ABOUT THE FORUM
We are collecting more data than ever today. Consumers are constantly generating data from various interactions. Big data is a collection of data from traditional and digital sources inside and outside your company that represent a source of ongoing discovery and analysis. It has been described in a variety of different ways since the term was coined, so it is no wonder that many are confused and intimidated.
However, exactly how to use all of this information in a way to benefit your business has become a major issue. How can you identify such issues and make wiser decisions going forward?
Research shows the predictive analytics market will reach $5.2 to $6.5 billion by 2018/2019; they are calling it the game changer as it has helped reinvent 6 industries (Healthcare, Manufacturing. Marketing & Financial Services, Government, Credit Risk Insurance and Workforce Management). This is why so many organisations are turning to predictive analytics to increase their bottom line and competitive advantage.
Corporate Parity presents the Global Predictive Analytics Forum 2018, that will provide attendees with the opportunity for learning through case study presentations, interactive panel discussions and multiple networking opportunities. During these 2 days, event analytics pioneers will share their ideas on how to shape the future of your organisation through effective data analysis. Register today and secure your place at this top-tier event.
- Role of predictive analytics in modern business strategies
- Data analytics techniques
- Applying predictive analytics to your business: where to look?
- Practical real-world use-cases from across the globe
- How should analytics be applied to infer the social context of customers?
- How does this work in practice for a CRM and targeted marketing programme?
- What are the practice and ethical issues that this raises?
- Lean Six-sigma framework
- Applying Lean Six Sigma in the IIoT age & challenges
- 3 steps approach : correlate data source, perform advanced analytics, derive and implement measures
- Benefits: What you can expect?
- Model capacity (aka expressiveness)
- Model interpretability (aka understandability)
- The enablers:
- Algorithmic improvements for learning
- Hardware speedups
- Data: the new currency
- Growth in semi-supervised and Bayesian techniques
- Reinforcement learning
- Differential Privacy