Golden Source

Finding the single source of truth in corporate data
Traditionally, organisations struggled to achieve this goal because their customer data was lying in multiple systems and different file formats (PDFs, Word and Excel documents, charts, images, scans, videos, etc.).   Technology was seen as a limiting factor to integrate this scattered and massive data and meet the business goals.  fraXses brings […]

By |August 20th, 2016|Data, Federation, Virtualisation|

Federation in full flight in online gambling – securely


Create a single view of disparate encrypted data sets across the network which will offer the same level of functionality that would be possible from a Master Data Warehouse.  In addition the system must allow real-time analysis of player behaviour and provide and automated, yet personalised set of promotions to increase player engagement.


Users based in London
Config team in […]

By |July 20th, 2016|Analytics, Data Ingestion, Federation, Gaming, Security, Virtualisation|

Agile BI and data solutions

Guest article by Steven Offen
Can we deliver BI and data solutions Agile? Not doing things the way we have been!
I have spent many years trying to perfect agile delivery in Enterprise Business Intelligence (BI) environments. What I have always struggled with is how you line up all the teams needed, at the same time, to be truly agile.

Usually, you have […]

By |June 20th, 2016|Data Ingestion|

Death of the traditional Data Warehouse

Guest article by Steven Offen

I have recently been on training for a new federated data platform solution called fraXses. The promise was that the solution could consolidate data from any data source without any ETL development simply by using a configuration GUI. These solutions have been spoken about for many years but this is the first I have seen, that […]

By |May 20th, 2016|Data, Data Ingestion|

Rich Data, Poor Data

…What the Data Rich Do – That the Data Poor and the Data Middle Class Do Not!

Guest Article by By Shelly Palmer, President & CEO of Palmer Advanced Media
Generally speaking, there are two kinds of companies in the world: data rich and data poor. The richest of the data rich are easy to name: Google, Facebook, Amazon, Apple. But you don’t need […]

By |April 20th, 2016|Algorithms, Analytics, Data, Machine Learning|

Components of a Modern Analytics Platform

Guest article by Martin Rennhackkamp

In order to cater for the demands of a modern data-centric and analytics-driven organisation, one needs a more extensive ecosystem for analytics than what a traditional simple “data source – ETL – data warehouse – dashboard” environment can cater for.  This is especially relevant considering the more complex data types and structures and the more dynamic data […]

By |March 20th, 2016|Analytics, Data|

Halting decline in Student retention


The University is operating in a competitive regional market where the deregulation of fees coupled with increasing competition for traditional regional markets, is presenting the challenge of increasing student enrolments and halting the decline in student retention.

The University Management put in place a number of initiatives but has been frustrated by an inability to measure and predict the effectiveness of these using available […]

By |February 20th, 2016|Data, Education, Social Media|

Maximise player engagement & satisfaction


In a multi-room, multi-game environment what are all your players doing right now?  With 500,000+ players, in multi-room, multi-game environments spread across the globe…   The challenge is to intervene with individual players to reduce churn and improve conversion.  Creating a “player journey” to track each player and identify the most appropriate intervention points in real-time.


Using a mixture of data relationship discovery, data analysis, pattern […]

By |January 20th, 2016|Algorithms, Analytics, Data, Gaming, Pattern Recognition|

Liquidity Risk Management

Volumes of data are increasing rapidly due to cash flow orientation and banks are struggling to perform finance and risk management in real time.  This is especially acute for liquidity risk management where the current spread sheet applications perform slowly due to the massive amounts of data.  Compliance with new liquidity rules under Basel III is a must and especially […]

By |December 20th, 2015|Data, Financial Markets|

Faster retail analytics


Help a Large fashion retailer that was taking 36hrs to process 2 years of ePoS data (8 Billion records) within the traditional business intelligence system. (Microstrategy & Oracle). Merchandising team required predictive analytics and better performance to enable calculations on sales data to enable stock to be in the correct stores for the following week. (Calculations would include last week’s […]

By |November 20th, 2015|Analytics, Data, Retail|