Cloudera

    • Cloudera Now, our quarterly virtual event, is designed for all data practitioners including data scientists, data engineers, and analytics professionals who want to learn about our latest and greatest product innovations. Through comprehensive demos, customer use cases, and interactive Q&A, attendees will gain new skills and knowledge to bring back to their organizations.

     

    Join us and be among the first to get early access to products, code drops, and sneak previews of new technologies. Can’t make it? You’ll be able to access all content on-demand to view at your convenience.

    What you can expect from Cloudera Now

    Drive results with the only open data lakehouse for trusted AI

    With emerging technologies like large language models (LLM) and real-time self-service analytics at scale, your business requires the most advanced open data lakehouse to power fast and complete data workflows at the lowest cost. From data movement to AI and beyond, get everything you need to drive business impact at Cloudera Now.

     

    Practical knowledge you can use

    Whether you’re migrating to CDP Private Cloud or just starting your journey with Cloudera, take the guesswork out of implementing the latest updates and start delivering business impact fast.  Step-by-step walkthroughs, led by Cloudera experts, will help take your analytics and AI capabilities to new heights with practical implementation and optimization knowledge you can use today. Learn how to understand and optimize Cloudera Data Platform deployments across your data lakehouse, including how to deliver a scalable, open lakehouse on prem to power analytics and machine learning (ML).

    Product demos

    See demonstrations of new products, including the latest optimization tooling for ML and data engineering across any cloud. Learn how we enable trusted AI at scale—from LLMs to AI applications and whatever comes next. Discover how our new private cloud open data lakehouse enables any analytic and AI workload in any data center with full interoperability across any cloud. And don’t miss other great demos, like the latest developments and use cases for Apache Iceberg, how to modernize your data pipelines, and more.

    Interactive Q&A sessions

    Whether you’re looking to advance your ML capabilities, make data workflows fast and versatile with Apache Iceberg, or create transparent, observable data flows, we’ve got answers to all your questions. Join a live Q&A session to ask Cloudera product experts anything and everything you can think of about the challenges and opportunities that lie ahead.

    Agenda

    Harnessing Enterprise AI for LLMs and Beyond: Latest Innovations in ML & Data Engineering

    • Ian Brooks, Principal Sales Engineer
    • Ying Chen, Product Manager

    Advanced ML can be challenging, but with the latest innovations in ML and data engineering tooling, we will show you how to level up your predictive analytics game across your whole business. In this session, we will explore new features designed to improve data practitioner workflows to support the rapid development of Enterprise AI applications on Cloudera’s Open Data Lakehouse.

    We will cover the specific enhancements made to model management, focusing on the model registry, and discuss their real-world applications. We will also discuss the new Interactive Sessions and Virtual Cluster types, and their importance in refining data engineering development workflows.

    Key Takeaways:

    • Understand the improvements in model development and management and how they apply to real-world scenarios.

    • Learn about the new Interactive Sessions and Virtual Cluster types and their role in streamlining data engineering development workflows.

    • Discover how these and other updates enable efficient and effective delivery of trusted, enterprise data and AI solutions.

     

    Cloudera Open Data Lakehouse on Private Cloud: the easy button for trusted AI

    Navita Sood, Director Product Marketing, MDA
    Vineeth Varughese, Sr. Product Marketing Manager

    Trusted AI needs trusted data from a trusted data lakehouse. Cloudera’s Open Data Lakehouse now makes it easier than ever to turn your data into insight at scale, everywhere. No more compromises as CDP Private Cloud Base now adds support for Apache Iceberg, letting you deploy the same great analytics wherever you need them, across hybrid cloud.

    In this session we will cover the key use cases Cloudera’s Open Data Lakehouse enables for organizations to become data-driven while improving data user efficiency and reducing costs.. We’ll show you how, regardless of where your data is or what you are using to get value from it now, Cloudera lets you turn it into value faster with a platform that always operates best thanks to Cloudera Observability. You’ll see Cloudera’s Open Data Lakehouse in action and hear about the benefits customers are reaping. 

    Key Takeaways:

    • Cloudera’s Open Data Lakehouse is now available for private cloud, and can move with you across hybrid cloud as needed

    • Discover the latest data lakehouse use cases that let you reap insight and value 

    • Learn how Cloudera Observability makes Cloudera deployments always operate best

    • See how it’s now easier than ever to move to Cloudera’s open Data Lakehouse on premises.

     

    Mastering Data-in-Motion to fuel AI

    • Tim Spann, Principal Developer Advocate, Data-in-Motion

    In this session, we will explore how customers are building high performance data pipelines with Cloudera’s data-in-motion capabilities to execute on their AI initiatives. We will focus on both  generative AI as well as the process of building and deploying traditional ML against data of increasing velocity. 

    Learn how to "own" data ingestion into vector DB's for security and efficiency with a new NiFi processor exclusive to Cloudera customers that vectorizes data with connectors to popular vector DB's.  We will also cover how to use SQL to enable self-service analytics against streaming and batch data, and how the resulting data can be used to drive ML efforts, including real-time scoring.  

    Key Takeaways:

    • Understand how to solve for ingestion into vector databases to drive generative AI

    • Discover how to ensure data pipeline security for Trusted AI

    • Learn how to use SQL to accelerate traditional ML efforts from exploration through to real-time scoring for critical use cases

    Optimize Your Analytics With Workload-Aware Autoscaling

    • Manish Maheshwari, Director, Product Management

    Keeping track of what runs where on which clusters, how it performs, and how or whether it could perform better is a big undertaking. Or rather, it used to be; not anymore! Cloudera’s proud to reveal its first applied observability solution that helps you understand and optimize your Cloudera Data Platform deployments across your data lakehouse.

    Workload-Aware Autoscaling delivers a brand new compute autoscaling capability that allows your virtual data warehouse to be sized and used for diverse data storage and analytical workloads. This enables dynamically and on-demand, according to CPU and memory utilization, and effective parallelism required to deliver results for your business quickly.

    Key Takeaways:

    • Efficient SLA and cost-bound autoscaling and multithreading 

    • Effective and efficient hardware utilization of cloud provider compute instances 

    • Manage diverse workloads in a single VW to improve usability and workload management

    Integrating Cloudera Data Warehouse with Kudu Clusters

    • Manish Maheshwari, Director, Product Management

    Apache Kudu is an open source distributed data storage engine that makes fast analytics on fast and changing data easy. Therefore, the combination of Apache Impala and Apache Kudu make a great combination for real-time analytics on streaming data for time series and real-time data warehousing use cases. In this session, we will discuss how you can now connect Apache Impala in Cloudera Data Warehouse service with Apache Kudu clusters running in Data Hub.

    Key Takeaways:

    • Primer on Apache Kudu, supported use cases and customer case studies 

    • Learn how to integrate Apache Impala in CDW and and Kudu in Datahub together to achieve separation of compute (i.e. Impala) and storage (i.e. Kudu)

    • Learn the benefits of using Impala in CDW and scale up compute and storage independently on demand

    Speakers

    Santiago Giraldo Sr. Director, Product Marketing - Hybrid Data Services
    Ying Chen Product Manager
    Ian Brooks Principal Sales Engineer
    Navita Sood Director Product Marketing, MDA
    Vineeth Varughese Sr. Product Marketing Manager
    Tim Spann Principal DIM Specialist and Developer Advocate
    Manish Maheshwari Director, Product Management

    Not sure? Check out what past attendees have to say about Cloudera Now

    Amazing presentation of some genuinely out of the box feature sets.”

     

    - Independent Consultant

     

    Great webinar, well-tailored for tech and ease to business implementation.”

     

    - Desert Consulting

     

    Register now

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