Barry Devlin presents two sessions:
- New Analytics Architectures – The Role of A Data Reservoir and Data Refinery
- BI Organisation 2.0 – The expanding role of Data Scientists and Business Analysts
New Analytics Architectures – The Role of A Data Reservoir and Data Refinery
New technology, especially in the Hadoop space, has become increasingly popular and pervasive in the past few years. In order to make sense of these tools, vendors, consultants and even customers have begun to sketch architectures to position the pieces and fit the function together. Thus, we have seen the emergence of architectural diagrams of Data Reservoirs (also known as Data Lakes) and Data Refineries, to name but a few of the more common. However, this is still very early days. The definitions remain as varied as their sources and their claims controversial.
This session sheds light on these new analytics architectures:
- What is a Data Reservoir/Lake and how does it compare to a Data Warehouse?
- What is a Data Refinery and what is its relationship to ETL?
- What are the benefits and drawbacks of these new architectural components
- Do Reservoirs and Refineries replace or complement traditional architectural thinking?
- What technologies and tools are needed?
BI Organisation 2.0 – The expanding role of Data Scientists and Business Analysts
For more than twenty years, businesses have striven to define and deliver BI according to a well-defined organisational model typically called BI Centre of Competence (or Excellence). This model provides a largely singular and formal approach to delivering consistent and controlled data. Today, faster business needs have led to an increasing emphasis on data discovery and instant self-service analysis. Big data technologies and external data sources have reduced focus on traditional database and data management. The result has been suggestions that radical, new ways of organising and managing information are required.
This session examines the evolution of this thinking and shows how:
- The roles of business analysts and data scientists are changing and expanding
- A balance of formal control and innovative data use can be achieved
- A new Adaptive Decision Cycle can support the transition from exploration to production
- Business and IT must define a new, symbiotic approach to collaboration to derive maximum business benefit from information and technology