-Ozone object storage, a new storage paradigm for drastically better scalability than HDFS, solving challenges with name node limitations and inefficiencies with small file storage.
-YARN Queue Manager enhancements including dynamic queue configuration and dealing in absolutes when administering/managing your cluster configuration, giving you even more granular control over your cluster resources.
-Automatic translation of access policies from Hive to HDFS with the new Ranger Resource Mapping Server.
Additionally, we'll also give you a sneak peek of what to expect in the upcoming CDP Private Cloud Base 7.1.5 release.
- Fast intelligent reporting with built-in AI-powered Natural Language Search and Visual Recommendations
- Ease of use in an intuitive, visual UI for instant insight sharing without moving data or 3rd party tools
- Accelerated collaboration with a consistent, integrated data visualization experience across all data and business teams
- Is a fundamental part of Cloudera Data Platform’s architecture
- Delivers an integrated set of security and governance technologies built on metadata
- Addresses key enterprise challenges around data access and governance while reducing costs
- Provides organizations the opportunity to make better business decisions, faster
Join us for the latest from the Cloudera Fast Forward research team. This webinar will cover two recent research reports.
META-LEARNING: LEARNING TO LEARN
In contrast to how humans learn, deep learning algorithms need vast amounts of data and compute and may yet struggle to generalize. Humans are successful in adapting quickly because they leverage knowledge acquired from prior experience when faced with new problems. In this webinar we will explain how meta-learning can leverage previous knowledge acquired from data to solve novel tasks quickly and more efficiently during test time. We’ll cover:
when you should think about meta-learning and lessons to apply in your data science practice
how meta-learning helps models to generalize to new circumstances or classes during inference
a foundational approach to the kind of problems it can help us solve, along with our experimental results
THIS DEBATE WILL EXPLORE WHICH SQL ENGINE IS BEST FOR:
Enterprise Data Warehouse use cases
Ad-hoc analytics and data marts use cases
Long-running queries or complex SQL
Supporting traditional business intelligence tools for exploration
Traditional dashboards and pre-defined reporting
Please join our experts David Dichmann, Justin Hayes, and Bill Zhang from the Cloudera Data Warehouse team for this lively debate on the strengths and merits of each of these SQL Engines followed by live Q&A.
Attend this webinar, led by Pierre Villard, to hear him talk about:
- An introduction to Apache NiFi
- Perform a live demonstration of Apache NiFi
- Show how easy it is to create a data flow with no coding required
- Recommend best practices to help users accelerate data flow creation and monitoring
Abbas Moraj, Navdeep Alam, Katie Pyburn, Luke Dunlap
Leverage IQVIA’s implementation of Cloudera’s hybrid cloud capabilities to help customers accelerate their analytics and AI initiatives and deploy data lakes on-demand. IQVIA will discuss use cases in Clinical, RWE and Commercial showing how they leverage a Cloudera-based high-tech ecosystem to drive global analytics and AI.
AS PART OF THE WEBINAR YOU CAN LEARN MORE ABOUT:
A new enterprise data cloud for Healthcare that supports both multi and hybrid cloud environments
How to enable a secure, compliant, scalable, open source enterprise data cloud in days – instead of weeks (or months) with no vendor lock in with IQVIA’s PaaS solution
How to extend your cloud capability for sensitive data (PII, PHI, HIPAA)
How you can benefit from IQVIA's data science expertise in healthcare
For enterprise organizations, building robust data pipelines has become increasingly resource-intensive. Modern data engineering requires more advanced data lifecycle integration for streamlining security, governance, and maintaining data quality to enable advanced analytics and machine learning at scale. To tackle these challenges, enterprise organizations need a comprehensive and integrated data engineering experience for data pipeline preparation and management.
JOIN THIS WEBINAR TO:
Learn how Cloudera enables streamlined scheduling and workflow orchestration with Apache Airflow for analytical services such as Data Warehousing and Machine Learning using Spark
Experience visual, self-service troubleshooting and complete monitoring service for identifying and solving issues quickly
Explore how the Cloudera Shared Data Experience breaks down data silos and enables enterprise-grade security, governance and lineage tracking for data workflows
This webinar will highlight key use cases and demonstrate unique CDP capabilities, including: ·
Deep dive on CDP architecture
How to get control of data across the entire data and analytics lifecycle – from data collection to Machine Learning
Simplify data privacy and compliance for diverse enterprise data with a common security model to control data on any cloud – public, private and hybrid
Enable self-service analytics & make it easy for businesses to consume data easily without compromising on security & governance
Enterprise IT is overwhelmed trying to manage data security and governance across fragmented systems infrastructures. This impacts security and efficiency and also frustrates business users through a lack of agility and flexibility. With SDX, IT has centralized data security, governance, and control it requires to safely and securely meet the ever-changing business needs.
During this demo, you’ll learn how Cloudera’s SDX:
Provides IT with enterprise-grade data security and governance
Log Analytics is critical to maintaining and leveraging your business and operational infrastructure, but Logging Modernization could be the difference between new revenue streams and missed opportunities. Join Abdelkrim Hadjidj, Data In Motion Solution Engineering Manager, and Laura Chu, Data In Motion Product Marketing Manager, to hear them discuss:
The challenges of log analytics
What is required to unlock the value of machine-generated data
The approach to Logging Modernization
Use cases where the customer benefits the most using Cloudera DataFlow
Machine learning allows us to detect subtle correlations in large data sets, and use those correlations to make accurate predictions. However, these subtle correlations are often spurious - they exist only in a particular dataset - and the resultant model performs poorly, or gives unexpected results in the real world. Moreover, reasoning based on spurious correlations is dangerous. Business decisions should be based on things that are true, not things that are true only in a limited dataset. The trouble, of course, is identifying what is spurious and what is not. In this webinar, we’ll explain how combining causal inference with machine learning can help us address these problems.
when you should think about causality and lessons to apply in your data science practice
the latest research at the intersection of machine learning and causality
how causal thinking helps us write models that generalize to new circumstances, including an example of the causal approach applied to a computer vision problem
Learn how CML’s MLOps functionality eliminates the model black box and drives secure, transparent ML workflows from data to experimentation to production at scale.
In this session we will discuss:
- CML’s robust and flexible model monitoring service for both technical metrics (latency, throughput, etc.) and the mathematical/functional monitoring
- First-class prediction tracking, metric stores, and Python SDK.
- How CML’s unique model cataloging and model lineage capabilities eliminate silos and lead to better, faster results
Join Cloudera in this webinar as they explain how your business can become AI-First leveraging the cloud with Cloudera Machine Learning, part of the new Cloudera Data Platform (CDP).
Cloudera will demonstrate how IT teams, data scientists and data engineers can have on-demand access to business data, open tools and computing resources for end-to-end machine learning - bringing the agility and economics of the cloud to self-service data science in a secure and governed way.
Michael Ger, Managing Director, Manufacturing & Automotive
Join us in this session, as we:
- Harness real-time time-series data to boost production and improve profitability
- Leverage time series data as a stepping stone to machine learning and predictive maintenance
- Learn through a practical demo how Cloudera tackles time series data in the data lifecycle
Advancing digital transformation with an enterprise data cloud
At Cloudera, we believe that data can make what is impossible today, possible tomorrow. We empower people to transform complex data into clear and actionable insights.
To that end, we deliver an Enterprise Data Cloud for any data, anywhere, from the Edge to AI. Powered by the relentless innovation of the open-source community, Cloudera accelerates digital transformation for the world’s largest enterprises.