Question

COMP 309 - Research

Research about Cloudera

1. Overall architecture and key technologies used in the platform/tool

2. Key components of the software

3. Cloud / Hybrid capabilities

Answer 1

1.

From autonomous vehicles and surgical robots to churn prevention and fraud detection, enterprises rely on data to uncover new insights and power world-changing solutions.

It all starts with a data platform that enables you to say "yes". Yes to the analytics your people want to use. Yes to operating on any cloud your business requires. Yes to the future with a cloud-native platform that flexes to meets your needs today and tomorrow. And we have delivered. Cloudera Data Platform is the industry's first enterprise data cloud:

• Multi-function analytics on a unified platform that eliminates silos and speeds the discovery of data-driven insights
• A shared data experience that applies consistent security, governance, and metadata
• True hybrid capability with support for public cloud, multi-cloud, and on-premises deployments

Cloudera is leading hospitals to better cancer cures, securing financial institutions against fraud and cyber-crime, and helping humans arrive on Mars — and beyond.

But even the most transformative organizations had to start somewhere. That's where we thrive:

• Guiding passion into proofs of concept
• Extracting value from vision.
• Empower continuous optimization and learning across the enterprise
• Turning data into predictions at any scale, anywhere

Features:

Hybrid & multi-cloud: Operates across all major public clouds and the private cloud with a public cloud experience everywhere.

Multi-function analytics: Integrates big data management and analytic experiences across the data lifecycle for data anywhere.

Secure & governed: Delivers security, compliance, migration, and metadata management across all environments.

Open platform: Open source, open integrations, extensible, & open to multiple data stores and compute architectures.

2.

CDP demo

Watch technical demos aimed at both educating and inspiring users with deep dives into topics such as application development with Operational Database and building end-to-end data pipelines spanning edge devices all the way to the public cloud.

Discover CDP video tour

Get a look under the hood of Cloudera Data Platform in an eight-video product tour that explains the importance of connecting, managing, and securing the entire data lifecycle and details how individual CDP products work together to further that effort.

CDP technical resources

Save time with one-stop-shop delivering resources for technical users aimed at helping you build skills and gain knowledge about Cloudera Data Platform, including videos, tutorials, blogs, training, events, community, Professional Services offerings, documentation, and more.

Free CDP training

Get up to speed with a free, on-demand training course that walks you through the specific ways that CDP enables both business teams and IT staff to be more productive and explains its capabilities for turning data into actionable insight. Hear, as well, from two customers who have successfully implemented CDP.

3.

CDP Public Cloud services are;

1. DATA HUB: Simplify building mission-critical data-driven applications with security, governance, scale, and control across the data lifecycle.

2. DATA WAREHOUSE: Unleash hybrid and multi-cloud data warehouse service for all modern, self-service, and advanced analytics use cases, at scale.

3. MACHINE LEARNING: Accelerate development at scale, anywhere, with self-service machine learning workspaces and the underlying computing clusters.

4. DATA ENGINEERING: Orchestrate, operationalize, and automate complex data pipelines to increase efficiency and accelerate time to value.

5. DATA VISUALIZATION: Curate and deliver rich, visual dashboards, and applications that accelerate the operationalization of analytical insight across your enterprise.

6. OPERATIONAL DATABASE: Bring unparalleled scale and performance to your mission-critical applications while securing future readiness for evolving data models.

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