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Programme

Session One: Big Data’s potential for disruptive innovation

  • Exploring the latest trends in the big data space
  • Impact of data on business models and profitability
  • Disruptive technologies like AI, Machine Learning, IoT and their application to solve business problems
  • Leading large scale data-driven transformation across your enterprise
  • Achieving ROI from your data projects
  • Moving to real-time analysis for better responsiveness and forecasting
  • Security, compliance, privacy and transparent use of data
  • Turning data into new visibility and business intelligence
  • Utilising predictive analytics for impactful action
  • Widening data applications to achieve specific business outcomes – from personalised customer journeys to marketing and more
09.15
Conference Chair’s Opening Address
09.25
Why Data Matters for your Digital Transformation

Data and Digital Transformation enable one another. According to Forbed, “by 2018, 35% of IT resources will be spent to support the creation of new digital revenue streams and by 2020 almost 50% of IT budgets will be tied to digital transformation initiatives.”

We look at how your organisation can:

  • Use data to solve strategic business problems
  • Use advanced analytics, ML and AI to build intelligent business processes
  • Drive digital transformation and monetise data assets while being mindful of information governance post-GDPR

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09.45
Interactive Visualisation Tools: Making Sense of Big Data

Visualisation is a critical component of driving employee engagement. Interactive elements of visualisation have multiple uses and benefits, including better comparative analysis and forecasting which allow businesses to make quicker and more efficient decisions.

We explore:

  • Visualisations ease of usability and quicker identification of solutions to business issues
  • How to find patterns and trends for impactful action
10.00
An NLP Deep Dive within Big Data

Regardless of the sector, every business today relies on large volumes of text information. So what problems can natural language processing for mission critical big data solve in your enterprise?

  • Using natural language processing for sentiment analysis to better understand what is being said about your brand and products
  • Leveraging natural language processing to find relevant information and/or summarise the content of documents in large volumes of information for collective business insight
10.20
Harnessing Machine Learning for Data Cleansing

Businesses often approach data cleansing with a trial and error method. There is a growing need for scalable and principled data cleaning solutions within enterprise, this session explores machine learning as a scalable solution for data cleansing:

  • Scalability by automated data matching, avoiding errors and manipulation in new and existing data sets
  • Automating data matching by using a learning model to predict matches which consequently sees the algorithms work better
  • Taking a holistic approach compiling all available rules and scripts into signals and features to enable clearer process guidance
10.35
Rise of the Chatbots: Combining AI with Big Data to Create a Flawless Journey for your Customer

The significant rise in chatbot implementation for customer inquiry management throughout enterprises have seen vast improvements in time management and cost-effectiveness for businesses, as well as driving customer engagement. This session explores how you can give your business a competitive advantage utilising AI:

  • Implementing the right architecture for chatbots: Avoiding poorly governed bots.
  • Utilising a hybrid approach between customer service representatives and chatbots
  • Unlocking the future potential of AI within customer services
10.50
Questions To The Panel Of Speakers
11.00
Refreshment Break Served in the Exhibition Area
11.35
Using Data for Customer Engagement

We look at some of the most innovative ways in which marketers can utilise big data to optimise productivity and cut overall enterprise costs:

  • Exploring the numerous exciting benefits of using Big Data through various marketing channels i.e marketing strategy optimisation, developing loyalty and brand trust
  • The impact of big data on email and mobile targeted marketing and how push notifications can revolutionise your strategy
  • Deriving actionable business intelligence to drive forward your marketing campaigns and strategies
11.55
Big Data DevOps

Little is said about combining Big Data with DevOps however trends in data are shifting. In this session we look at integrating DevOps with Big Data, the challenges and the benefits:

  • Breaking down siloes between departments to improve collaboration and using resource coordination as key driver for implementation
  • More effective planning of software updates earlier in the cycle to decrease error rates which enables increased efficiency
  • The benefits for both DevOps teams and Data teams are mutually exclusive in particular the case of the DevOps feedback process
12.10
Questions to the Panel of Speakers and Delegates move to the Seminar Rooms
12.15
Seminar Sessions

(To view topics see the seminars page)

13.00
Networking Lunch Served in the Exhibition Area

Session Two: Making Data the Centrepiece of your Business

  • Exploring common pitfalls and how to avoid these
  • Solving Critical Challenges and Fulfilling your Strategic Vision
  • Cultivating a data-driven culture, people, and skills
  • Managing and implementing a secure and scalable Big Data architecture
14.00
Conference Chair’s Afternoon Address
14.05
Implementing a Data-Driven Culture

Data driven decisions take the guesswork out of business tactics. We drill down into the key components of a data driven culture, by exploring how to:

  • How to assess your current data culture to identify your businesses urgent goals
  • Set data priorities – mapping out steps to lead to complete data absorption
  • Segment data – identify key streams of data and which sources provide the most valuable information
  • Streamline your data and avoid inaccurate reporting by applying a cross analysis data system which will also reduce costs in your data storage
  • Trust your data – depersonalise decision making and introducing A/B Testing to measure and determine success metrics.
14.20
Sharing Big Data in the Cloud

A well implemented cloud solution can have ample benefits to any business; it can also drive innovation on an unprecedented level and makes an agile working culture more possible than ever before. This presentation explores how Cloud has advanced big data analytics, and how to:

  • Create a cost effective elastic cloud environment which will give better ROI on Big Data technologies
  • Reduce workplace limitations
  • Improve data governance – the best way to protect your Big Data
14.35
Improving Data Science Ethics

Exploring best practices and ethical approaches for data collection and eliminating data bias. How can large enterprise harness and utilise the recent government framework on data ethics to create an ethical strategy of their own?

  • Evaluating the seven data ethics principles
  • Creating a data framework and agreeing standardised practice this can then be then used as a testing tool for evaluating existing work against the framework
  • Creation of workbooks to give employees a practical way to apply the framework
14.50
Improving Employee Performance with Big Data

This session explores how business leaders can develop a solid corporate training strategy by utilising data analytics. Learn how to:

  • Measure and track employee metrics
15.05
Questions to the Panel of Speakers
15.15
Afternoon Networking and Refreshments served in the Exhibition Area
15.45
The Impact of Big Data on Datacentre Infrastructure

The masses of data are driving development of storage hardware and networks in DC’s, ultimately creating continuous innovation in areas such as capacity and security. We look at:

  • How to scale out without affecting performance: Analysing the flash based storage system for optimal real time performance
  • Techniques to create cost effective storage: E.g Data redundancy and data de-duplication
16.00
Securing your Big Data with Machine Learning

Security for data tends to be an afterthought in many enterprises, they often struggle to implement the appropriate processes. We look at the innovative role of Machine Learning and its practical application to data cybersecurity.

16.15
Closing Key Note: What’s Next for Big Data?

What does the future have in store for the data-centric enterprise? We examine the forward momentum of big data in the coming months and years.

16.30
Questions to the Panel of Speakers
16.40
Closing Remarks from the Conference Chair
16:45
Conference Closes

Please note:
Whitehall Media reserve the right to change the programme without prior notice.