# data-governance Processes for formally managing enterprise data assets and establishing authority, management, and decision-making parameters for data. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Mistral raises EUR 3B to make sovereign, open-weight AI the technology frontier DevFeed: [Mistral raises EUR 3B to make sovereign, open-weight AI the technology frontier]() Original publisher: [Read original article]() Published: 2026-09-08T12:00:22Z Content type: news Language: en Sources: [Mistral AI Blog]() Topics: [AI Chat](), [data-governance](), [samsung]() Tags: [ai](), [data-governance](), [generative-ai](), [open](), [samsung]() ### AI overview Mistral announced a EUR 3 billion Series D round to expand frontier AI research, compute capacity, infrastructure, and international commercial growth. The article presents its open-weight, full-stack approach as a way for organizations to retain control over data, models, compute, and production systems. ### Source excerpt Mistral today announced that it has raised EUR 3 billion in a Series D funding round at a post-money valuation of more than EUR 21 billion. ## ISO 42001 Evidence: What Auditors Ask For DevFeed: [ISO 42001 Evidence: What Auditors Ask For]() Original publisher: [Read original article]() Author: info@goteleport.com (Preet Dhatt) Published: 2026-09-03T00:00:00Z Content type: article Language: en Sources: [Teleport]() Topics: [audit](), [AI Development](), [Deployment](), [CI/CD](), [data-governance](), [Monitoring](), [Requirements]() Tags: [ai](), [ai-development](), [article](), [audit](), [ci-cd](), [data-governance](), [deployment](), [eu](), [iso](), [monitoring](), [requirements]() ### AI overview This article explains what auditors look for in ISO 42001 evidence and how organizations can connect access, approvals, infrastructure, CI/CD activity, releases, and production changes into an evidence trail. It also discusses monitoring, human oversight, third-party access, and data governance within an AI Management System. ### Source excerpt Prepare ISO 42001 audit evidence that proves your controls work in practice. ## Navigating SAMA, ADGM & DFSA Requirements with Teleport DevFeed: [Navigating SAMA, ADGM & DFSA Requirements with Teleport]() Original publisher: [Read original article]() Author: info@goteleport.com (Mukund Cadambi) Published: 2026-08-12T00:00:00Z Content type: article Language: en Sources: [Teleport]() Topics: [Requirements](), [Cybersecurity](), [Cloud](), [audit trail](), [data-governance](), [Architecture & Design]() Tags: [audit-trail](), [cloud](), [compliance](), [cybersecurity](), [data-governance](), [requirements](), [security]() ### AI overview This article explains how SAMA, ADGM, and DFSA requirements affect cloud service providers operating in Saudi Arabia and the UAE. It describes challenges involving data sovereignty, cybersecurity, identity and access controls, privileged and third-party access, and audit evidence, and presents a unified identity layer as an approach to operationalizing compliance. ### Source excerpt Learn how Teleport helps CSPs meet SAMA, ADGM, and DFSA compliance. ## Announcing Confluent Platform 8.3: Powerful Apache Flink® SQL operations, Easier KRaft Migrations, Expanded Monitoring and more. DevFeed: [Announcing Confluent Platform 8.3: Powerful Apache Flink® SQL operations, Easier KRaft Migrations, Expanded Monitoring and more.]() Original publisher: [Read original article]() Author: Premika Srinivasan Published: 2026-07-29T15:00:10Z Content type: release Language: en Sources: [Confluent: Data in motion]() Topics: [apache-flink](), [Kafka](), [Monitoring](), [data-governance](), [Model Context Protocol](), [Claude Code](), [codex]() Tags: [apache-flink](), [apache-kafka](), [claude-code](), [codex](), [confluent](), [confluent-platform](), [data-governance](), [mcp](), [mcp-server](), [monitoring]() ### AI overview Confluent Platform 8.3.0, built on Apache Kafka 4.3.0, adds simplified Apache Flink SQL operations, expanded monitoring through Unified Stream Manager, easier KRaft migration, and structured governance for data in motion. The release also introduces an MCP server for Confluent Platform for Apache Flink, allowing AI agents such as Claude Code and Codex to inspect and manage Flink resources through existing security controls. ### Source excerpt Announcing Confluent Platform 8.3: Powerful Apache Flink® SQL operations, Easier KRaft Migrations, Expanded Monitoring and more ## AWS Weekly Roundup: Local Zone in Athens, Claude Opus 5 on AWS, Lambda durable execution for .NET, and more (July 27, 2026) DevFeed: [AWS Weekly Roundup: Local Zone in Athens, Claude Opus 5 on AWS, Lambda durable execution for .NET, and more (July 27, 2026)]() Original publisher: [Read original article]() Author: Daniel Abib Published: 2026-07-27T14:54:41Z Content type: news Language: en Sources: [AWS News Blog]() Topics: [Amazon Web Services](), [AWS Local Zones](), [Latency](), [Amazon Bedrock](), [Amazon EC2](), [Amazon S3](), [Claude](), [cloud-infrastructure](), [Amazon Elastic Container Service](), [anthropic](), [data-governance]() Tags: [amazon-bedrock](), [amazon-bedrock-agentcore](), [amazon-connect](), [amazon-ec2](), [amazon-s3](), [amazon-sagemaker-ai](), [announcements](), [anthropic](), [aws](), [aws-lambda](), [aws-local-zones](), [claude](), [data-governance](), [latency](), [news](), [week-in-review]() ### AI overview An AWS weekly roundup covering a new Local Zone in Athens, Greece, and selected AWS launches and updates, including Claude Opus 5 on Amazon Bedrock. The article highlights local data processing, data residency, low latency, and infrastructure for regional workloads. ### Source excerpt Last week I had the privilege of spending three days in São Paulo with technical builders from across Latin America, brought together for a regional tech event full of deep-dive sessions, hands-on workshops, and conversations with customers and partners. What struck me most wasn't any single session, it was the energy of a technical community [...] ## How TEFCA is impacting platform engineering in Healthcare DevFeed: [How TEFCA is impacting platform engineering in Healthcare]() Original publisher: [Read original article]() Author: Marc Mangus Published: 2026-07-23T05:40:01Z Content type: opinion Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [Architecture & Design](), [data-governance](), [API](), [Orchestration]() Tags: [api](), [architecture](), [compliance](), [engineering](), [governance](), [healthcare](), [orchestration](), [platform](), [platform-engineering](), [policy](), [regulatory]() ### AI overview The article argues that TEFCA is making healthcare data-exchange compliance effectively mandatory, creating substantial platform-engineering challenges. Teams must address consent management, data governance, purpose-of-use restrictions, audit trails, varying state privacy laws, and differing QHIN interpretations. It advocates composable architectures and policy-as-code approaches to manage this complexity at scale. ### Source excerpt TEFCA is turning "voluntary" healthcare data exchange into de facto mandatory compliance - forcing platform teams to rebuild consent, governance, and multi-state policy controls. Here's how to scale it with policy-as-code. ## The data platform 1Password needed didn't exist. So we built it. DevFeed: [The data platform 1Password needed didn't exist. So we built it.]() Original publisher: [Read original article]() Author: info@1password.com (Wayne Duso; Mandy Gu; and Amie Bright) Published: 2026-07-22T00:00:00Z Content type: article Language: en Sources: [Blog on 1Password Blog]() Topics: [data](), [Data Infrastructure](), [data-governance](), [real-time](), [Unified Access](), [Artificial Intelligence]() Tags: [agentic](), [ai](), [building-1password](), [data](), [data-governance](), [data-infrastructure](), [developers](), [real-time](), [sql](), [systems](), [unified-access](), [workflows]() ### AI overview 1Password describes building an internal data platform to make business data accessible, trustworthy, and available in real time across product, finance, engineering, analytics, SQL, APIs, dashboards, and AI workflows. The effort addresses bottlenecks caused by a centralized data lake, bespoke pipelines, and tightly coupled storage, governance, and compute. ### Source excerpt Consider a few tasks that take place across every business, every day: A product team ships a feature and wants to know if customers are using it successfully. A finance team needs customer and account information for planning. An analyst needs definitions to create a report. An AI assistant needs operational context to answer a business question. Those sound like different workflows, but they all rely on the same underlying data. And each one of these actors, across each of these teams, needs that data to be both accessible and trustworthy. At 1Password, trust is at the center of everything we build. Millions of people and businesses rely on us to protect the credentials, secrets, and access workflows that power modern work. The same principle applies to our own internal data. As our products, systems, and use of AI evolved, data became a shared dependency across the business. It powers everything from Unified Access andsecure agentic access patterns for customers, to the workflows used by product, finance, and engineering teams. As those systems grew, so did the number of people and applications that depended on our internal data. But our data infrastructure did not respond well to this. We had built a centralized data lake supported by a growing collection of bespoke data pipelines and one-off solutions. Each new use case required another integration or transformation. Over time, the data platform became a bottleneck: teams turned to CSVs to move faster, and data engineers spent more time maintaining pipelines than enabling new capabilities. What we learned was that manually moving data was no longer enough. Data needs to be available in real time, accessible wherever it's needed, and trusted through the forms our customers need, whether that is through SQL, APIs, dashboards or AI workflows. Privacy and governance need to be built into data the moment it's created so every downstream use remains secure and unambiguous by design. This is the foundation we're build ## Announcing Upvest as Confluent's 2026 EMEA Data Streaming Startup of the Year DevFeed: [Announcing Upvest as Confluent's 2026 EMEA Data Streaming Startup of the Year]() Original publisher: [Read original article]() Author: Tim Graczewski Published: 2026-07-16T00:07:01Z Content type: article Language: en Sources: [Confluent: Data in motion]() Topics: [Streaming](), [real-time](), [Resilience](), [event driven](), [Scalability](), [Cloud](), [data-governance](), [Microservices](), [Architecture & Design](), [Disaster Recovery]() Tags: [2026](), [cloud](), [cloud-native](), [compliance](), [confluent](), [confluent-cloud](), [data](), [data-governance](), [disaster-recovery](), [emea](), [event-driven](), [fintech](), [infrastructure](), [microservices](), [real-time](), [resilience](), [revolut](), [scalability](), [startup](), [streaming]() ### AI overview Confluent recognizes Berlin-based Upvest as its inaugural EMEA Data Streaming Startup of the Year. The article describes Upvest's real-time, event-driven fintech infrastructure, which supports embedded investments, client onboarding, data governance, disaster recovery, scalability, and regulatory resilience for major financial institutions. ### Source excerpt Confluent for Startups provides an easy on-ramp to Confluent Cloud for early stage startups with great data streaming use cases. ## Introducing the OpenAI Economic Research Exchange DevFeed: [Introducing the OpenAI Economic Research Exchange]() Original publisher: [Read original article]() Published: 2026-06-08T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [OpenAI](), [data-governance](), [jobs](), [data]() Tags: [ai](), [company](), [data](), [data-governance](), [economics](), [external](), [jobs](), [openai](), [research]() ### AI overview OpenAI is launching the Economic Research Exchange, a platform for structured collaborations with external researchers studying AI's economic effects on workers, firms, institutions, and the broader economy. Selected projects may use privacy-protected OpenAI tools and datasets under defined milestones, data governance, and review processes. ### Source excerpt OpenAI launches the Economic Research Exchange to study AI's impact on jobs, productivity, and the economy. Applications are now open for selected research projects. ## EU AI Act Compliance: Requirements, Risks, and What to Document DevFeed: [EU AI Act Compliance: Requirements, Risks, and What to Document]() Original publisher: [Read original article]() Author: info@goteleport.com (Kayne McGladrey, CISSP) Published: 2026-04-15T00:00:00Z Content type: tutorial Language: en Sources: [Teleport]() Topics: [Artificial Intelligence](), [Requirements](), [Documentation](), [audit](), [data-governance](), [Logging](), [Monitoring](), [Deployment](), [data]() Tags: [ai](), [compliance](), [cybersecurity](), [data](), [data-governance](), [dataset](), [deployment](), [development](), [documentation](), [eu](), [iso-27001](), [lifecycle](), [logging](), [monitoring](), [nist](), [real-time](), [reproducibility](), [soc-2](), [versioning]() ### AI overview A practical guide to EU AI Act compliance covering requirements, risks, technical documentation, logging, data governance, lifecycle evidence, traceability, monitoring, and human oversight. It outlines key compliance milestones from August 2025 through August 2027. ### Source excerpt Cut through EU AI Act complexity with practical guidance on requirements, risks, and documentation. ## CockroachDB v26.1 Adds Security and Compliance Features DevFeed: [CockroachDB v26.1 Adds Security and Compliance Features]() Original publisher: [Read original article]() Author: David Bressler Published: 2026-02-03T00:00:00Z Content type: release Language: en Sources: [Cockroach Labs]() Topics: [CockroachDB](), [Security](), [data-governance](), [Zero Trust](), [Cloud](), [Databases](), [JSON Web Tokens](), [OpenID connect (OIDC)](), [Self-hosted](), [Azure]() Tags: [azure](), [cloud](), [cockroachdb](), [compliance](), [data-governance](), [database](), [encryption](), [jwt](), [oidc](), [security](), [self-hosted](), [zero-trust]() ### AI overview CockroachDB v26.1 introduces security and compliance improvements for CockroachDB Cloud and self-hosted deployments. The release includes data governance and zero-trust access controls for AI agents, expanded HIPAA and PCI/DSS compliance participation on Azure, and identity integrations using JWT and OpenID Connect. ### Source excerpt Enterprise security is a key factor in reducing cost-of-ownership and getting new solutions into production efficiently. With CockroachDB v26.1, available as of February 3rd in CockroachDB Cloud and February 18th for CockroachDB self-hosted, we are introducing security improvements that help organizations integrate CockroachDB more seamlessly with their existing security infrastructure. ## How to optimize real-time data ingestion in Snowflake and Iceberg DevFeed: [How to optimize real-time data ingestion in Snowflake and Iceberg]() Original publisher: [Read original article]() Author: Sesethu Mhlana Published: 2026-01-21T00:00:00Z Content type: article Language: en Sources: [Redpanda]() Topics: [real-time](), [Apache Iceberg](), [Streaming](), [Kafka](), [data-governance](), [systems]() Tags: [cost](), [data](), [data-governance](), [high-availability](), [infrastructure](), [integration](), [kafka](), [monitoring](), [performance](), [pipelines](), [real-time](), [schema](), [storage](), [streaming]() ### AI overview This guide explains how architectural inefficiencies in real-time data ingestion can increase Snowflake credits, storage costs, and query delays. It focuses on streaming pipelines involving Apache Iceberg and describes the infrastructure overhead of Kafka deployments, including brokers, coordination services, connectors, schema registries, and monitoring. ### Source excerpt Learn about the hidden costs of real-time data ingestion and practical strategies to optimize your streaming infrastructure. ## Streaming IoT and event data into Snowflake and ClickHouse DevFeed: [Streaming IoT and event data into Snowflake and ClickHouse]() Original publisher: [Read original article]() Author: Mdu Sibisi Published: 2025-12-09T00:00:00Z Content type: tutorial Language: en Sources: [Redpanda]() Topics: [Internet of things](), [Streaming](), [Redpanda-Connect](), [clickhouse](), [data observability](), [Compression](), [data-governance](), [DataOps](), [Database]() Tags: [clickhouse](), [cloud-storage](), [compliance](), [data](), [data-governance](), [event](), [iot](), [pipelines](), [redpanda-connect](), [streaming]() ### AI overview A guide to streaming IoT and event data through Redpanda and Redpanda Connect into Snowflake and ClickHouse. It compares ClickHouse for real-time analysis with Snowflake for scalable cloud storage, historical reporting, and querying, while discussing governance, compression, data freshness, and robust pipeline design. ### Source excerpt Learn how to stream IoT and event data into Snowflake and ClickHouse using Redpanda ## OpenAI named Emerging Leader in Generative AI DevFeed: [OpenAI named Emerging Leader in Generative AI]() Original publisher: [Read original article]() Published: 2025-11-17T10:00:00Z Content type: release Language: en Sources: [OpenAI News]() Topics: [OpenAI](), [Generative AI](), [ChatGPT](), [data-governance](), [Monitoring]() Tags: [2025](), [chatgpt](), [company](), [enterprise](), [generative-ai](), [governance](), [monitoring](), [openai]() ### AI overview OpenAI announces that Gartner named it an Emerging Leader in the 2025 Innovation Guide for Generative AI Model Providers. The article links this recognition to OpenAI's enterprise adoption, reporting that more than 1 million companies use its platform and that ChatGPT Enterprise seats have grown ninefold year over year. It also highlights privacy controls, data governance, data residency, monitoring, and evaluations for safer AI deployment. ### Source excerpt OpenAI has been named an Emerging Leader in Gartner's 2025 Innovation Guide for Generative AI Model Providers. The recognition reflects our enterprise momentum, with over 1 million companies building with ChatGPT. ## Announcing General Availability of ClickHouse BYOC (Bring Your Own Cloud) on AWS DevFeed: [Announcing General Availability of ClickHouse BYOC (Bring Your Own Cloud) on AWS]() Original publisher: [Read original article]() Author: ClickHouse Published: 2025-02-20T00:00:00Z Content type: news Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [Amazon VPC](), [Amazon Web Services](), [Cloud](), [Deployment](), [autoscaling](), [data-governance]() Tags: [availability](), [aws](), [byoc-deployment](), [clickhouse](), [cloud](), [cloud-native](), [compliance](), [data-governance](), [scale](), [security](), [vpc]() ### AI overview The article announces the general availability of ClickHouse BYOC on AWS, a fully managed ClickHouse Cloud service deployed in a customer's own AWS account and VPC. Customer data, compute, storage, cache, and backups remain within the customer's VPC, supporting security, compliance, governance, workload isolation, scaling, and lower infrastructure costs. ### Source excerpt Today, we announce the GA of ClickHouse BYOC on AWS. A fully managed ClickHouse Cloud service deployed in your own AWS account. Designed for large-scale deployments, with personalized support and onboarding. SOC 2 and ISO 27001 aligned. ## Data Inventory DevFeed: [Data Inventory]() Original publisher: [Read original article]() Author: Ritesh Modi Published: 2025-02-19T14:24:14Z Content type: tutorial Language: en Sources: [Wise Engineering - Medium]() Topics: [data-governance](), [data-architecture](), [Security & Privacy](), [Databases](), [Provisioning](), [Terraform]() Tags: [backend](), [data](), [data-governance](), [databases](), [frontend](), [governance](), [least-privilege](), [network-segmentation](), [platform](), [provisioning](), [security](), [security-privacy](), [terraform]() ### AI overview Wise's Data Governance team describes Data Inventory, a catalog of data assets that records their locations and security or privacy controls. The article explains the system's constraints, design outcomes, and process for discovering operational databases and their metadata. ### Source excerpt The Data Governance team, part of Data Platform, develops and operates platform products through which autonomous teams can govern their data. The team's vision is to democratise data in a secure and compliant manner. Data Inventory was the team's first product. What is Data Inventory? A data inventory is an extensive catalog of the Wise's data assets. It helps us understand where the data is located and what kind of security / privacy controls are in place. This is also a requirement for ISO 27001:2022. What are the constraints? Any system has to work well with our controls and way-of-working. This led to following constraints: It shall be built in a way that satisfies our security controls such as network segmentation, least privilege access, secure secret management, etc. It shall be easy to integrate with other in-house platforms to provide cohesive experience. It shall be built to connect with heterogeneous and fragmented infrastructure. Many data systems are built through off-the-shelf or managed service offering but others are built & operated in-house. The system shall be integrated by default with technology provided by Data Platform. On another hand, it shall be extensible enough to integrate with data systems not maintained by Data Platform. How did we build our inventory? At high level, we split this into 4 main outcomes: 1. Register assets at correct granularity. 2. Identify the correct owner and make them accountable for the life cycle. 3. Extract the schema of the data asset. 4. Classify the asset with correct sensitivity. This is how design looks at high level: To achieve the above design and outcome, we follow the following steps: Step 0: Discover data systems network metadata Scanners need to be aware of the network metadata before doing scanning. For example: - What is the host or connection string? - What is the technology of the data system? - What is the name of the data system? Let us take an example of how we solve it in our operational datab ## Guest Post: Securing the Foundation of Dynamic Data Governance at Velotix DevFeed: [Guest Post: Securing the Foundation of Dynamic Data Governance at Velotix]() Original publisher: [Read original article]() Published: 2025-02-19T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [data-governance](), [chainguard images](), [Security](), [Vulnerabilities](), [Amazon OpenSearch Service](), [Kafka]() Tags: [case-study](), [chainguard](), [chainguard-images](), [common-vulnerabilities-and-exposures](), [guest-post](), [performance](), [productivity](), [security](), [time](), [velotix](), [vulnerabilities](), [zero-cves]() ### AI overview A guest post explains how Velotix uses Chainguard Images to reduce CVEs across its data-governance platform. The article describes challenges with vendor-provided images and dependency upgrades, and highlights scheduled recompilation to keep infrastructure-level libraries current. ### Source excerpt Velotix utilizes Chainguard Images to help reduce CVEs, improve performance, and save time. Learn how Chainguard helps them build a more secure infrastructure. ## How to sell MLOps in large Organizations DevFeed: [How to sell MLOps in large Organizations]() Original publisher: [Read original article]() Author: Raphaël Hoogvliets Published: 2024-02-07T09:36:58Z Content type: tutorial Language: en Sources: [Raphaël Hoogvliets]() Topics: [MLOps](), [data-governance](), [Security]() Tags: [how-to](), [mlops](), [organizations](), [stakeholder-management](), [strategy]() ### AI overview This article offers practical advice for gaining management buy-in for MLOps initiatives in non-technical organizations where machine learning is still viewed as a nice-to-have. It argues that MLOps is often overlooked despite helping keep data investments and ML results available, dependable, and tested. ### Source excerpt A toolbox for strategy and stakeholder management ## Heroku Private Spaces Global Expansion: Canada, India, Singapore, and the UK DevFeed: [Heroku Private Spaces Global Expansion: Canada, India, Singapore, and the UK]() Original publisher: [Read original article]() Author: Ethan Limchayseng Published: 2023-08-31T21:00:00Z Content type: release Language: en Sources: [Heroku]() Topics: [Heroku](), [spaces](), [Availability](), [data-governance](), [Network]() Tags: [apac](), [apache-kafka](), [aws](), [canada](), [cloud-infrastructure](), [data](), [dynos](), [heroku](), [heroku-shield](), [india](), [kafka](), [london](), [news](), [platform-updates](), [private-spaces](), [uk]() ### AI overview Heroku announces general availability for Private Spaces in India and Canada, plus new regions in the United Kingdom and Singapore. The expansion supports data-location control and includes services such as Heroku Postgres, Apache Kafka on Heroku, Heroku Data for Redis, Heroku Connect, and most Heroku Add-ons. ### Source excerpt In May 2023, we announced our limited release of two new Heroku Private Spaces regions: India (Mumbai) and Canada (Montreal). This month, we're announcing the full general availability of those two regions, along with new Heroku Private Spaces regions for the United Kingdom (London) and Singapore. This expansion enables customers to maintain greater control over [...] The post Heroku Private Spaces Global Expansion: Canada, India, Singapore, and the UK appeared first on Heroku. ## Lakehouse summer camp at Trino Fest 2023 DevFeed: [Lakehouse summer camp at Trino Fest 2023]() Original publisher: [Read original article]() Author: Brian Olsen Published: 2023-04-05T00:00:00Z Content type: news Language: en Sources: [Trino Blog]() Topics: [data-architecture](), [Query (disambiguation)](), [data-governance](), [SQL](), [Data Space](), [Apache Iceberg]() Tags: [analytics](), [collaboration](), [community](), [conference](), [data-governance](), [data-lake](), [education](), [event](), [latest-features](), [sql](), [tools-and-integrations](), [trends]() ### AI overview Trino Fest 2023 is a virtual two-day event focused on Trino as a data lakehouse query engine and on improving data lakehouse management. The event emphasizes education, community collaboration, and practical insights into Trino, its ecosystem, and data and analytics platforms. ### Source excerpt Get ready to kick off your summer with Commander Bun Bun at Trino Fest 2023! This year's event is going virtual and will take place over two days, the 14th and 15th of June. The focus of the event will be on Trino as a data lakehouse query engine, with discussions on how new features and the ecosystem around Trino can support better data lakehouse management. Trino Fest 2023 is the new annual summer event dedicated to all things Trino. Building on the success of last year's Cinco de Trino, we're excited to bring the community together once again to explore the latest trends and innovations in Trino and data lakehouse management. With a focus on education, community collaboration, and inspiration, Trino Fest 2023 will be a valuable experience for anyone interested in improving their data and analytics platform. We hope to see you there as attendee, speaker, or sponsor! Read below to find out how to sign up. ## My first weeks at Acer Europe DevFeed: [My first weeks at Acer Europe]() Original publisher: [Read original article]() Published: 2022-10-16T00:00:00Z Content type: opinion Language: en Sources: [Mutt0-ds Notes]() Topics: [Azure](), [dashboards](), [Databases](), [etl](), [DevOps](), [Purview](), [active directory](), [data-governance]() Tags: [active-directory](), [azure](), [dashboards](), [data-governance](), [databases](), [developer](), [devops](), [etl](), [purview]() ### AI overview A Business Intelligence Developer reflects on their first weeks at Acer Europe, describing the transition from a small company to a large IT organization. The post covers the scale of its data, reporting, ETL, Azure services, and cross-team work, along with the information overload and learning challenges of the first week. ### Source excerpt This is a post for my future self when I will be asking myself: "How were my first days at Acer like?". Note: I'm working at Acer EMEA HQ,... ## Airflow Summit 2022 DevFeed: [Airflow Summit 2022]() Original publisher: [Read original article]() Author: Apache Airflow Published: 2022-05-16T00:00:00Z Content type: news Language: en Sources: [Apache Airflow Blog]() Topics: [airflow](), [Data pipelines](), [data-governance](), [Open Source](), [AI, ML & Data Engineering]() Tags: [airflow-summit](), [apache-airflow](), [community](), [data-governance](), [data-pipelines](), [events](), [machine-learning](), [network](), [open-source](), [summit]() ### AI overview Airflow Summit 2022 was scheduled for May 23-27 as a free conference for Apache Airflow practitioners and data leaders. The program covered Airflow practices, data pipelines, data governance, machine learning, the project's future, and non-code open-source contributions. ### Source excerpt The biggest Airflow Event of the Year returns May 23-27! Airflow Summit 2022 will bring together the global community of Apache Airflow practitioners and data leaders. What's on the Agenda During the free conference, you will hear about Apache Airflow best practices, trends in building data pipelines, data governance, Airflow and machine learning, and the future of Airflow. There will also be a series of presentations on non-code contributions driving the open-source project. How to Attend This year's edition will include a variety of online sessions across different time zones. Additionally, you can take part in local in-person events organized worldwide for data communities to watch the event and network. Interested? 🪶 Register for Airflow Summit 2022 today 🤝 Check out the in-person events planned for Airflow Summit 2022. ## The Journey of Corpus DevFeed: [The Journey of Corpus]() Original publisher: [Read original article]() Published: 2021-04-29T00:00:00Z Content type: article Language: en Sources: [SoundCloud Backstage Blog]() Topics: [data-governance](), [BigQuery](), [Data Quality](), [Data Management](), [Amazon Redshift](), [datasets](), [data]() Tags: [amazon-redshift](), [bigquery](), [data](), [data-engineering](), [data-governance](), [data-management](), [data-quality](), [datasets]() ### AI overview SoundCloud describes its effort to replace an outdated, poorly documented data warehouse and inconsistent ETL processes with Corpus, a centralized BigQuery project serving as a single source of truth. The Data Corpus team focuses on applying data governance to datasets critical for product and business decisions, including maintaining high data quality throughout the data lifecycle. ### Source excerpt It seems like a simple enough concept: You take data from how your users interact with your product, and you use it to make business and... ## How We're Solving Data Discovery Challenges at Shopify DevFeed: [How We're Solving Data Discovery Challenges at Shopify]() Original publisher: [Read original article]() Author: Ranko Cupovic Published: 2020-07-21T18:14:00Z Content type: article Language: en Sources: [Shopify Engineering](), [Shopify Engineering - Shopify Engineering]() Topics: [data](), [Shopify](), [data-governance](), [data-architecture](), [dashboards]() Tags: [accessibility](), [dashboards](), [data](), [data-governance](), [github](), [logs](), [pipelines](), [shopify](), [slack]() ### AI overview Shopify describes Artifact, a data discovery and management tool built to catalog data assets and metadata. The article discusses the challenges of data growth, asset discovery, governance, and accessibility, and reports that Artifact reduced the share of Shopify's Data team saying discovery hindered delivery from 80% to 41%. ### Source excerpt Humans generate a lot of data. Every two days we create as much data as we did from the beginning of time until 2003! The International Data Corporation estimates the global datasphere totaled 33 zettabytes (one trillion gigabytes) in 2018. The estimate for 2025 is 175 ZBs, an increase of 430%. This growth is challenging organizations across all industries to rethink their data pipelines. [Next page]()