|
By Navita Sood
The lakehouse architecture was developed with the mission to combine the unstructured scale of the data lake with the structured performance of the data warehouse. This shift unified enterprise data and delivered the first true "single source of truth". But in 2026, the mission has expanded.
|
By Charu Anchlia
Autonomous agents act toward complex goals without requiring human direction at each step. In enterprise environments, deploying these agents introduces a more exacting set of challenges: they must navigate heterogeneous data systems; satisfy compliance, audit, and data sovereignty mandates; and keep all data within the organization's operational boundary.
|
By Jeremiah Morrow
In today's state, local, and education (SLED) environments—especially higher education—budgets are under constant scrutiny, and the demand for data excellence is constant. That means doing more with fewer resources. One high-impact change to your data workflows that can transform the quality of your data and AI while lowering costs is automating and documenting data lineage.
|
By Stephen Catanzano
Enterprise interest in generative and agentic AI has accelerated dramatically over the past two years. Organizations across industries are exploring how AI agents, intelligent assistants, and automation can improve productivity, streamline operations, and unlock insights from growing volumes of enterprise data. Yet as enthusiasm grows, so do questions around cost, security, and operational complexity.
|
By Ron Pick
In the current enterprise technology landscape, we’re witnessing an industry-wide scramble. As organizations shift from monolithic architectures to complex environments leveraging heterogeneous infrastructures, cloud-based data platforms are hitting a visibility—i.e., observability—wall. Their response has been a wave of reactive, multi-billion-dollar acquisitions designed to "bolt-on" the observability that they lack natively.
|
By Blake Tow
For the better part of a decade, the enterprise technology mandate was simple: “cloud first,” or more pointedly “cloud only.” Modernizing meant moving to the public cloud, and on-premises architecture was viewed as legacy infrastructure to be maintained until it could eventually be migrated. Fast forward to today, that narrative has shifted dramatically, with AI as the major catalyst.
|
By Cloudera
With the integration of Trino, Cloudera SDX, and Cloudera Octopai Data Lineage, Cloudera arms enterprises with seamless access and control of their data, anywhere, automating workflows and boosting efficiency.
|
By Ron Pick
Do you know where your data is? The number of people who can pat their server and say fondly, “Right here!” is decreasing. Instead, more people are lifting their eyes to the heavens and answering, “Um… up there… somewhere…” McKinsey reports that in 2025, large enterprises have 60% of their environment in the cloud. If you’re considering moving your data assets, processes, and applications to the cloud, you’re in good company.
|
By Cloudera
Report recognizes Cloudera as an ideal choice for organizations that want robust data processing, scalable storage, and persistent data management to power modern business use cases.
|
By Blake Tow
The recent global IT outage experienced by a major cloud hyperscaler was a disruptive, real-world reminder that downtime and service disruptions are inevitable. The event impacted services across banking, retail, and healthcare, and served as a powerful warning that relying on any single provider, or even a single cloud region, creates a critical business vulnerability. This outage highlights the critical risk of a single-provider strategy, rather than an inherent problem with the cloud.
|
By Cloudera, Inc.
Ready to eliminate data delays and fuel your AI models with trusted, real-time insights? In this video, we break down how Cloudera Data in Motion allows organizations to unlock the full potential of their data fabric. Whether your corporate datasets are scattered across diverse storage systems, multiple cloud vendors, or on-premises data centers, Cloudera provides the scalable, engine-agnostic data services required to stream and process information instantly—without needing to redesign or refactor your existing pipelines.
|
By Cloudera, Inc.
This is a comprehensive walkthrough of the metadata extraction process for Cloudera Data Lineage. Learn how to utilize the harvesting agent to set up a new metadata source, such as Informatica Oracle, and perform a local extraction. The video demonstrates how the agent securely reads metadata from databases, ETL tools, and reporting systems, staging it as local XML files to ensure data does not leave the network without explicit action.
|
By Cloudera, Inc.
In this video, Cloudera’s Dipankar demonstrates how to build an AI agent in Cloudera Agent Studio powered by an open-source Apache Iceberg MCP Server. As a real-world use case, the agent monitors Apache Iceberg table health by analyzing metadata for issues such as small files, partition skew, snapshot history, and other operational signals. Subscribe to stay ahead of the curve with the latest in data strategy, open architectures, and enterprise AI innovations.
|
By Cloudera, Inc.
Can AI actually save lives? In this video, see how Cloudera and Mercy Corps have partnered to put people—not just technology—at the heart of humanitarian aid. Through a two-and-a-half-year collaboration, we’ve worked side-by-side with analysts to map real-world workflows and co-create AI solutions that solve their most pressing daily challenges.
|
By Cloudera, Inc.
Unlock the full potential of your data fabric and accelerate your AI journey with Cloudera Data in Motion. Many organizations struggle with massive amounts of diverse data spread across different formats, vendors, and locations—whether in the cloud or on-premises data centers. Cloudera provides the scalable, performant data services needed to move and process this information in real-time. Discover how Cloudera’s open-source approach can help you unlock the power of your data anywhere.
|
By Cloudera, Inc.
Hey, did you know that Cloudera has achieved the AWS Generative AI Competency? This major specialization milestone continues to validate the technical work we're doing to deliver high-impact Generative AI solutions on AWS. Because AWS Competencies require rigorous technical validation and verified customer success reviews, this achievement proves real-world impact where it matters most.
|
By Cloudera, Inc.
Ask an AI system a question, and you'll get an answer. Decision logic determines whether you should trust it. In this episode of The AI Forecast, Paul Muller sits down with Darlene Newman, Innovation Lead at Duczer East, to explore the hidden layer that helps AI move from pattern matching to practical decision-making.
|
By Cloudera, Inc.
Hey, did you know your AI agents could be making decisions based on data they were never meant to see? When enterprise data governance is fragmented across separate tools, it creates severe blind spots. Rogue AI agents can over-index, modify, or even accidentally delete production databases simply because proper data guardrails weren't uniformly enforced. In this video, we tackle the root cause of why 79% of enterprise AI initiatives stall and show you how to build a unified data fabric that secures your hybrid estate.
|
By Cloudera, Inc.
Unlock the full potential of your data fabric and accelerate your AI journey with Cloudera Data in Motion. Many organizations struggle with massive amounts of diverse data spread across different formats, vendors, and locations—whether in the cloud or on-premises data centers. Cloudera provides the scalable, performant data services needed to move and process this information in real-time.
|
By Cloudera, Inc.
What exactly is a Catalog, and why has it become such a critical component of the modern Lakehouse architecture and AI workloads? In this episode, we break down the differences between technical catalogs (metastores) and business catalogs, explore how catalogs enable governance and interoperability, and explain why the Iceberg REST Catalog specification became the open standard for sharing Iceberg tables across platforms without vendor lock-in.
|
By Cloudera
Enterprises require fast, cost-efficient solutions to the familiar challenges of engaging customers, reducing risk, and improving operational excellence to stay competitive. The cloud is playing a key role in accelerating time to benefit from new insights. Managed cloud services that automate provisioning, operation, and patching will be critical for enterprises to leverage the full promise of the cloud when it comes to time to value and agility.
|
By Cloudera
The adoption of cloud computing in the financial services sector has grown substantially in the past three years on a global basis. Diversification of risk is always a key concern for financial institutions and the seeming safety of having a single cloud provider is not being properly measured from a systemic risk and operational risk perspective.
|
By Cloudera
This white paper provides a reference architecture for running Enterprise Data Hub on Oracle Cloud Infrastructure. Topics include installation automation, automated configuration and tuning, and best practices for deployment and topology to support security and high availability.
|
By Cloudera
A cloud-based analytics platform needs to be easy, unified, and enterprise-grade to meet the demands of your business. This white paper covers how Cloudera's machine learning and analytics platform complements popular cloud services like Amazon Web Services (AWS) and Microsoft Azure, and enables customers to organize, process, analyze, and store data at large scale...anywhere.
|
By Cloudera
In the wake of the global financial crisis, the world has become much more interconnected and immensely more complex. As a result, you can no longer simply look at the past as an indicator of future trends. The financial services industry needs real-time insights into numerous interacting variables to make informed decisions.
- July 2026 (11)
- June 2026 (10)
- May 2026 (14)
- April 2026 (17)
- March 2026 (25)
- February 2026 (11)
- January 2026 (6)
- December 2025 (9)
- November 2025 (12)
- October 2025 (9)
- September 2025 (7)
- August 2025 (4)
- July 2025 (4)
- June 2025 (4)
- May 2025 (8)
- April 2025 (10)
- March 2025 (6)
- February 2025 (8)
- January 2025 (8)
- December 2024 (16)
- November 2024 (13)
- October 2024 (4)
- September 2024 (5)
- August 2024 (6)
- July 2024 (3)
- June 2024 (12)
- May 2024 (9)
- April 2024 (10)
- March 2024 (11)
- February 2024 (14)
- January 2024 (11)
- December 2023 (10)
- November 2023 (14)
- October 2023 (18)
- September 2023 (15)
- August 2023 (10)
- July 2023 (16)
- June 2023 (17)
- May 2023 (13)
- April 2023 (13)
- March 2023 (16)
- February 2023 (6)
- January 2023 (2)
- December 2022 (13)
- November 2022 (9)
- October 2022 (19)
- September 2022 (21)
- August 2022 (20)
- July 2022 (10)
- June 2022 (18)
- May 2022 (9)
- April 2022 (9)
- March 2022 (13)
- February 2022 (13)
- January 2022 (6)
- December 2021 (15)
- November 2021 (18)
- October 2021 (23)
- September 2021 (22)
- August 2021 (26)
- July 2021 (14)
- June 2021 (21)
- May 2021 (24)
- April 2021 (30)
- March 2021 (16)
- February 2021 (19)
- January 2021 (18)
- December 2020 (22)
- November 2020 (17)
- October 2020 (19)
- September 2020 (23)
- August 2020 (27)
- July 2020 (21)
- June 2020 (11)
- May 2020 (22)
- April 2020 (18)
- March 2020 (14)
- February 2020 (8)
- January 2020 (13)
- December 2019 (3)
- November 2019 (1)
- October 2019 (3)
- September 2019 (1)
- August 2019 (2)
- July 2019 (5)
- May 2019 (2)
- April 2019 (1)
- March 2019 (2)
- February 2019 (1)
- January 2019 (3)
- December 2018 (3)
- November 2018 (2)
- September 2018 (7)
- August 2018 (6)
- July 2018 (3)
- June 2018 (3)
- May 2018 (2)
- March 2018 (1)
Cloudera delivers the modern platform for machine learning and analytics optimized for the cloud. Imagine having access to all your data in one platform. The opportunities are endless. We enable you to transform vast amounts of complex data into clear and actionable insights to enhance your business and exceed your expectations.
The right products for the job:
- Enterprise Data Hub: Operate with confidence—thanks to comprehensive security and governance—while at the same time enabling unrivaled self-service performance at extreme scale. All in an enterprise-grade solution that lets you run anywhere, on-premises or in hybrid- and multi-cloud environments.
- Data Science Workbench: Accelerate machine learning from research to production with the secure, self-service enterprise data science platform built for the enterprise.
- Data Warehouse: A modern data warehouse that delivers an enterprise-grade, hybrid cloud solution designed for self-service analytics.
- Data Science & Engineering: Cloudera Data Science provides better access to Apache Hadoop data with familiar and performant tools that address all aspects of modern predictive analytics.
- Altus Cloud: The industry’s first machine learning and analytics cloud platform built with a shared data experience.
The world’s leading organizations choose Cloudera to grow their businesses, improve lives, and advance human achievement.