demonstrate that Bedrock can navigate the nuanced failure modes of a multi-service environment.
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Product launchData engineering & the warehouse/lakehouseAWS
Announcing Spark Connect on Amazon EMR on EKS: Interactive PySpark development, anywhere
AWS Big Data Blog · Read source ↗

Amazon has announced Spark Connect on Amazon EMR on EKS, enabling interactive PySpark development across various platforms like VS Code, PyCharm, and Jupyter notebooks. This allows developers to build, test, and debug Spark applications while utilizing full-scale Spark operations on existing Amazon EKS clusters.

MyDataWork POV — Spark Connect on Amazon EMR on EKS is a strategic leap forward, especially for teams entrenched in hybrid cloud environments. By connecting interactive PySpark development with efficient Spark operations on EKS clusters, Amazon is effectively democratizing access to scalable data processing. This serves as a catalyst for innovation, not merely a convenience. However, the key challenge will be how seamlessly teams can integrate these capabilities into their existing workflows without disrupting established processes or incurring unexpected costs.
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Product launchData engineering & the warehouse/lakehouseDatabricks
Lakebase Search: State-of-the-art full text and vector search for Postgres
Databricks Blog · Read source ↗

Lakebase Search introduces advanced full text and vector search capabilities for Postgres, addressing the limitations of traditional OLTP systems in handling AI-driven search demands.

MyDataWork POV — Lakebase Search promises to retrofit Postgres with cutting-edge search capabilities, but let's not skip the hard questions. Can it truly align with the complex, evolving needs of AI agents? The claim of 'state-of-the-art' feels premature without real-world validation. Postgres is a workhorse, but adding vector search is not a magic bullet. We need to see if it can handle the scale and complexity without becoming another layer of technical debt.
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BI & analytics tools 3 items
Product launchBI & analytics toolsSnowflakePower BI
Apache Ossie: Microsoft Ecosystem Support & Power BI Converter
Snowflake · Read source ↗

Apache Ossie introduces support for the Microsoft ecosystem along with a Power BI converter, integrating with Snowflake.

MyDataWork POV — Apache Ossie's move to support the Microsoft ecosystem and offer a Power BI converter is a strategic win for data teams entrenched in Microsoft's universe. By bridging Power BI with Snowflake, it simplifies the transition for those looking to leverage Snowflake's capabilities without abandoning their existing Power BI investments. The focus extends beyond adding another tool; it involves creating a seamless flow of data between platforms, enhancing both accessibility and utility.
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MyDataWork users can benefit from Apache Ossie's integration by automatically cataloging Power BI outputs as they are converted and stored in Snowflake, ensuring that all data transformations are easily traceable and accessible without additional integration steps. Explore MyDataWork ↗
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Vendor newsBI & analytics toolsSAP
Coming Soon: A Smarter, More Transparent Feedback Experience
SAP News (Data & Analytics) · Read source ↗

SAP is promising a more intelligent and transparent system for incorporating customer feedback into their software development process. This initiative aims to enhance the way feedback is gathered and utilized to improve their products.

MyDataWork POV — SAP's pledge to refine their feedback loop sounds promising, but it's hard to ignore the vagueness surrounding 'smarter' and 'transparent.' How exactly will this feedback be gathered and analyzed? Without clear metrics or examples of past successes, it feels more like a promise than a proven capability. Transparency, in particular, is a buzzword that's easy to claim but difficult to deliver without concrete mechanisms in place. Until SAP provides specifics, skepticism remains warranted.
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ResearchBI & analytics tools
Forrester Puts Its Research Inside Microsoft Copilot, But Can It Stay Vendor-Neutral?
CX Today · Read source ↗

Forrester has integrated its research capabilities into Microsoft's Copilot, raising questions about the firm's ability to maintain vendor neutrality. This partnership aims to leverage Forrester's data insights within the Copilot environment, potentially impacting how users access and interpret analytical research.

MyDataWork POV — Forrester embedding its research within Microsoft Copilot is a double-edged sword. On one hand, it promises streamlined access to valuable insights directly within a widely-used tool. On the other, the partnership risks compromising Forrester's objectivity, as users might question the impartiality of insights delivered through a Microsoft platform. For organizations already deep in the Microsoft ecosystem, this integration could be a boon, offering seamless access to analytics. However, those outside it may view this as a potential bias, favoring vendor alignment over neutrality.
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AI platforms — data science & ML 3 items
Vendor newsAI platforms — data science & MLDatabricks
How Databricks rolls out frontier models to 12,000 employees on Day 1
Databricks Blog · Read source ↗

Databricks has introduced frontier AI models to its entire workforce of 12,000 employees on the first day of availability. This move underscores the company's commitment to integrating cutting-edge AI capabilities into its operations.

MyDataWork POV — Databricks' decision to deploy frontier AI models to all 12,000 employees immediately is a bold step that highlights the importance of democratizing AI within the enterprise. By doing so, Databricks not only accelerates innovation but also empowers its workforce with the latest tools to drive data-driven decisions. This approach reflects a broader trend where AI is woven into the fabric of everyday business operations, moving beyond isolated deployments to become a core component of enterprise strategy. Yet, the real value lies in how these models will be utilized to enhance productivity and insight across diverse teams.
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MyDataWork users could leverage this approach by ensuring their data assets are seamlessly cataloged and accessible, enhancing collaboration and enabling quicker adoption of new AI capabilities across the organization. Explore MyDataWork ↗
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Product launchAI platforms — data science & MLTeradata
Teradata (TDC) Unveils AI Coworker As Fair Value Narrative Stays In Focus
simplywall.st · Read source ↗

Teradata has introduced an AI Coworker feature, aligning with its focus on maintaining fair value in the market. This development aims to enhance the company's AI capabilities and support its strategic objectives.

MyDataWork POV — Teradata's AI Coworker brings to the forefront significant concerns regarding the potential for over-reliance on automated systems in complex data environments. While AI promises efficiency, it risks sidelining the nuanced judgment of human analysts who understand the intricacies of data interpretation. The danger lies in assuming that AI can fully replace human insight, potentially leading to oversimplified decision-making processes that ignore critical context and subtleties. It's a reminder that AI should augment, not replace, human expertise.
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MyDataWork users can leverage AI-powered features like Use Case Recommendations and automation candidate identification to ensure AI complements their workflows, enhancing rather than overshadowing human expertise. Explore MyDataWork ↗
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AnalysisAI platforms — data science & MLSAS
AI ethics and SAS Models: Designing models with trust, transparency, and accountability
SAS Blogs · Read source ↗

The article discusses the importance of ethical considerations in AI model design, focusing on SAS Models. It highlights SAS's commitment to trust, transparency, and accountability in their model development process.

MyDataWork POV — SAS's commitment to embedding ethical principles in their AI models is a refreshing counter to the usual tech race. By prioritizing trust and transparency, SAS sets a standard others should follow. In a market often driven by speed over substance, emphasizing responsible innovation is a necessary shift. This approach highlights the necessity for AI systems to be built with integrity, ensuring they serve users while upholding ethical standards. It's a model for how AI should be crafted: thoughtfully and with accountability.
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Governance, catalog & semantic layer 2 items
ResearchGovernance, catalog & semantic layer
Towards safety cases for frontier AI training
OpenAI Blog · Read source ↗

The guidelines for safety cases in frontier AI training focus on implementing technical safeguards, improving operational practices, and examining incidents of misalignment.

MyDataWork POV — Safety cases for frontier AI training serve as a critical backbone for trust in AI systems rather than merely a checklist. By emphasizing technical safeguards and operational practices, these guidelines aim to prevent misalignment incidents before they become crises. Yet, the challenge lies in how these guidelines translate into everyday practice. Without diligent adherence, even the best frameworks risk becoming mere formalities, sidelining the very safety they intend to ensure.
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Vendor newsGovernance, catalog & semantic layerSAPNVIDIA
SAP and NVIDIA OpenShell: Working Toward Governance and Security for Auditable AI Agents in Enterprise Systems
SAP News (Data & Analytics) · Read source ↗

SAP and NVIDIA are collaborating on OpenShell to enhance governance and security for AI agents in enterprise systems, focusing on creating an auditable execution layer.

MyDataWork POV — The collaboration between SAP and NVIDIA on OpenShell is a significant step in enterprise AI. By focusing on governance and security, they are addressing the often-overlooked execution layer, which is essential for ensuring that AI agents operate within defined boundaries. This partnership is significant because it recognizes the need for a solid framework to manage AI agents, rather than deploying them indiscriminately. The emphasis on auditable processes could set a new standard for enterprise AI deployment.
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Agent Studio users can leverage its scoping capabilities to ensure that any AI agent use case aligns with governance and security standards, as highlighted by the SAP and NVIDIA collaboration. Explore MyDataWork ↗
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