Big data processing enables enterprises to mine and analyze large unstructured data sets quickly for better business insight and improved decision-making. Apache Hadoop has matured to the point where it is at the center of the next-generation of enterprise data architectures.
Semantify is pleased to have earned the HortonWorks Certification as an ISV partner at the MDS level, integrating with HDFS in HDP. Integration with the Hortonworks Data Platform (HDP) enables customers to rapidly acquire, prepare and deliver Apache Hadoop with Semantify’s industry-leading cognitive search platform.
Leveraging HDFS’s ability to connect to multiple data sources and types, Semantify provides Data Extraction, Modeling and Dynamic Reporting and Dashboarding. The platform can be leveraged in analyzing both structured and unstructured data sources including PDFs, Excel sheets, Word Documents, RSS feeds and XML. The platform comes with prebuilt ontologies for Financial Services, Healthcare and Insurance, out of the box connectors to multiple data sources and offers a Natural Language querying capability for adhoc insights.
To certify partner technologies, Hortonworks reviews each product for architectural best practices, validates it against a comprehensive suite of integration test cases and performs benchmarks for scale under varied workloads, while comprehensively documenting every step in the process.
Semantify has achieved the following certifications:
HDP – HDP Certified badge indicates this partner’s solution has been certified to work with HDP; reviewed for architectural best practices and validated against a comprehensive suite of integration test cases, benchmarked for scale under varied workloads and comprehensively documented.
Yarn Ready – Apache Hadoop YARN is the data operating system for Hadoop 2. YARN Ready certification recognizes applications that integrate with YARN and process data via pushdown computation to the cluster. Examples of a YARN ready solution includes an application that has native YARN application master or leverages scale-out capabilities of the platform like Hive, Spark and MR2.