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.
In an increasingly data-driven world which impacts daily on key business processes, it is easy to feel overcome by events.
- Deploying event-driven architecture
- Managing the flow of disruptive forces
- Limiting the impact on the systems we rely upon
- Software scalability required
Intelligent data governance
As organisations continue to utilise AI and machine learning to drive business insights, whilst simultaneously managing existing challenges which threaten the normal functioning of business, from achieving efficiencies and meeting regulatory requirements, the benefits of
intelligent data governance only serves to increase in importance.
Historical data governance models can no longer manage the complexity of today’s business landscape.
- Supporting cutting edge-disruptive tech-led projects
- Delivering measurable business benefits
- Being more operationally efficient
- Supporting the evolving customer expectations
Analytics at speed and scale
Compared to just a few years ago, the data acquisition capabilities of both medium and large enterprises have increased massively. Despite such increases in data monetisation efforts, many are still relying on databases built to handle 2016 volumes. This has resulted in delayed reporting, which in turn impacts on taking data and producing information which drives insights.
We address a leading analytics platform being utilised by the world’s most successful corporates to meet the challenge of accelerating BI in order to reveal previously unseen contexts.
Big data analytics for every business user: self-service analytics
One of the leading trends within the big data analytics space is the democratisation of access. Being able to consolidate multiple sources of data for easier analysis benefits the business as it expands the capabilities of key decision-makers and influencers from a non- technical, data science-led background to gain insights quicker and make better informed decisions.
With the deployment of self-service analytics, you can visualize big data with engaging, state-of-the-art graphics and gain business insight in just five minutes, no matter how much data.
Leveraging your data visualisation capabilities
Whilst the reality and hype of machine learning can sometimes clash in the enterprise environment, the evidence shows us that effective deployment can lead to the refinement of an expansive set of data and the identification of data which leads to the feted goal of being truly information-driven in order to drive BI.
Combined with data visualisation, ML can be a useful tool in meeting the challenge of making sense of data.
- How virtualisation can maximise your ML analytics
- How virtualisation drive insights and connects data at speed
- Real-world examples of data virtualisation and ML in action
The AI Revolution: Increasing efficiencies and saving your employees time
Using the example of an insurance corporate, we will highlight the role played by AI in assessing fraudulent insurance claims, how this reduced the investigation period from a 1-hour human-led exercise to an AI-led few seconds.
- Transferring the analytics exercise to AI
- Reducing the room for human error
- Freeing up your human capital