BDA EUROPE

Big Data Analytics

12 March 2019

Postillion Convention Centre WTC Rotterdam

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SEMINARS

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.

SESSIONS

SEMINAR 1
How real-time data can help you stay ahead of the curve

Businesses are collecting data at an exponential rate. Real-time data offers businesses the chance to move from being reactive and static to being automated continuous learning environments. Through a practical demo on real-time data, we explore how you can:

  • Significantly improve Customer Experience (CX)
  • Increase efficiencies and cut overhead costs
  • Mitigate risks and detect fraud
SEMINAR 2
Understanding Internet of Things Data

What is the value of data generated by the IoT? And what do you need to do to realise that value? Businesses are increasingly collecting data from physical sources, especially sensors on equipment, smart meters, delivery trucks, and other machinery. As the depth and complexity of this data continues to grow, the ability to analyse data from ‘things’ in real-time is becoming a necessity for businesses that want to reduce maintenance costs, avoid equipment failure, and improve business outcomes. Join this session as we explore the advantages of streaming analytics and how they can be used to build on the value of IoT data.

SEMINAR 3
Data Lake Best Practice

In this session we look at the key ways you can maintain the order and utility of your data lake by:

  • Improving data profiling and metadata
  • Improving your data quality
  • Ensuring data retention and lifecycle management best practices
SEMINAR 4
How Machine Learning can capture the full of value of your data

Most basic analytical methods in BI reduce reporting to sums, simple averages and running SQL queries. We look at how machine learning is ideal for exploiting opportunities in your disparate data sources, and how it can yield higher quality insights.

SEMINAR 5
Tools to Build Data Science Collaboration

Encouraging collaboration across individuals and data science teams is a fantastic way to improve outcomes and bring new approaches to long-standing issues and accepted wisdom. Join this seminar for a look at the latest tools that allow data scientists to share work environments and collaborate on different datasets.

SEMINAR 6
Going Deep on Your Data

Data is everywhere in the modern information economy. But it’s what you see in your data that makes the difference. We typically hear a lot about how big data can deliver usable insights but what does this mean exactly? How can companies turn big data into decision-making power on customers, security and much more?

This seminar explores how advanced analytics are being utilised across industries for business success. We explore how you can reduce time to value, why business and IT collaboration is necessary, how data visualisation and big data technologies are coming together with agile development methods to empower users to be productive with data sooner.

SEMINAR 7
Data Science in the Cloud

This seminar will explore:

  • Challenges and Solutions for Big Data in the Cloud
  • Unlocking the potential of big data in cloud environments
  • Solving problems and delivering value with cloud-based analytics
SEMINAR 8
Maximising the Potential of Real-time Visualisations

We explore the benefits of using real-time visualisation to identify areas that require your attention, uncover trends, and communicate a compelling story both in the business and in the marketplace.

SEMINAR 9
Why Data Quality Matters

Taking the time to map out what data quality means to your organisation can have ripple-effects for improved growth, better outcomes and ultimately better customer experiences and retention. In this seminar, we walk you through how to create a data quality checklist, assessment and cleansing methods, and the characteristics of good quality data.

SEMINAR 10
Data Security and Data Science

This seminar looks at how data security and a rigorous ownership model can be deployed in data rich business environments to protect data sources without inhibiting innovation. We look at a unique platform for security data science that offers a deep and personalised security response and advanced detection.