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Big Data & Analytics Innovation Summit, Australia: Day 1 Highlights


Highlights from the presentations by Big Data leaders from GE Capital, Datawatch and MapR Technologies on day 1 of Big Data & Analytics Innovation Summit 2014 in Sydney, Australia.



Big-Data-Analytics-Innovation-SummitThe Big Data Innovation & Analytics Summit (Sept 17-18, 2014) was organized by the Innovation Enterprise in Sydney, Australia. It brought together a large gathering of senior business executives leading Big Data initiatives in Australia. The summit brought together business leaders and innovators offering solutions and insight in the Big Data space. Big Data Innovation helps utilizing data-driven strategies and discovering disciplines that change because of the advent of data. With a vast amount of data now available, modern businesses are faced with the challenge of storage, management, analysis, visualization, security and disruptive tools & technologies.

Here are highlights from Day 1 (Sept 17, 2014):

Cameron PartridgeCameron Partridge, Director, Digital Analytics & Information Management, GE Capital talked about how combining digital analytics with user experience research can help optimize customer experience. He emphasized that companies should go for valuable data rather than just huge amount of data. Today, digital channels are opening up more ways for one to engage with one's customers than ever before, and these channels can be a very fast cost-effective way to drive business performance. However, if one gets the customer experience wrong, then digital channels become a very fast way to destroy value instead. Missed conversion opportunities, opt-outs, do-not-solicit requests, and negative brand experience, all have a real impact on the bottom line.

Opportunities to engage with customers are precious and one needs to ensure these interactions are optimized. Using the power of digital analytics, one can reach a deeper understanding of one’s customers’ behavior and allow every hypothesis to be tested. Combining this with User Experience (UX) research, one can understand why customers behave the way they do and how they would like their digital experience be improved. He concluded saying that we should not forget/ignore the human side of big data and decisions should not be taken without taking into account customer experience.

Pete SymonsPete Symons, Regional Director, Datawatch talked about how real-time visual data discovery is demystifying big data. Giving a quick overview of Datawatch, he differentiated traditional BI/data-warehousing with real-time analytics visualization as the former one presents what you already know but in a very nice way and the latter one shows what you don’t know but should know. Talking about return on real-time visualization, he mentioned organizations utilizing real-time data visualization have outpaced all others in several key metrics. Event streams come from various sources such as IOT (Internet of Things), Web click streams, commercial data, log files, etc. He gave some interesting use cases and data visuals.

Data is increasingly available at real-time speeds, and from disparate sources such as databases, PDF files, web pages, machine data and text files. This trend is only going to grow as organizations demand the ability to make quicker decisions with all the information available. It is no longer feasible to analyze only structured data sources, and to wait until the end of the month, or week to do so for reports to become available. Things can go wrong intra-day! Organizations should learn how Visual Data Discovery enables the identification of patterns and outliers in data at any speed, and from virtually any source, to highlight 'what you don't know, but should'.

Henry LaiHenry Lai, Principal Consultant, MapR Technologies delivered a talk on "Ensuring Production Success for Hadoop". Google recently invested $110 million in MapR. He briefly explained basics of Hadoop and its working. He mentioned that big data trends are forcing a revolution in enterprise architecture.

2014 was expected to be the year when Hadoop goes mainstream. A majority of companies moved Hadoop from small-scale test environments into full-fledged production deployments. However, enterprises should complement Hadoop production success with an architecture designed specifically for business-critical applications. MapR ensures seamless data access and integration. It runs both online, to support analytical processing and applications reliably on one platform.

Highlights from day 2.

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