This full day workshop examines the trends in analytics deployment and developments in advanced technology. The implications of these technology developments for data foundation implementations will be discussed with examples in future architecture and deployment. This workshop presents best practices for deployment of a next generation data management implementation as the realization of analytic capability for mobile devices and consumer intelligence. We will also explore emerging trends related to big data analytics using content from Web 3.0 applications and other non-traditional data sources such as sensors and rich media.
This full-day workshop examines the trends in analytic technologies, methodologies, and use cases. The implications of these developments for deployment of analytic capabilities will be discussed with examples in future architecture and implementation. This workshop also presents best practices for deployment of next generation analytics.
Organisations often struggle with the conflicting goals of both delivering production reporting with high reliability while at the same time creating new value propositions from their data assets. Gartner has observed that organizations that focus only on mode one (predictable) deployment of analytics in the construction of reliable, stable, and high-performance capabilities will very often lag the marketplace in delivering competitive insights because the domain is moving too fast for traditional SDLC methodologies. Explorative analytics requires a very different model for identifying analytic opportunities, managing teams, and deploying into production. Rapid progress in the areas of machine learning and artificial intelligence exacerbates the need for bi-modal deployment of analytics. In this workshop we will describe best practices in both architecture and governance necessary to modernise an enterprise to enable participation in the digital economy.
Optimiser choices in determining the execution plan for complex queries is a dominant factor in the performance delivery for a data foundation environment. The goal of this workshop is to de-mystify the inner workings of cost-based optimisation for complex query workloads. We will discuss the differences between rule-based optimisation and cost-based optimisation with a focus on how a cost-based optimization enumerates and selects among possible execution plans for a complex query. The influences of parallelism and hardware configuration on plan selection will be discussed along with the importance of data demographics. Advanced statistics collection is discussed as the foundational input for decision-making within the cost-based optimiser. Performance characteristics and optimiser selection among different join and indexing opportunities will also be discussed with examples. The inner workings of the query re-write engine will be described along with the performance implications of various re-write strategies.
Big Data exploitation has the potential to revolutionise the analytic value proposition for organisations that are able to successfully harness these capabilities. However, the architectural components necessary for success in Big Data analytics are different than those used in traditional data warehousing. This workshop will provide a framework for Big Data exploitation along with recommendations for architectural deployment of Big Data solutions.