Thursday 22nd June, 2017
The Seminars will take place from 12.15 – 13.00.
Delegates will be able to attend one seminar at the event. No pre selection is required – delegates will be able to select which session they attend onsite.
Build Big Data Models in Minutes with BI Office from Pyramid Analytics
Ian Macdonald, Principal Technologist, Pyramid Analytics
Lofty and academic discussion of Big Data is all very well, but in the end a business user needs to be able to create analytic models easily, quickly and simply, accessing data no matter where it might reside. Watch how analytic Models can be created in minutes and data analysed and visualised immediately for maximum business impact
Machine Learning: from Exploration to Production
Wim Stoop, Senior Technical Marketing Manager EMEA, Cloudera
Dr. Chris Royles, Sales Engineer, Cloudera
Machine learning is all about the data, but it’s often out of reach for analytics teams working at scale. Cloudera customers such as Wargaming.net can store, process and analyse 550 million events each day to help them improve gamers’ experiences and increase customer lifetime value.
Whether you are just starting out with machine learning and advanced analytics or you have already begun the journey, this workshop will include practical exercises to inspire you with new ideas to take back to the business.
Discover how you can accelerate machine learning from exploration to production by empowering their data scientists to take advantage of their favourite languages, frameworks, cloud resources and more in one unified platform.
Taming the Data Lake
Mark Pritchard, Sales Engineering, Denodo
Big Data technologies offer a way of consolidating the continual flow of raw data generated from interactions between the enterprise and the external world and also internally within the enterprise itself.
While consolidation of data into a Big Data Data Lake seems a good way of harnessing this stream of data, it poses several challenges that can reduce the effectiveness of turning this raw data into an enterprise usable asset.
This session highlights how data virtualization is being used to tame the turbulent nature of data lakes by improving enterprise readiness and providing access to enterprise relevant data quickly and cost effectively. This will be illustrated with two client case studies of data virtualization deployed in this context.
The Value Metrics for the CDO
Abhas Ricky, Head of Value Management, Hortonworks
Measuring the value of any digital engagement is the no1 challenge faced by digital leaders across industries (per a Mckinsey global institute report – only 15 percent have been able to make any sense of it). This presentation will cover:
- The challenges faced by data and digital leaders in the age of the fourth industrial revolution
- The key metrics to measure ROI for digital engagements
- New employee engagement methods needed in this digital era
- Hortonworks’ value based engagement methodology
Machine Learning for Real Time Anomaly Detection & Analytics
David Drai, CEO & Co-Founder, Anodot
As data-heavy businesses grow, detecting business incidents – revenue leaks, obstacles to efficiency, or new business opportunities – can be a major challenge. Manual tracking, static thresholds, or even standard BI visualizations, are not enough for complex, seasonal data, and data professionals today tell us they are overloaded with dashboards and alert storms.
Automated business incident detection based on machine learning can discover and highlight unusual patterns in any type of metric. It allows you to quickly identify things like a decrease in number of users, revenue, conversion, increase in application errors, or track any and all metrics that will allow you to identify and resolve issues immediately, not days or weeks later. David will present the benefits and challenges of implementing machine learning-based anomaly detection, sharing industry benchmarks and case studies, and discussing how it can help you gain more visibility into your data and gain competitive advantage.
The Keys To Digital Transformation
Pinakin Patel, Senior Director EMEA Systems Engineering , MapR
The most advanced companies are able to transform their data into value and not focus solely on queries and Data Lake. They actively integrate analytics into their operations by focusing on the development of data-centric applications. Real-time adjustments to improve sales, reduce costs or mitigate risks are based on applications that reduce the latency of multiple data sources. Pinakin Patel will present three concrete uses in the advertising / media, financial services and health sectors to highlight how these applications are dynamically developed, deployed and updated by customers. It will demonstrate why a data-centric approach is fundamentally different from more traditional applications.