Blog
ComputerWeekly guest blogpost by Mike Ferguson, “A Decade of Hadoop”
Posted by Mike Ferguson | February 5, 2016 | BlogThis is a ComputerWeekly guest blogpost by analyst Mike Ferguson on the 10th anniversary of Hadoop’s becoming a separate Apache subproject. In the 10 years since Hadoop became an Apache project the momentum behind it as a key component platform in big data analytics has been nothing short of enormous. In that time we have […]
Is Self-Service BI Going to Drive a Truck though Enterprise Data Governance?
Posted by Amanda Dascalakis | February 1, 2014 | BlogThere is no doubt that today self-service BI tools have well and truly taken root in many business areas with business analysts now in control of building their own reports and dashboards rather that waiting on IT to develop everything for them. Using data discovery and visualisation tools, like Tableau, Qlikview, Tibco Spotfire, MicroStratagy and […]
Agile Governance in the form of Automatic Discovery and Protection Is Needed to Create Confidence in a Big Data Environment
Posted by Amanda Dascalakis | August 23, 2013 | BlogThe arrival of Big Data is having a dramatic impact on many organizations, in terms of deepening insight. However it also has an impact in the enterprise that drives a need for data governance. Big Data introduces: New sources of information Data in motion as well as additional data at rest Multiple analytical data stores […]
ELT Processing on Hadoop Will Boost Confidence in Big Data Quality
Posted by Amanda Dascalakis | August 16, 2013 | BlogIn my last blog I looked at big data governance and how it produces confidence in structured and multi-structured data that data scientists want to analyse. I would like to continue that theme in this blog by looking at what is happening in the area of Big Data governance in a little more detail. Over […]
Exploratory Analytics Vs Big Data Governance – Freedom Vs Control or Freedom with Confidence?
Posted by Amanda Dascalakis | August 9, 2013 | BlogExploratory analytics is at the heart of most Big Data projects. It involves loading data from multi-structured sources into ‘sandboxes’ for exploration and investigative analysis, often by skilled data scientists, with the intent on producing new insights. Data being loaded into these sandboxes may include structured, modelled data from existing OLTP systems, data warehouses and […]
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