One of the best ways to speed up big data processing operations is to not process so much data in the first place; i.e. to eliminate unnecessary data ahead of time.
Big data integration activities can happen outside the database in an extract, transform, load (ETL) environment, or inside the database in ELT:
One example of an ELT operation would be Informatica’s Pushdown Optimization option, in which users transform data in a relational database like Oracle, or in Teradata.
As IRI CoSort integrates and stages big data from a variety of sources, it plays a natural role in producing data for reporting and analytics.
CoSort not only transforms data for loading data warehouse tables, it can report at the same time, or feed data in filtered, aggregated, sorted, and properly formatted subsets (like .CSV
In 1992, Digital Equipment Corporation (DEC, long since acquired) asked IRI to develop a 4GL interface to CoSort in the syntax of the VAX VMS sort/merge utility.
Big Data Problem Big data volumes are growing exponentially. This phenomenon has been happening for years, but its pace has accelerated dramatically since 2012. Check out this blog entitled Big Data Just Beginning to Explode from CSC for a similar viewpoint on the emergence of big data and the challenges related thereto.
Hadoop is an increasingly popular computing environment for distributed processing that business can use to analyze and store huge amounts of data. Some of the world’s largest and most data-intensive corporate users deploy Hadoop to consolidate, combine and analyze big data in both structured and complex sources.