“We are happy to announce FirstEigen as one of the “100 Most Promising Big Data Solution Providers- 2016” for helping clients in maximizing ROI on their data assets as well as the business impact of their IT investments,” said Jeevan George, Managing Editor of CIOReview.
High volume and velocity data, in multiple formats, from multiple sources and through multiple platforms invariably changes and gets corrupted. “A critical Big Data challenge is the absence of good Big Data tools for Data Integrity and Data Validation. Existing tools are architected for regular data and are unable to cope with the demands of Big Data” said Seth Rao, CEO of FirstEigen.
FirstEigen’s Big Data tool, DataBuck, sieves out errors from petabyte-sized data both in real time and batch processes using massive parallel processing. Even with low-cost hardware, it processes >1.6 Bil records/min, >100x faster than any traditional approaches. Data Validation checks can be set up in less than 15 mins and requires no coding.
DataBuck, a Big Data Governance tool, guarantees data integrity via the following features:
- Big Data Quality: Ensures data is fit-for-use by checking Validity, Uniqueness (no duplicates), Completeness, Consistency, Timeliness, Accuracy and Adherence to Business Rules
- Big Data profiling: Tracks aggregate information about the data and compares with historical trends
- Big Data Matching: Matches the data with the original source across platforms to ensure integrity
- Big Data Forensics: Algorithmically picks anomalous or suspicious data
DataBuck can be used to accelerate and guarantee Data Integrity during transmission, for example, when data is moved from the mainframe to Hadoop environment or, On-Premise to Cloud or, from multiple systems into one system for analysis. It enhances performance of Master Data Management and ETL/ELT tools. DataBuck certifies data for audit and compliance related activities such as AML, BCBS 239, FINRA, Dodd-Frank. It validates data across diverse systems including Cloudera, Hortonworks, MapR, HBase, MongoDB, Datastax, HP Vertica, Teradata, Oracle, Amazon AWS, MS Azure, etc.
This article was originally published on www.prurgent.com and can be viewed in full


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