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.
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.
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.
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
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.
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.
How Datazoom Standardizes Data
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.
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.
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.
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.
Datazoom Announces 3 Looker ‘Blocks’ for OTT Video: Engineering, Content, and Product Performance
NEW YORK, NY / ACCESSWIRE / March 9, 2021 / Datazoom, a real-time video data platform, announced the release of three new Looker Blocks for Engineering, Content, and Product Performance. Datazoom customers who are also Looker subscribers can now use one or more pre-built, out-of-the-box dashboards in Looker to easily gain a detailed understanding of audience growth and engagement, advertising, content performance, Quality of Experience (QoE), and other core KPIs specific to OTT video.
The key to ensuring the growth and quality of a streaming service is being able to derive meaningful insights and actions from data. Although the task of analyzing raw data might seem daunting, ultimately having access to the underlying raw data and queries, coupled with a prolific visualization and analytic solution, is what makes these Looker Blocks so unique. They assist in generating those contextualized insights which are paramount to a resilient service and a healthy business. These Looker Blocks can help technical operations make configuration or other changes to ensure viewers get the best viewing experience. And the Blocks can provide executives insight into the business performance of their service-from subscription levels to advertising placement to viewer engagement.
Through these new Looker Blocks, customers of both Datazoom and Looker can accelerate their understanding of critical video streaming data. For OTT streaming operators, both Datazoom and Looker can be adapted and extended to meet whatever data and analytics needs arise.
Although these Looker Blocks focus on data captured by Datazoom from the player, Looker subscribers can modify and create new dashboards to correlate data from multiple sources, such as between the player and Content Delivery Network (CDN). This process enables a more robust picture of QoE, and can result in creating an actual root-cause analysis solution. Furthermore, the data collected from delivery and player components can show desirable viewer behavior (as it relates to increasing content consumption), subscribers who exhibit that behavior, and opportunities to nudge other users in that direction.
“Data is foundational to the growth of direct-to-consumer OTT offerings,” said Anil Jain, Managing Director,Media & Entertainment, Google Cloud.”As these services undergo rapid scale and global growth, the key to increasing revenue and expanding the lifetime value of consumers is having real-time operational insights to improve the consumer experience, inform business decisions, and measure KPIs. Through platforms like Datazoom and Google Cloud’s Looker, companies can advance their data strategies, turning information into actionable insights.”
“The Datazoom platform has been built to source data from the various parts of the streaming workflow for real-time consumption, such as within these Looker Blocks,” says Diane Strutner, Datazoom CEO. “Because Datazoom captures, standardizes, and correlates data sets relevant to OTT video, solutions like Looker can be easily leveraged to provide deep and vertically-specific analytics for the OTT streaming space.”
Recently, Datazoom announced one of the industry’s first end-to-end data collection, standardization and routing services for streamingCDN log data. Beyond CDN data, Datazoom also offers a Collectors for Video Players and a Video Player Data Dictionary with over 200 standardized data points. The company has plans to announce additional integrations before the end of the year.
For more information about these Looker Blocks, visit Datazoom.
About Datazoom
Datazoom is an enterprise Video Data Platform technology company that standardizes and enriches data for video teams and their technology partners. Through a variety of real-time data collection software and routing services, the Datazoom’s platform offers flexibility and transparency in data collection so that operations, engineering, product and business decisions can be made with confidence. Companies that drive revenue with video use Datazoom to democratize insight, decrease inefficiencies, and deliver captivating end-user experiences. Unlock your data’s Black Box at datazoom.io.
PR Contact
Diane Strutner
diane@datazoom.io
Datazoom Announces CDN Collector for Amazon CloudFront
New Collector Integration Facilitates The Real-time Analysis of Amazon CloudFront Performance Alongside Other CDN Logs and Video Playback Datasets for Content Owners
(New York, Jan 14, 2021) — Datazoom, the Real-time Video Data Platform, announced today the release of their integration with Amazon CloudFront, expanding upon their capabilities to capture, standardize, and route data from across the end-to-end workflow of video.
Recently, the company announced one of the industry’s first end-to-end data collection, standardization, and routing services for streaming Content Delivery Network (CDN) log data.
At the end of August, Amazon Web Services (AWS) announced the first Amazon CloudFront real-time logging solution. Datazoom’s integration with Amazon CloudFront leverages this release, and collects data via Amazon Kinesis Data Streams, standardizes the common data elements that appear in Datazoom’s CDN Data Dictionary, and delivers CloudFront CDN data to destinations including Amazon Simple Storage Service (Amazon S3), Splunk and Google BigQuery. Documentation on the setup process can be found here.
Furthermore, Amazon CloudFront supports the logging of query parameters, which customers can use to pass the client-side identifiers necessary to adhere to the Common Media Client Data spec (CTA-5004). This feature enables a granular matching between client-side experience data with the corresponding CDN telemetry.
“Our customers see value in examining CDN data alongside other data sets, such as client-side Quality of Experience (QoE) data. The ability to correlate these data sets helps in determining causation more easily. Our goal is to provide the best service possible to our customers, and this means facilitating ways for our customers to track the impact of Amazon CloudFront’s performance on their viewers’ experience,” said Nishit Sawhney, Head of Product Management for Amazon CloudFront, Amazon Web Services, Inc. “The joint analysis of CDN and player data helps customers monitor CDN and viewer experience in real-time and act swiftly. This is why we invested in creating a real-time logging solution, and why we support AWS Partners like Datazoom through the integration efforts.”
Creating access to correlatable data sets will unlock the ability to automate root cause analysis, and potentially enable streaming experiences that can adapt to availability changes or failures once detected. However, the effectiveness of those solutions will be predicated on having great data.
“Datazoom’s platform has been uniquely built to support the future of streaming,” says Datazoom CEO Diane Strutner. “The adoption and integration of machine-driven technologies that can provide optimization and issue prevention at scale will be stalled by a lack of real-time, standardized data from all relevant sources. This is the biggest challenge that exists in the streaming space, our integration with Amazon CloudFront brings us one step closer to this reality.”
Beyond CDN data, Datazoom also offers a Collectors for Video Players and a Video Player Data Dictionary with over 200 standardized data points and plans to announce additional integrations before the end of the year.
PR Contact
Diane Strutner
diane@datazoom.io