Published: 06 July 2015
Summary
As this year's Hype Cycle clearly indicates, the field of advanced analytics and data science is extremely innovative. Some important infrastructure concepts — including analytic marketplaces — allow the use of advanced analytics to scale much better, but much more development in this area is needed.
Included in Full Research
- What You Need to Know
- The Hype Cycle
- The Priority Matrix
- Off the Hype Cycle
- On the Rise
- Analytics Marketplaces
- Chief Analytics Officer
- Natural Language Generation
- Model Factory
- Smart Data Discovery
- Crowdsourcing of Microwork
- Hadoop-Based Data Discovery
- Graph Analysis
- In-DBMS Analytics
- Data Lakes
- Deep Learning
- PMML
- Uplift Modeling
- Citizen Data Science
- Real-time Analytics
- Self-Service Data Preparation
- Optimization
- At the Peak
- Emotion Detection/Recognition
- Prescriptive Analytics
- Event Stream Processing
- Geospatial and Location Intelligence
- Spark
- Predictive Analytics
- Machine Learning
- Sliding Into the Trough
- Natural-Language Question Answering
- Model Management
- Speech Analytics
- Linked Data
- R
- Text Analytics
- Video Analytics
- Climbing the Slope
- Ensemble Learning
- Simulation
- Load Forecasting
- Appendixes
- Hype Cycle Phases, Benefit Ratings and Maturity Levels