David Dichmann, Director, Product Management, Cloudera

Companies struggle to answer new burning business questions quickly enough to respond to constant change, because ingesting, transforming, analyzing, and visualizing new data requires multiple people and products working together across different environments. In this session, you’ll see an end-to-end demonstration of how Cloudera dramatically streamlines this process with role-based, pre-integrated solutions to common use cases. With Cloudera Data Platform’s integrated data lifecycle tools, practitioners can quickly discover, analyze, prepare and publish new data insights across hybrid cloud.

Session Takeaways 

• Spend less time waiting and more time doing with self-service access to data that lets LoB Analysts discover new insights and create queries that satisfy the growing demands of business managers

• Reduce the delivery of high-performance decision support from months to days with self-service business intelligence (BI) at scale for data ingestion, data science, and BI development

• Get instant answers to burning business questions and fast turnaround on solutions in production through self-service capabilities for LoB Analysts

Peter Ableda, Product Manager, Cloudera

To build models and power Machine Learning (ML) use cases, data scientists and ML engineers need to fully understand their data. In this session, you’ll see how Cloudera Machine Learning (CML) solves this problem with built-in  SQL and data visualization tools, which are integrated and accessible directly from data science and ML project spaces. CML is available on both public cloud and private cloud, giving companies the flexibility of data discovery in hybrid cloud.

Session Takeaways 

• Spend more time solving business problems and less time conducting data exploration with code or across multiple tools

• Reduce time to value with CML which enables you to train your ML models through rapid iterations on datasets

• Fetch datasets with just two lines of code using CML’s connection library snippets

Raman Rajasekhar, Director, Product Management, Cloudera

Public and private cloud each have their advantages, especially when it comes to cost-efficiency. Public cloud is best for low-utilization workloads, while private cloud is more suitable for high-utilization workloads. But how do you know which workloads are high vs low utilization? In this session, you’ll see how Cloudera Data Platform Hybrid Cloud analyzes and identifies the best environment, public or private, for each workload.

Session Takeaways 

• Get insights on tenant costs in a simple, straightforward way with Workload Manager in CDP

• Custom define cost centers to proactively monitor your most expensive tenants and their workloads

• Optimize and control application costs with ease using the prescriptive recommendations provided by Workload Manager

Michael Kohs, Senior Product Manager, Cloudera

With the rise of streaming data (or, data in motion), companies must figure out how to deliver high-scale data ingestion, transformation, and management. In this session, you’ll see how Cloudera Data Platform’s (CDP) new DataFlow service provides real-time data movement capabilities to address hybrid cloud use cases.

Session Takeaways 

• Manage your infrastructure and auto-scale your data flows as needed with Cloudera DataFlow for Data Hub — the first cloud-native runtime for Apache NiFfi

• Meet performance SLAs and ensure the health of data flows with the monitoring dashboard that offers insights and KPIs at a glance

• Deploy your first data flow in minutes using the growing library of ReadyFlows and adjust as needed to meet your needs