Trehanz EDI is a full-fledged ETL for migrating all the Enterprise Data Warehouse workloads and storage from existing systems
to a Hadoop based cluster. It provides an intuitive user interface to import all the data from existing data sources into a Hadoop cluster. Enterprises can migrate their existing Informatica or Datastage Ascential or proprietary ETL jobs to Trehanz EDI fairly quickly. Within a span
of a couple of weeks an enterprise can get started with a Hadoop based data warehouse. It can pull data from all existing data sources, file systems and applications of an enterprise into a Hadoop cluster. One key hallmark of Trehanz EDI is the ease with which a user can enrich, transform, slice and dice the data ingested into the hadoop cluster. It also provides complete access to the lineage and meta-data information of the data without having to deep dive into every nitty-gritty involved with migrating to a Big Data technology based system. It provides a Hive based interface to enterprises’ existing BI tools like Tableau, QlikView, Microstrategy.
In short, it makes the Hadoop journey of an enterprise a breeze by drastically cutting down on learning curve and time needed to get started with a Big Data Enterprise data warehouse.

Enterprises can leverage all the goodness of having a Hadoop cluster namely:

  • No need to purge data or archive it onto another media or archival systems.
  • There is no limit to how far back the users can go to analyze the data and hence no need for random sampling of small portions of data and meaningless extrapolation of a small set of data. The insights produced through are accurate down to the last piece of transactional data available in the system.
  • Hadoop’s inherent scalability and scaling out capabilities provide the advantage of unlimited storage using commodity hardware with storage costs at low as less than 50 cents/ GB.
  • Ability to host on cloud and leverage the pay per use model of cloud eliminates the need to maintain big data centres for processing of massive amounts of data. The total cost of ownership of system is cut down drastically depending upon usage of cloud.
  • Prepare an enterprise for its hadoop journey and the ability to deal with unstructured data characterized by the volume, velocity and variety. Enterprise can start planning for leveraging orthogonal views of customer behavior by factoring in the unstructured streams of social and mobile data.