New York-based Parse.ly that provides web analytics and content optimization software for online publishers has announced the availability of the Parse.ly Data Pipeline that processes the raw data and unlocks it for real-time analysis for data engineering projects. In simple words, it collects the audience interactions across channels (blogs, site, mobile apps) and ‘pipe’ them into secure long-term storage.
Parse.ly claims this as an ideal data platform for developers as it provides a complete access to historical raw data including real-time data via streaming endpoints. According to company, it is now available to a much wider group of users’, not just publishers and media companies, but anyone who has a considerable user analytics challenge and wants a fast path to insight. The data formats integrate cleanly with open source data analysis stacks, like R, Python, Pandas, Hadoop, and Spark. The raw events are also ideal for imports into cloud SQL engines like Amazon Redshift or Google BigQuery.
Andrew Montalenti, Co-Founder and CTO at Parse.ly said:
“Digital publishers and other web companies have long felt that point vendor solutions are holding their data hostage. Parse.ly’s Data Pipeline unlocks this data, making it easy to build an in-house practice around analytics. This lets our customers focus on meaningful analysis, rather than the arduous task of building and managing data infrastructure.”
How does it work?
Data Pipeline enables the user to analyze data using existing tools and on the other hand data pipeline collects, enhances and streams real-time user and content data to warehouse.
Parse.ly’s JavaScript and native mobile trackers collect all the data from the user’s site and apps and ensures that every event is captured constantly.
Events are automatically enriched with extra information, like geographic region and device breakouts and are customizable, so the team can send events of any kind.
The user can stream data directly in AWS or integrate with Redshift, BigQuery or other tools using the open source recipes. In the end the user owns a clean, structured, first-party data source that can be analyzed directly.
Parse.ly’s Data Pipeline provides ‘streaming’ access to its real-time events, with end-to-end latency measured in seconds; this will let the team build true real-time dashboards.
Parse.ly that claims Data Pipeline as the ‘easy button’ where the teams can build in-house analytics as it save time and money on an expensive build-out of data infrastructure plumbing, as well as on the long-term maintenance of that infrastructure.
Sachin Kamdar, Co-Founder and CEO at Parse.ly said, “The better an organization can utilize its data, the closer it comes to understanding its audience. With our Data Pipeline, we’re pleased to provide sites with a turnkey way to bring their raw data in-house. Taking ownership of your data is the first step; unlocking its secrets is next. Parse.ly’s here to help you do both.”