mobile payments

Will quality data differentiate banks from mobile operators?

Traditional financial institutions are fighting a war against mobile operators for the lucrative mobile payments market in Africa. At stake – billions of dollars in transaction fees and deposits – particularly targeting the traditionally unbanked population. In more mature markets, such as Europe, where banking penetration is high, most mobile payments options work in partnership…

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…

rugby

Why Business Intelligence fails

The opening round of Super Rugby this last week end was a classic example of how business intelligence fails. Predicting the first round of any sporting event is always a bit of a gamble – largely because one is looking at historical data. In many cases this can be a sound strategy. In the absence of…

Rhodes University

On data management education

I have recently returned from a trip to Grahamstown where I had the opportunity to visit the the Rhodes University IS department It has been over twenty years since I graduated and I was curious to see how the curriculum has changed. In particular, I was curious to uderstand how data management is catered for…

Bury your head in the sand

Big Data: Time to Vorget about the 3 V’s?

Almost any definition of big data is based on Doug Laney’s original preposition of the 3 V’s – Velocity (the data is growing rapidly), Variety( the data comes from many sources – both structured and unstructured) and Volume (the data is big). For example, Gartner defines big data as “high volume, high velocity, and/or high…

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…