Your Big Data engine to prepare data for Analytics and AI
Organizations today are seeking ways to get quality and trusted data into the hands of their data scientists, BI groups, and frankly, everyone across their business, fast.
While legacy methods like ‘ETL’ are still options for some companies to collect and aggregate data, the issues continue to be speed, cost, and quality. Consumers of data, regardless if it’s for ad hoc data science initiatives, or for regulatory and compliance reporting, need data cleansed, standardized, and discoverable. Without waiting for time-consuming and expensive developer efforts.
Automation, security and governance are core principles built into our innovative metadata-driven ingestion engine, Cornerstone®. With Cornerstone, users can automatically ingest all types of data, with NO ETL!
Cornerstone offers significant advantages over ETL
and other legacy data ingestion processes:
Automate & Standardize
Cornerstone‘s fully automated, metadata-driven ingestion engine standardizes and secures data when ingesting from any source to any target, while capturing granular data lineage and metadata. Cornerstone‘s patented technology allows users to ingest structured and unstructured data via batch, streaming or direct-to-database methods, without writing a single line of code.
This means companies looking to build out Enterprise Data Lakes, they are able to ingest new data sources much faster than ever before. This is especially useful when creating, for example, a data marketplace for Risk analysis or pulling in more data for Machine Learning or training AI.
Integrate with any legacy or modern data platform, including Hadoop and Cloud
Automated Metadata and Lineage Capture
Captures metadata and granular data lineage; for Batch, Streaming and Direct-to-Source ingestion – no manual coding
Support for complex cloud, on-prem and hybrid environments
Encrypt, tokenize and enforce policies via metadata
Data Manufacturing Pipeline
Quickly collect and prepare data in a governed state to produce risk and regulatory reports.
Ingest data from multiple sources, and combine them through a single pipeline to feed marketing engines for real-time analysis.
Quickly ingest and monitor streaming transactional data for fraud and suspicious activity and report on outliers in batch or real-time.
Ingest quality data, and metadata, from multiple sources and create a governed pool of data to train AI and ML algorithms faster.