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Blog Category: Asia Pacific; Big Data; Advanced analytics; enterprise data warehouse; business intelligence; BI; analytics; Hadoop; data mining; predictive analytics; sentiment analysis; behavioral analytics; Asia Pacific
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A number of my colleagues and I attended the recent global SAS analyst event to understand the future of SAS’s business and technology strategy. It was clear to me from this event that SAS is attempting to bridge the increasing divide between “traditional” analytics and the big data and cloud-based analytics worlds.
Here’s a few of our key observations and takeaways from the event:
A greater emphasis on visual analytics. The range of tools available and the integration capabilities to enable visual analytics will be significantly improved in future releases.
Better support for governance and audit. One of the benefits that any decision support system should provide is better business governance – the transparency and auditability of how and why decisions were made and what data was used to make them. SAS continues to make good progress here.
A more encompassing view of big data. Most analytic vendors believe either nothing – or everything - has changed in the emerging world of big data. SAS’s view is generally an inclusive one, which will be more beneficial to clients long-term if successfully implemented. The SAS architecture is evolving towards supporting big data economies of scale, in theory at least.
Better integration with all forms of cloud technologies. Still operating largely at the OS virtualisation layer, SAS is nonetheless extending its portfolio to include a range of cloud-enabled architectures. We expect that client demand will drive further development here.
Some markets and industry sectors in Asia Pacific (AP) were clearly early adopters of big data initiatives, but interest has now spread to almost all subregions and verticals. The reason is simple: More and more organizations now understand the value of data for not only addressing customer demands and expectations but also for responding to changing market dynamics and improving operational efficiency.
The common link across all big data initiatives is an interest in using more types of data, from more sources, to enable timelier, better-informed insights. With that in mind, we’re seeing two common use cases driving big data awareness and investment across industries:
These initiatives are a response to increasing customer expectations for more personalized service. Typically centered on improved customer insight and engagement, organizations are seeking ways to better access and leverage customer data to improve understanding, more effectively personalize relationships, predict behavior, and ultimately deliver improved value via increased customer intimacy. Specifically, the sheer volume of readily available and increasingly accessible data that organizations can leverage — such as location data from mobile devices, apps and personal data on customer preferences and relationships from social networking sites — is driving big data initiatives. Early adopters typically include telcos, retailers, banks, insurance firms, and citizen-oriented eGovernment initiatives.
In a previous post I highlighted that disruptive technologies don't even need to be implemented to be disruptive. The mere fact that vendors and other organisations are either creating or being swept up in the hype can be a major disruption to any organisation.
In our soon to be released research on Asia Pacific Trends for 2013 we highlight a number of disruptive trends that are affecting organisations all all types and sizes - whether commercial, government or not-for-profit. None is more profound than the impact that big data will have on Asia Pacific organisations in 2013. The Asia Pacific region has a very broad spectrum of capabilities, maturity and variations in its outlook and optimism. Big data and deep analytics are two areas where we see significant disruption occurring. The Asia Pacific 2013 trends report highlights some of these differences in Asia Pacific and calls out specific implications for specific markets. There's also more detailed information in our Big Data in Asia Pacific report, also due out shortly.