International Data Management, Analytics and Business Intelligence Summit 2015
Most companies today use Business Intelligence (BI) reports and dashboards to measure business performance at strategic, tactical and operational levels. However today, business is demanding much more than just descriptive BI. Many organisations today want to go beyond this by implementing predictive and prescriptive analytics. To that end, many companies are now establishing advanced analytics teams in business departments to help develop new advanced and predictive analytics that can be deployed in real-time and in historical environments to produce new insights for competitive advantage. This is happening both in traditional Data Warehouse and in new Big Data environments where data scientists are analyzing new multi-structured data sources to produce new models and insights. Also business analysts are using these analytics in visual data discovery tools to help predict and forecast the future. In addition analytics are being embedded in applications to help embed recommendations, alerts and forward looking insights in processes and applications to optimize business operations.
Another challenge is the number of data sources that companies are now accessing to capture data for analysis to produce deeper insights. Clickstream data, social network interaction data, weather data, sensor data, location data and news feeds are just a few of these. The question is what should companies do with this data? How should it be organized and stored? The emergence of Hadoop has seen data cleansing and integration being offloaded from Data Warehouses, to cheaper lower cost Hadoop environments but is this at the expense of Data Governance? How do you govern data in Big Data environments and traditional Data Warehouses with confidence? What if structured data is brought into Hadoop?
This Summit examines trends in Business Analytics and Business Intelligence and examines how organizations should manage and govern all this data going forward.
- BI Organisation 2.0 - The Expanding Role of Data Scientists and Business Analysts
- The Impact of Self-Service Data Integration – Data Chaos or Data Governance?
- Agile Data Modelling using Data Vault and Data Virtualisation
- Best Practices in Data Discovery and Visualisation
- Advanced and Predictive Analytics for the Big Data Enterprise
- Graph Analytics and Visualisation
- Actionable Intelligence Using Storytelling and Collaborative BI
- New Analytics Architectures – The Role of a Data Reservoir and Data Refinery