Session ONE – Extracting Value and Insights from Enterprise Data
- Exploring the Big Data value proposition for your enterprise
- Transforming your organisation into a data-driven company
- Harnessing disruptive technologies like AI and Machine Learning for better business value
- Posing and answering new business questions
- Identifying trends and patterns in your data assets to better understand your customers, users, transactions and systems
- Operationalising new processes based on the insights you discover
- Improving business forecasting and decision-making
- Turning data into new visibility and finding areas of your organisation that can benefit from harnessing data
- Gaining real-time actionable insights from your data
- Measuring the effectiveness of your Big Data programme
- Awareness of Big Data’s impactfulness and limitations
The Conference Chair's Opening Remarks
Keynote Address: Exploring the Disruptive Potential of Neural Networks and Machine Learning
Big data has moved to a new stage of maturity and its impact is set to grow. Enterprises were once looking at historical data but advances in database technology and system processes has led to near real-time data collection and analytics reports. What’s more, the ability to access large volumes of data is leading to a rapid evolution in the application of AI and machine learning techniques. Enterprises are moving beyond traditional linear models and hypothesis-based approaches to self-learning algorithmic intelligence that is capable of telling a story of its own with limited and next to no human input.
Our opening keynote explores the disruptive potential of these new areas of development for enterprises. We look at:
- Potential applications of AI and Machine Learning for enterprise
- How businesses can adapt and embed disruptive technologies
- Leveraging your data using machine learning
- Applying machine learning to move beyond traditional data modelling techniques
- Constructing models and algorithms that learn from data
- Limitations and biases, and how to overcome them
Enabling your Business to make Smarter Decisions
To allow data initiatives to grow within large organisations it is essential that stakeholders and the C-Suite are fully engaged with the value big data can offer. How is this done? By creating and adhering to measurable indicators of value when it comes to big data.
This session will look at:
- Setting achievable and measurable key performance indicators that will help a data programme stay relevant and justify its costs
- The benefits of a data strategy – key components, challenges, risks and rewards
- Using your data to react to changing commercial environments
- Choosing metrics that demonstrate value – from the customer to the board
- Focusing on measuring and standardising the time it takes to make data available and how quickly you are developing insights and efficiencies
Are We Asking the Right Questions of Our Data?
Data is only as good as the questions we ask of it. Too often data scientists treat the insights they derive as infallible and yet, the meaning we interpret from data is not only subjective but prone to biases. We consider:
- The Dos and Don’ts of asking good data analysis questions
- Overcoming cognitive biases that affect the way you approach data problems
- Changing attitudes to data interpretation to increase awareness of imperfection in data science
- Understanding if your data contains the relevant information to answer your questions, and if you have enough material to answer them fully
Building Deeper Customer Relationships Powered by Data
Recommender systems have revolutionised the way businesses engage and retain their customers. While bespoke goods and recommendations used to be prohibitively expensive, it is now possible to individually tailor products and content on a huge scale, especially since customer habits are continually changing and there is growing demand for personalisation. We deep dive into:
- How recommendation systems can alter customer retention rates
- How you can utilise existing data to create intelligent recommendation systems
- How new advances in machine learning algorithms have shaped and will continue to shape this space
- Ways in which recommendation systems can be deployed across different areas of business
Using Big Data and Industrial IoT to Improve Life of Assets
A look at how one manufacturer has utilised big data to improve the manufacturing process, increasing yield over time and improving productivity by actively managing the condition of equipment and using analysed data to identify potential faults before they happen.
This case study will look at:
- Product quality and defect tracking
- Measuring output efficiency
- Intelligent maintenance scheduling
Get Your Data in the Supply Chain
Supply Chain Management is an area which can benefit hugely from big data schemes, but also suffers from being unwieldy and incredibly complex. It covers a diverse geography, is in constant flux, and any errors can cause backlogs and impact profit.
This session will discuss how big data innovations can be introduced to:
- Mitigate supply chain risks
- Implement early warning mechanisms
- Build resilience into supply chain management
- Improve forecasting accuracy
- Minimise the impact of disruptive events
Questions to the Panel of Speakers
Refreshment Break Served in the Exhibition Area
Using Predictive Analytics to Answer Tough Business Questions
Predictive capabilities can lead to better financial results and greater competitive advantage.
- How can key areas of your business benefit from predictive analytics?
- What impact can predictive analytics have on product profitability, revenue analysis, customer sentiment analysis, demand chain optimisation, and sales performance monitoring?
- What data hygiene and governance mechanisms do you need in place before you can unlock the full potential of predictive analyses?
Monitoring Marketing Insights to improve Campaign Performance
By monitoring multiple media channels and collating the information from them, companies can use the insights gathered to dramatically improve marketing performance.
- How to build a big data platform to accommodate diverse media channels
- How insights can be used to improve tactical decision making
- Using marketing analytics to create operational efficiencies and improve the customer journeys
- Creating new adaptive approaches to marketing and sales campaigns that increase ROI
Questions to the Panel of Speakers and Delegates move to the Seminar Rooms
Networking Lunch Served in the Exhibition Area
Conference Chair’s Afternoon Address
SESSION TWO – HARNESSING THE POTENTIAL OF DATA COLLECTION AND ANALYSIS
- Ensuring Data Quality remains high
- Overcoming the Challenges of Unstructured Data
- Creating Scalable and Adaptive Database Architectures
- Creating Clear and Insightful Data Visualisation
Why Data Quality Matters
When used well, an analytics programme can have a transformative effect on an enterprise’s decision-making process. But if your business decisions are founded on poor quality data, then not only does it mean you are making decisions without objective value, you are also possibly steering your organisation in the wrong direction. We walk you through:
- How you can improve your data hygiene at every stage of the data journey
- How to identify data quality issues – from user errors to processing inaccuracy
- How you need to introduce data quality awareness into every level of your collection and analytics programme
Big Data Infrastructure in the Cloud
As the demands on data increase and analytics teams are expected to reduce the time taken for data insights to reach decision makers, issues around database performance will pose serious challenges to agile data-driven decision-making.
Cloud infrastructure lends itself well to these challenges, offering flexible resourcing, accessibility, and usability that can drastically improve the time taken to process large datasets.
We look at how big data workloads can be moved to the cloud, the challenges you will have to overcome, and how to best optimise your cloud infrastructure for your data assets.
Seeing the Big Picture: Key Elements of Good Data Visualisation
The proliferation of mobile and strong consumer demand has driven many organisations to adopt an on-demand delivery model. This new reality manifests itself in a boundary-less enterprise environment.
This session looks at how enterprises can:
- Extend their IAM infrastructure to mobile deployments
- Implement mobile authentication, end to end security for device, apps, users
- Monitor behavioural anomalies, preventing hacker and malware activity
- Ensure their mobile deployment is secure through encryption and other techniques
- Prevent data loss, enforcing security policies and compliance
- Strengthen device and app security
Peering into the Abyss: Finding Sense in Unstructured Data
Around 80% of all data is unstructured. And it’s everywhere – in logs, lists, audio, emails, social media posts, memos and more. As the usage of data lakes increases, the mammoth task of organising, collating and eventually extracting insights only grows.
We discuss implementation strategies and structures that can help you to bring some order to the chaos unstructured data presents. The value of this data is still there, it just needs extracting.
Questions to the Panel of Speakers
Afternoon Networking and Refreshments served in the Exhibition Area
SESSION THREE – THE PEOPLE BEHIND THE DATA
- Facing the operational and administrative challenges of a data and insights programme
- Regulatory Compliance and Big Data
- Creating a Data-Driven Culture in Your Enterprise
Overcoming Big Data’s Decision Paralysis Problem
Provided with a huge amount of information from a huge number of sources, it’s easy to be overwhelmed by the diversity of possible interpretations of large datasets and freeze. It’s equally as tempting to get lost in the analytics process while you try to find the perfect interpretation or story from the data. The result though is the same: slow decision-making or complete paralysis.
This presentation will look at how you can overcome the decision paralysis problem by:
- Identifying key metrics and insights in collected data
- Identifying and benchmarking your aims and business needs
- Focusing on data quality, not quantity, for enhanced decision capabilities
GDPR Compliance and Big Data: An Opportunity not a Curse
With the European General Data Protection Regulation coming into force in May 2018, it can be tempting to see the consumer-friendly regulation as antagonistic towards the concept of data collection. Or worse, privacy regulations and big data analytics as being diametrically opposed.
But is this really the case? The standards applied to data collection around ownership, quality, privacy and ethics will not only improve the way we treat consumer data, but in the long term be hugely beneficial to the insights we can collect as trust between industry and consumers grows.
Cultivating a Data First Culture: Why Information Can be an Asset at Every Level
The IT world is slowly becoming aware that successful digital transformation across business and society does not trickle down from the top, but is instead user-driven. Users have to be educated, empowered, and trusted. Businesses therefore have a stake in cultivating a data-first culture that democratises the use of big data and fully harnesses its potential. We explore:
- Improving data literacy across your organisation
- Building communication channels so potential innovations aren’t siloed
- Introducing data analytics at the ground level, potential opportunities and pitfalls
Questions to the Panel of Speakers
Closing Remarks from the Conference Chair
Whitehall Media reserve the right to change the programme without prior notice.