Building the Data Driven Smart Enterprise

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by Mike Ferguson, Barry Devlin, Jos van Dongen, Daragh O' Brien, Hans Hultgren, Donald Farmer download a PDF brochure Download Event Brochure


As companies invest in digitalization the number of operational applications and processes being made available through the Web, Mobile and Social computing channels continues to grow. In many cases, digitalization has resulted in new structured, semi-structured and unstructured data being captured in addition to increasing amounts of transaction data. This includes JSON data, sensor data, text and machine data like Web logs recording every click of a mouse or touch of a mobile device screen.

Naturally, when new data is available, business wants to analyze it and so new ‘workload optimized’ analytical systems have emerged in companies wanting to move beyond traditional Data Warehouses. Big Data and Streaming Analytics platforms have been added to Data Warehouses to create an extended analytical ecosystem. It is not surprising therefore that with all this data that predictive and advanced Analytics have risen up the priority list as executives realize the strategic importance of evidence based insights to future business success. Almost everywhere companies are now using or planning to use Analytics to gain a much better understanding of customer behavior and interactions, to reduce risk and to optimize operations. In addition, with so much data and analytical opportunity around, business is demanding insights be produced quickly for competitive gain.

They want to modernize Data Warehouses by introducing agile data modelling techniques that easily accommodate change. They want to reduce total cost of ownership by replacing physical data marts with virtual data marts all accessible from self-service BI tools so they can create insights themselves. They also want to use new modern visualization techniques like infographics for more effective communication.

Furthermore, business is demanding that we move beyond basic interactive dashboards on historical transaction data to making use of predictive and advanced Analytics on traditional and Big Data to deliver high value insights.

This content rich conference addresses all these needs by focusing on Data Warehouse modernization, governing self-service BI and introducing Analytics. It looks at introducing an agility data strategy into traditional Data Warehouses by adopting agile Data Vault modeling, data virtualization and Data Warehouse automation. It also looks at new data visualization techniques and machine learning including developing predictive Analytics.

It discusses advanced Analytics such as text and graph analysis, and how these can be used to drive up sales in digital and traditional channels. Just how powerful is graph analysis and what would you use it for? Also what happens if you combine advanced Analytics such as machine learning and text analysis or text analysis and graph analysis? How can text analysis of social media data help improve e-commerce sales? We also introduce Fast Data - also known as Streaming Data and discuss you need to do to get ready for it? We will look at how your architecture needs to change, how to ingest high velocity data at scale and what’s involved in introducing a Streaming Analytics platform?

We will also look at how self-service BI tools integrate with all this and how to integrate it with your traditional Data Warehouses.

Finally we look at the impact of the EU General Data Protection Regulation (GDPR) and what it means in terms of governing data in the modern analytical environment. We will answer key questions like what do we have to do to be compliant with GDPR and how do we get started in implementing data security and data privacy?

This Conference aims to provide an update on all this, how it fits together and how you can use it to maximize business value. It tries to show the latest advances in technology to help improve your understanding of when to use what where and for what business purpose. It tries to help get more out of Analytics while introducing governance, flexibility, agility and your existing analytical environment.

Main Topics

  • All The Way From BI to AI
  • Data Vault Modeling for the Agile Data Warehouse
  • Data Warehouse Automation - Time to stop Hand-Crafting Your Information Environment
  • Migrating to Virtual Data Marts and Logical Data Warehouse Using Data Virtualization
  • Machine Learning for Business
  • Using text and graph Analytics to create Business Value
  • Getting ready for Fast Data - Introducing Streaming Analytics into the Enterprise
  • The Power (and Pitfalls) of Modern Data Visualization - New Techniques for Effective Communication
  • Governance in the Age of Self-Service Analytics
  • Getting ready for GDPR - Implementing Data Privacy in a Modern Analytical Ecosystem