Time to put the “T” back into ETL?

A hidden cost of ELT is the proliferation of costly database staging areas to do transformations. High performance ETL may be a better option

true cost of ELT

Big data use case: Offloading the data warehouse to Hadoop

The true cost of ELT Today’s business world is demanding more from the data warehouse, because more than ever an organisation’s survival depends on its ability to transform data into actionable insights. However, ELT data integration workloads are now consuming up to 80% of database capacity, resulting in: Rising infrastructure costs Increasing batch windows Longer development cycles Slower…

build your enterprise data hub

Cloudera and Hortonworks merge – good news for customers

Late last year, Cloudera and Hortonworks announced plans to merge the two companies – a move that came into play early this year. According to Tendü Yoğurtçu, CTO of our partner, Syncsort, the two companies have emerged as clear winners in the data space and gained momentum. “But each has had its own unique strengths,…

Big Data Architecture

Are you Hadooping?

“Are you Hadooping?” [Tweet this] This was the key question asked by Gartner analysts, Merv Adrian and Nick Heudecker, during their insightful Hadoop 2015: The Road Ahead webinar which you can register to watch. Their research shows that nearly 40% of all respondents have either deployed Hadoop into production or are a long way into…

Big Data Quality for Hadoop

Big data quality

Ventana’s Research recent Big Data Integration benchmark survey  supports the growing awareness that data quality and integration are the principle time sinks for big data projects. There research finds that more than 50% of the time allocated to any big data project is taken in reviewing the data for quality and consistency – not surprising given…

Why Hadoop

Hadoop: Quick Facts

Hadoop is a highly scalable, NoSQL database used to perform high speed analytics against large volumes of data. Hadoop works on the principle of schema on read, not schema on write. Any data (structured or unstructured) can be stored in Hadoop with out developing a schema. This cuts the development time scales, reduces risk complexity…