Datatecture Levels

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How the Datatecture is Organized

The datatecture is organized into levels. The top-most level represents the highest organization of data functions within the streaming technology stack. Below that, the data functions become more specialized until they reach a level where the specialization is addressed by specific companies.

Infrastructure

Operations

Workflow

Infrastructure

Containers and Virtualization

Queuing Systems

Storage and Caching

Storage and Caching

Data Warehouse

Object Storage

Open Cache Management

Origin Services

Time-Series Databases

Operations

Analytics

Configuration Management

Customer Data Platforms

Monitoring

Configuration Management

Data Management Platforms

Multi-CDN Solutions

Analytics

Ad Viewability and Vertification

Audience Measurement

Customer and Product Analytics

Identity and Attribution

Log Analysis

Video Analytics

Video Quality Assurance

Monitoring

Synthetic Monitoring and Testing

Visualization and Dashboards

Workflow

Content Recommendations

Delivery

Monetization

Playback

Security

Transformation

Delivery

Content Delivery Network

Multicast ABR

Peer-to-Peer (P2P)

Ultra-Low Latency Streaming

Monetization

Advertising Systems

Paywall

Advertising Systems

Ad Exchange

Ad Network

Buy-Side Ad Severs

Demand Side Platforms

Supply Side Platforms (SSP)

Video Ad Insertion

Video Ad Servers

Playback

Devices

Players

Devices

Connected Streaming Devices

Connected TVs

Gaming Consoles

Mobile

Set-top Boxes (STBs) and OS

Players

Commercial

Offline

Open Source

Security

Geo IP

Watermarking

Transformation

Encoding

Metadata

Packaging

Transcoding

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The Streaming Video Datatecture and microsite provide free and educational compilations of all of the companies and services involved in the streaming video industry. It provides a deep look into the ecosystem and layout, and explains the technologies that power video streaming. Created by Datazoom, the enterprise video data platform technology company, the goal is to help content owners, technology and service providers, investors, and other stakeholders better understand the data, systems, and leveled architecture that come together to create the data fabric of streaming video.

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  • Why Video Data Telemetry is Critical to DevOps Success (And How to Get It)
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    DevOps has been a revolution in software development. To support agile methodologies, in which developers can incrementally release features that are tested by users in real-time, developers needed to have an increasingly larger role in operationally supporting their code. Waiting for operations to make configuration changes to environments or push out new code didn’t support The post Why Video Data Telemetry is Critical to DevOps Success (And How to Get It) appeared first on Datazoom.

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