Advanced Analytics

Advanced Analytics

1. Related topics

   • Business Analytics
   • Business Intelligence
   • Data Mining
   • Predictive Analytics

2. Description

   • Advanced Analytics enables the rapid extraction, transformation, loading, search, analysis and sharing of massive data sets. By analyzing a large, integrated, real-time database rather than smaller, independent, batch-processed data sets, Advanced Analytics seeks to quickly identify previously unseen correlations and patterns to improve decision making.
   • Although it is related to traditional Database Management and Business Intelligence systems, Advanced Analytics dramatically increases the ability to process data in four major ways:
     • Volume: moves beyond terabytes to petabytes and exabytes
     • Velocity: enables real-time insights and actions
     • Variety: analyzes everything from click-stream data to video streams
     • Variability: manages changes in data formats and information fields

3. Methodology

   • Companies start by identifying significant business opportunities that may be enhanced by superior data and then determine whether Advanced Analytics solutions are needed. If they are, the business will need to develop the hardware, software and talent required to capitalize on Advanced Analytics.
   • To apply Advanced Analytics, companies should:
     • Select a pilot (a business unit or functional group) with meaningful opportunities to capitalize on Advanced Analytics
     • Establish a leadership group and team of data scientists with the skills and resources necessary to drive the effort successfully
     • Identify specific decisions and actions that can be improved
     • Decide whether to purchase or rent the system
     • Determine the most appropriate hardware and software solutions for the targeted decisions
     • Establish guiding principles such as data privacy and security policies
     • Test, learn, share and refine
     • • Develop repeatable models and expand applications to additional business areas

4. Common uses

   • Improve internal processes, such as risk management, Customer Relationship Management, supply chain logistics or Web content optimization
   • Improve existing products and services
   • Develop new product and service offerings
   • Better target their offerings to their customers
   • Transform the overall business model to capitalize on realtime information and feedback