Standardization Unifies Data
Standardizing player and Content Delivery Network (CDN) data can give video and audio publishers a cohesive, holistic view that streamlines QoE, product, content and advertising decision making by reducing confusion stemming from inconsistencies and eliminating post processing efforts to unify datasets.
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All companies need to standardize and normalize data when receiving from multiple sources but building that capability, and providing ongoing maintenance, can be an unnecessary drain on resources.
Data Standardization Challenges
Designing an Extensible Data Standard
Given how quickly market landscapes, product directions and needs of data constituents can change, designing a future-friendly data standard that captures relevant metrics in a format that is analysis- and budget-friendly can be difficult.
Enforcing Consistency Across Integrations
Given your wide array of CDN and video player integrations, enforcing the standard across disparate contexts requires a meticulous approach and robust mechanisms to guarantee compliance.
Complex Integration Efforts
The level of effort to implement and maintain a data standard data point by data point across your video players and CDNs can be significant. The idiosyncrasies of the different integration contexts are highly prone to inaccuracies and inconsistencies.
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Data standardization is built into the Datazoom DaaS Platform. Users can easily select which data points to adjust based upon the player or CDN data dictionary.
How Datazoom Standardizes Data
Automated Data Collection
With pre-built collectors for various player versions and CDNs, Datazoom automatically captures data according to the Datazoom Dictionary, eliminating inaccuracies and inconsistencies that can arise from custom implementations.
Synergistic Player and CDN Standards
Datazoom’s player and CDN standards work hand in hand. By standardizing data collection at both levels, Datazoom bridges the gap between content consumption and content delivery
Enhanced Validation
Datazoom’s platform thoroughly validates that collected data meets expected standards and runs frequent, rigorous quality checks.
Adaptability and Flexibility
Adapt the Datazoom dictionary to other required standards within your ecosystem by using Datazoom’s transformations.
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Standardizing data at the time of collection means no more post-processing. The data comes normalized and ready to use straight from the Datazoom platform.
Standardize Example: Bitrate
What's Happening?
Data sources coming from the same endpoint, like a player, may have different names for the same value, such as bitrate. In this case, bitrate could be named Resolution, or video_quality, or bit_rate. Different variable names can make it difficult to relate datasets together when the data is viewed through a visualization tool, requiring manual post-processing. Datazoom’s CDN Data Dictionary and Player Data Dictionaries can provide an automatic standardization of data names and values across datasets speeding up analysis.
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Standardizing data at the time of collection means no more post-processing. The data comes normalized and ready to use straight from the Datazoom platform.
Data Nerd? Check Our The Datazoom Data Dictionaries
Datazoom’s Data Dictionary provides a source of truth for streaming-related variables. By standardizing data elements collected through Datazoom data pipes, streaming operators can ensure that similar variables collected from different sources are all named the same for analytical continuity.
