Precog, a developer of infrastructure for data warehousing and analysis, has announced the launch of its Precog platform in public beta.
The Precog platform is designed for developers and data scientists and combines the scalability of big data platforms with the number-crunching power of statistical tools, the company said. This means development teams can quickly build big data applications without custom data infrastructure development and maintenance, and data scientists can aggregate, massage, analyze and model large amounts of data, without needing a separate ETL (extract, transform and load) process, into a small-data statistical tool.
Precog simplifies big data capture, storage and analysis by enabling developers to build big data and analysis features into their applications via Precog APIs, then to store, process and analyze their big data in the Precog cloud environment. In addition, Precog eliminates the need for development teams to learn Hadoop and related complex data storage and analysis technologies, freeing them to focus on core application functionality, the company said.
Moreover, statistical models, aggregations or complicated analytical calculations developed by a data scientist can be transparently run in production by developers, allowing new features to be added to products or allowing automation of workflows.
“Modern applications, whether Web, mobile or desktop, have grown increasingly sophisticated in their ability to increase interconnectivity, drive efficiency and generate valuable data,” said John A. De Goes, CEO of Precog, in a statement. “Where Web applications often fall short is in their ability to create meaningful, actionable insight through the deep analysis of the massive volumes of data they are often creating. By making it easy for development teams to build advanced big data capabilities into their applications, Precog is powering a new generation of highly sophisticated applications that are poised to unlock the big data puzzle.”
Key features of Precog include warehousing, analysis and measured data. Precog provides deep data analysis, including analytics, statistics and machine learning. This functionality supersedes analysis features of standard warehousing offerings, which typically are limited to rollups and aggregations, and tend to rely on ETL to extract a subset of data into a more capable analysis product. Precog also is designed for capturing event-oriented data, such as behavioral data, transactional data, historical data, measurement data or any data set that is traditionally stored in a fact table under a relational database management system (RDBMS).
All Precog features are exposed via embeddable Precog APIs, which include a data ingest API, data analysis API, data integration API, security API and accounts API. Precog APIs make it easy and secure to package Precog-powered analysis into third-party applications and to load Precog with data from third-party sources, including external APIs -- such as Twitter, Facebook, Salesforce.com, CSV files, Websites and transactional data stored in existing databases (SQL, Hadoop, MongoDB).
SnapEngage, a popular online sales and support tool, uses the Precog platform to provide its customers with extremely deep insight into the support process and its effects on conversion and retention. Before adopting Precog, SnapEngage used a data warehousing and analytics solution to store interaction data, but the cumbersome data model and lack of first-class support for analytics made it difficult and expensive to iterate based on customer feedback, or look at data in new ways.
“SnapEngage has quickly become the de-facto live chat platform for any company interested in engaging with their customers in real-time,” said Chris Vieville, community manager for SnapEngage, in a statement. “As we grew our install base, we realized that there was an opportunity to give our customers the ability to access end-user interaction data and analyze it in new, powerful ways. Precog helps us capture all interactions between support agents and Website visitors and perform sophisticated analytics on that data to identify patterns, trends and correlations that help support managers improve conversion and retention.”
The Precog platform offers an end-to-end solution for programmatic big data analysis: from capture and storage, to cleaning and enrichment, to deep analysis designed to power intelligent, insightful features inside applications, the company said. Precog is useful for heterogeneous data, normalized and denormalized data, whole data analysis, complicated analysis, and data integration and munging.