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- Next-gen data science: building the workforce you need now and in the future
- Applied big data and AI in times of disruption
- Beyond the numbers: how to be a better data analyst
- Data storytelling: how to get people’s attention
- Analysing and modelling data in a complex world
- Tomorrow never knows: the crystal ball of predictive analytics
- Climbing the AI ladder: accelerate your journey
Conference Chair's Opening Address
Next-gen data science: building the workforce you need now and in the future
As demand for data experts looks set to continue at an exponential rate, with 2020 having registered a 28 percent increase in enterprise demand for scientists, engineers, architects, and analysts, businesses are finding that supply is not matching demand.
We address, the data science and analytics landscape, measure the skills gap, and explore ways in which the talent shortage can be addressed.
Applied big data and AI in times of disruption
In today’s highly disruptive environment, the successful application of big data and AI offers enterprises, no matter their industry sector, with the potential to diversify their product offering, realise new business opportunities, survive downturns, and hold onto their customers.
We explore, how businesses which adapt to customer needs through the systematic exploitation of big data and AI, integrated with analytics, reveals previously unimagined possibilities for data-driven initiatives which support revenue generation.
Beyond the numbers: how to be a better data analyst
When doing data analysis, investing time with people and the process of analysing data, as well as its resources, will allow you to better understand the data you have been tasked to make sense of. By doing so you will significantly improve the data analysis process as well as the results from that analysis.
Exploring your mindset and getting to a place of true neutrality and purpose while working can help clear the mind to do a more thorough and complete study.
Join us as we explore how to see the picture, both big and small; understand the bias and the purpose of the data you are tasked with turning into a story.
Data storytelling: how to get people’s attention
Understanding what our experiences are and being able to quantify them and tell the stories of our lives is something that we can all relate to. The same can be said of the value that businesses gain from taking raw data and turning into, not just actionable information, but a story which is of business-wide relevance.
We address how best to tell a story with data.
- Focus on one idea
- Keep it simple
- Explore the things you know best
- Turn bad charts into compelling data stories
- Understand the story you want to tell
Analysing and modelling data in a complex world
The amount of data available will continue to increase at an incredible rate. Of equal relevance is the fact that the average human spends 11 hours processing information on a daily basis. This has led many to question how we are going to manage the processing, storing, and accessing of such vast amounts of information.
We address, how to better simulate, store, access, and link your data sets in order to realise your organisations data strategy.
Questions to the Panel of Speakers
Refreshment Break Served in the Exhibition Area
Tomorrow never knows: the crystal ball of predictive analytics
A lot of business processes are done a certain way because, quite simply, that’s the manner in which they evolved from inception to the present. Such an approach leads to the space for innovation to narrow as organisations hold onto long held practices and fail to adapt to changing circumstances.
Better engagement with business and end users through the successful application of predictive analytics means that you are able to capture historical and current information to future proof against a variety of factors which were previously unimagined.
- Analyse, simulate, plan, and predict
- Bring digital transformation into your company’s processes
- From strategic and operative planning to data analysis
- Accelerate the efforts of your scientists, analysts, and developers
Climbing the AI ladder: accelerate your journey
Data is the modern-day obsession for business, government, and society alike. Without it, businesses do not progress, governments fail to improve services and society remains locked in a state of ignorance.
For data-led enterprise initiatives, the issue isn’t necessarily volume but the organisational capacity to successfully adopt the systems and structures needed to turn data into value.
AI unlocks the value of data and hybrid multi cloud is the platform to democratise the data.
- Make your data ready for an AI and multi-cloud world
- Engage in high-value work without limits
- Establish workflows that automate decisions and experiences
- Turn aspirations into outcomes
Questions to the Panel of Speakers and Delegates move to the Seminar Rooms
Networking Lunch Served in the Exhibition Area
Online Session Two
- Leveraging open source data and AI platforms
- Perpetually learning machines: keeping humans in the loop
- Building trust in big data and AI
- Real time decisions require a modern architecture
- GPU accelerated data analytics: unlock value and context from your data
- Where will your data live?
Conference Chair’s Afternoon Address
Leveraging open source data and AI platforms
In today’s enterprise environment there exists an exponential demand for insights and data-driven answers from clients which is driving demand beyond traditional business-consumer frameworks.
We address, the value of standardising open, cloud-based platforms to increase the speed and scale of operations; the democratisation of ML across the business, how this can drive transformation, deliver new products, improve time to market, drive growth and improve operational efficiency.
Perpetually learning machines: keeping humans in the loop
Intelligent systems are being permanently baked into every facet of business life. From smart, connected systems working hand in hand with powerful cloud AI systems which are able to aggregate input from devices in the real world, to an environment in which computing will finally become truly democratised as human capabilities are augmented by tailor-made AI solutions and tools.
Despite such progress, many organisations are in search of new ways to plug the comprehension gap in AI and enterprise data.
We address, how HILT in ML can advance the accuracy of datasets, improve safety and precision, avoid bias, augment rare data, and maintain expert level input.
Building trust in big data and AI
Many consumers struggle to trust AI. Naturally, they prefer genuine, human-led interactions.
By combining AI with human ethics, businesses can improve consumer relations, produce better engagement, retain their customer base, and secure revenue streams.
- Real-time, omni-channel AI capabilities
- Control your own AI for impact and empathy
- Switch between opaque and transparent AI
- Deploy the tools to build and enable empathetic actions
- Understand and decide the best decision for the customer
- Ethical considerations integrated with your ML
Questions to the Panel of Speakers
Afternoon Networking and Refreshments served in the Exhibition Area
Real time decisions require a modern architecture
Given that business success relies upon the ability to anticipate market changes, adapt operations at speed and implement alternate routes for product offerings and customer services, it is vital that enterprise architectures mature in line with changing business needs.
In response to increasing degree of disruption, businesses need a clear way to transform how they source, interpret, and consume information.
- Consolidate siloed data sources
- Migrate legacy systems onto the cloud
- Deliver analytics and intelligence that informs everything
- Increase speed of access
- Enable dynamic forecasting
- Turn chaos into a catalyst
- Base your actions on insightful, actionable intelligence
GPU accelerated data analytics: unlock value and context from your data
Identifying value in large datasets is vital, but many of today’s CPU systems are struggling to keep pace with the intensity of current data demands. This leaves your data science function without the cutting edge necessary to unlock the value of enterprise data.
By deploying the next-generation GPU platform which is built to support the ambitious data-led plans of businesses who need to harness their rapidly growing datasets, data and analytics practitioners will uncover valuable intelligence in milliseconds, process massive amounts of data, customise and adapt resources at scale, and integrate into existing systems with ease.
Where will your data live?
The average business has 5 different cloud providers, which has led to a complex IT environment. With such unpredictable costs, inconsistent security features, and multiple management tools, instead of sourcing, organising, and achieving value from your data, organisations are left fighting unnecessary battles.
With a multi-cloud platform, you can bring consistent infrastructure and operations, you can choose the right cloud for each application.
- Agile with increased workload migration
- Easy onboarding for new assets
- Get your teams to market faster
- Simplified operations and automated processes
- Reduce risk and strengthen security
- Flexible consumption costs
Questions to the Panel of Speakers
Closing Remarks from the Conference Chair
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