Big data: real-world benefits and ethical implications
10 January, 2014 by Andrew CollinsFour experts converge to discuss the true meaning of big data, the real-world insights it can provide and the ethical implications surrounding big data analytics.
Drilling for data
19 December, 2013 by Rob Sobers*The big question about big data remains: is this going to be another oil rush with a few winners and many losers, or will it enrich us all?
Three big problems with big data projects
21 November, 2013 by Andrew CollinsWhile a perfectly executed big data project can indeed reveal useful or surprising insights, there are some large stumbling blocks that can hamper the progress of big data projects.
The human flaws influencing big data
13 November, 2013 by Elizabeth Rudd, Director, FutureNousWill big data - the collecting of vast amounts of data about nearly everything - finally help us predict the future? Humanity's cognitive biases may prevent big data from making accurate predictions, Elizabeth Rudd writes.
Ancient maps get a high-tech facelift
07 November, 2013 by Dylan Bushell-EmblingA National Library of Australia exhibition uses modern technology to provide insight into rare and valuable old maps, as well as the origin of the geospatial industry.
Preparing for the big data revolution
30 October, 2013 by Alan Perkins*The businesses that succeed in the future will be those that gather information for analysis today, argues Rackspace's Alan Perkins.
Zettaset sues Intel in big data stoush
17 October, 2013 by Andrew CollinsBig data vendor Zettaset has sued Intel, claiming the chip maker misappropriated trade secrets related to its Hadoop management software.
Google's shared endorsements and the "creepy line"
16 October, 2013 by Dylan Bushell-EmblingGoogle's plan to use more Google+ profile data in advertising serves as both a potential model for other companies' big data monetisation efforts and as a cautionary tale.
The 8 worst practices in master data management and how to avoid them
04 October, 2013Master data management (MDM) is a key foundation for trusted data and using it strategically can differentiate companies from their competitors. It touches nearly every important activity in a company and depends on a partnership between business and IT. Avoid a dead end with your MDM program by reading this paper.
Have you got a 'big data problem'?
10 September, 2013 by Hugh Rogers*Hugh Rogers argues that we should worry less about the theoretical discussions about what is big data and focus more on the practicalities of how it can deliver value to an organisation.
Implementing real-time data quality management
30 August, 2013The Data Warehouse Institute estimates that bad information costs businesses close to $600 million each year. As a result, companies are embarking on broad-scale data quality management initiatives at a rapid pace.
Using big data to improve the customer experience
27 August, 2013 by Ananth Siva, Managing Director - Asia-Pacific, [24]7Big data is rapidly emerging as an important resource for enhancing customer relationships. Teamed with predictive analytics tools, it can be used to improve loyalty, increase sales opportunities and boost the bottom line.
CSIRO appoints data explosion leader
07 August, 2013CSIRO has named Dr Bronwyn Harch as chief of its new research division CCI, which will focus on tackling challenges including the exponential growth in data being produced.
Build a data warehouse that people actually use - and trust
30 July, 2013Business users require a holistic view of the enterprise to better understand business performance and uncover opportunities for competitive differentiation. These business requirements reflect the need to make trusted decisions in less time but most of the data they need is fragmented across many applications, which are hard to integrate. Therefore, a data warehouse is built to transform the data into a single system.
Dell Toad Business Intelligence Suite 2.0
21 May, 2013Dell has announced Toad Business Intelligence Suite 2.0, a solution that lets organisations access and extract meaningful information from traditional and non-traditional data sources.
