Name: Data lifecycle on CDP Private Cloud
Start: 2020-10-27T04:00:00Z
End: 2020-10-27T04:00:46.000Z
Location: BrightTALK
Rating: 0

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.

JOIN THIS WEBINAR TO:

- Discover how CDP Data Engineering, Machine Learning, and Data Visualization work together to scale AI use cases

- Learn how to create explainable predictive applications for decision-makers, powered by automated data pipelines and machine learning models

- Enable your business to take action with secure and governed end-to-end machine learning with SDX

Enable The Full Machine Learning Lifecycle For Scaling AI Use Cases

WE'LL DIVE INTO THE FOLLOWING KEY NEW FEATURES:

-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.

What's new in CDP Private Cloud Base?

In this webinar you will learn how DV delivers:

- 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

Introducing Self-Service Data Visualization On Cloudera Data Platform

JOIN THIS WEBINAR TO LEARN HOW SDX:

- 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

Security and Governance for Modern Data Management

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

Fast Forward Research Roundup

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.

Data Professionals, start your engines…

Racing for Results! Data Warehouse - Impala vs. Hive LLAP

JOIN US FOR THIS WEBINAR TO UNDERSTAND HOW CLOUDERA DATA PLATFORM PRIVATE CLOUD:

- Uses OpenShift to consistently provision and scale analytic workloads in minutes and allocates just enough resources to meet demand

- Enables users and groups to have self-serve access to data and analytics with Cloudera SDX, an integrated set of security and governance tools 

- Relies on principles of modularity, modern infrastructure management, and self-serve workflows to improve agility for the organization

CDP Private Cloud: A modern data platform, built on Red Hat OpenShift

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

Demo Jam Live: Create Data Flows with Apache NiFi

IN THIS LIVE DEMO, YOU WILL LEARN:

About sentiment analysis for unlabeled data using linear models in R/sparklyr

How to train Deep Neural Networks to perform sentiment analysis on training data then apply that model to new data using Python

How you can use Cloudera’s Sentiment Analysis Applied Machine Learning Prototypes to power use cases across your business today

Plus get access to instructions for building and deploying the Applied ML Prototype on Sentiment Analysis.

Build a sentiment analysis application in CDP

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

Accelerate your data science initiatives with a healthcare data lake on-demand

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

Data Engineering in the enterprise: How to accelerate and scale your data pipeli

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

Manage and Secure the Data Lifecycle in Any Cloud

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

Seamlessly and consisten

Security and Governance with Cloudera Shared Data

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

Logging Modernization: Unlock the Value of Machine Data

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.

WE’LL COVER:
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

Causality for Machine Learning

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

Enabling Production ML at Scale: Hands on with Cloudera Machine Learning, MLOps

Administrators can deploy ML workspaces for teams with secure access to data and tools for end-to-end data science workflows 

Users get on-demand access to auto-scaling, auto-suspending compute resources and their preferred editors, tools and libraries, all within administrative guardrails for security and cost  

Teams can collaborate to accelerate projects from data engineering and exploration to model training and experiment tracking, to deploying and managing models via interactive apps in production

Enterprise Machine Learning with Cloudera Machine Learning (CML)

New technology, New Data Techniques and New Business Theories are driving the evolution and modernisation of the Data Warehouse

To Leverage Data Warehouse Technology – It’s Time To Move on.

During this session, you'll learn how to use Cloudera Data Warehouse to:

 •  Architect for faster analytics on DW data sets with workload isolation and auto-scaling
 •  Optimise and tune in self-service with intelligent workload management

Cloudera Data Warehouse on Cloud

CDP Private Cloud is introducing new analytic experiences targeting the main pillars of every data analytics platform, starting with Cloudera Machine Learning (CML) and Cloudera Data Warehouse (CDW). These experiences have been developed from the ground up as containerized services orchestrated by Kubernetes.  

With this new architecture, CDP can provision and scale these analytics in minutes and allocate just enough resources to meet current demand, including peak loads.  CML and CDW also feature new end-user interfaces to simplify the end-to-end workflows of their respective data analytics domains.

JOIN US FOR THIS WEBINAR TO UNDERSTAND HOW CDP PRIVATE CLOUD:
Offers an easy, scalable data mart with a rich SQL editor in CDW

Allows users to create and visualize complex job pipelines in CML

Secures and governs these integrated analytics with Cloudera SDX

Data lifecycle on CDP Private Cloud

Data Analysis

Lifecycle

Public Cloud

Data Warehousing

Machine Learning

SQL server

Multi Cloud

Streaming

Big Data Analytics

Data Management

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Data lifecycle on CDP Private Cloud

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