Creating Data Products in a Data Mesh, Data Lake or Lakehouse for Use in Analytics (9-10 June 2022, Stockholm)
Smart Infrastructure & Smart Applications for the Smart Business – Infrastructure & Application Performance Monitoring
Data Warehouse Automation & Real-time Data – Reducing Time to Value in a Distributed Analytical Environment
Request information on running this seminar as an Onsite (can be given as Live Streaming training)
Although analytics in many organisations is well established, it is still the case that perhaps no more than 25% of employees make use of reports and dashboards from BI tools with even fewer using machine learning models or AI. There is still a long way to go if companies are to realise the promise of using ML and AI to automatically prevent problems, seize opportunities and continually optimise business processes in everyday business operations.
The vision that many executives have is to make use of BI, ML and AI to increase the level of automation and to enable everyone in the company to contribute towards improving business performance. They want to create an ‘always on’ data and AI-driven intelligent business where BI and machine learning models are deployed right across the business so that every person, and every application, in the enterprise is able to leverage the right insights at the right-time in every activity to help them contribute to the overall performance of the business. Therefore, it should be possible to embed BI and machine learning models into operational business processes to guide and drive decisions and actions in everyday business operations. It should also be possible to automate more using self-learning AI. This would move organisations towards creating intelligent applications, and utilising AI driven automation for right-time business process optimisation and decision management. This includes embedding analytics into all customer facing applications and websites to enable a personalised customer experience as well as partners and suppliers being guided by BI, alerts, and recommendations. The objective is to move towards automated, self-learning, AI-driven business operations.
To make this possible requires:
- Trusted and compliant data
- BI web services to integrate BI into operational business processes
- Developing and deploying machine learning models (ML) for use in automatic real-time scoring and analysis
- Real-time monitoring of operational events to detect exceptions and opportunities as they happen
- On-demand and event driven data integration for real-time analytics
- On-demand and event driven reporting
- Rules engines to make automatic decisions and take automatic actions
- Using prescriptive machine learning models for automated alerts
- Using prescriptive machine learning models for live recommendations
- Reward oriented re-enforcement learning
- Guided analytics
- Dynamically guided smart processes
- Data governance for trusted data
- Live dashboards and scorecards for situational awareness
- Dynamic event-driven budgeting and planning
This one-day seminar shows how you can embed BI, ML and AI-automation into applications and processes to make your company data and AI-driven. The purpose is to achieve ‘always on’ business optimisation, dynamic planning by automating, guiding, and empowering employees, business partners, suppliers, and customers to make better decisions to improve business performance. It provides a roadmap and methodology to creating the right-time intelligent enterprise by taking an in-depth look at the technologies and methodologies needed to make it happen.
This seminar is intended for business and IT professionals responsible for information delivery, business integration and leveraging BI, ML and AI in operational environments. It assumes that you have already built analytical systems and are now looking to leverage insights produced in everyday operations.
Attendees will learn how to justify, architect, and integrate AI, machine learning models and business intelligence into operational business processes and applications as part of a coordinated program to improve business performance. They will learn how to use automatic real-time event processing to monitor operational events as they happen to detect problems, identify opportunities, and drive and guide business operations. They will learn how to create intelligent apps and how to use AI to automate tasks. Attendees will also understand how to use real-time data integration, on-demand decision services, prescriptive machine learning models as a service, BI web services, queries, real-time decision engines, enterprise alerting and business process automation to put analytics to work in driving every-day business operations.