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    • Home
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    • Formcept
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    FORMCEPT: Expediting the Process of Data Driven Decision Making

    Conventional data warehousing technology focuses on unifying the internal data, which is predominantly transactional, and derive business intelligence out of it. However, this is not effective in the current business scenarios because transactional data only accounts for 14 percent of the available data and the remaining 84 percent is unstructured data that also holds ample value. Unless both structured and unstructured data, whether internal or external, are unified, it is impossible to build a holistic view of the business problem. Further, Unified data view and consistent insights need orchestration of variety of technologies that is of prime concern for enterprises. FORMCEPT, headquartered in Bangalore, brings a solution to this problem in the form of a state-of-the-art “Unified Data Analysis product” called MECBOT.

    MECBOT is an effort to make content analysis accessible to everyone, be it an enterprise, an individual or a device. “The MECBOT dramatically reduces the pre-processing time involved in the analytics cycle and makes the data available in consumable form for further analysis,” says Suresh Srinivasan, Co-founder, FORMCEPT. MECBOT not only provides a unified interface for storing and querying datasets but also provides batch processing, stream processing and interactive analysis out of the box.

    It is built on top of NoSQL technologies, like- HDFS, HBase for storage, systems like Map-Reduce, Spark, Shark and Storm for data processing and utilizes the power of graph database, key-value store and index store to provide a seamless experience for the end users. The platform incorporates the concepts of lambda architecture and can be deployed either On Premise or on Private Cloud.
    Redefining Data Analysis

    FORMCEPT believes that unless data is unified, standardized and semantically harmonized with minimal noise, it is impossible for downstream analysis to derive consistent insights. With that belief, MECBOT is designed to maintain a managed, semantically enriched data reservoir which enables each and every individual to access the data and perform various analysis on their datasets.

    MECBOT uses FactorDB, an innovative metadata handling methodology, which sits on top of proven NoSQL technologies, like key-value stores. The platform enables the enrichment of content using a knowledge base built on the concepts of LinkedData to identify precise context and extend across domains. It also seamlessly connects data across multiple sources, using thepatent pending Data Folding ™ techniques to discover the relations and patterns. By using MECBOT, Text Analysis, Graph based analysis and Statistical analysis can be done at a scale without worrying about volume, velocity and variety. It also scales horizontally and vertically on commodity machines.

    Unified Data Analysis

    MECBOT addresses the creation of unified data assets efficiently. Its Data Ingestion Module provides Visual Interface where one can configure various structured, unstructured and semi structured data sources. Once the data is configured, various transformations on the data can be defined visually. The data is stored efficiently in FactorDB. While the data is getting stored, FORMCEPT applies advanced mathematical concepts and advanced NLP techniques to create DataFolds™ across the unified data assets. Datasets stored in FactorDB are available for various analysis either through APIs or through SQL interface or “Free textual search.” The entire platform can be deployed in private cloud of choice or on premise and it scales elastically both vertically and horizontally. FORMCEPT wants to leverage its strong product aims to transform into a global customer focused company.
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    formcept Info

    Company
    formcept

    Headquarters
    ..

    Management
    Anuj Kumar, Chief Architect & Co-founder

    Description
    Helps enterprises to get actionable insights from their data faster to significantly reduce the time taken to convert data into decisions

    2016

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