Data Warehouse Modernisation

– From Passive Data Warehouse to Live Analytical Ecosystem

 

5-6 May, 2020 – Stockholm

21-22 May, 2020 – Amsterdam

9-10 June, 2020 – London

 

OVERVIEW

In today’s digital economy, the customer is all powerful. They can switch loyalty in a single click while on the move from a mobile device.  The internet has made loyalty cheap and many CEOs want new data to enrich what they already know about customers in order to keep them loyal and offer them a more personalised service.   In addition, companies are capturing new data using sensors in to gain sight of what’s happening and to optimise business operations.  This new data is causing many companies with traditional data warehouses and data marts to realise that this is not enough for analytics. Other systems are needed and with the pace of change quickening, lower latency data and machine learning is in demand everywhere.  All of it is needed to remain competitive. So how then do you modernise your analytical setup, to improve governance and agility, bring in new data, re-use data assets, modernise your data warehouse to easily accommodate change, lower data latency and integrate with other analytical workloads to provide a new modern data warehouse for the digital enterprise?  This new 2-day seminar looks at why you need to do this. It discusses the tools and techniques needed to capture new data types, establish new data pipelines across cloud and on-premises system and how to produce re-usable data assets, modernise your data warehouse and bring together the data and analytics needed to accelerate time to value.

AUDIENCE

CDOs, CIO’s, IT Managers, CTOs, Business Analysts, data scientists, BI Managers, data warehousing professionals, enterprise architects, data architects

LEARNING OBJECTIVES

After two days attendees will:

  • Understand why data warehouse modernisation is needed to help improve decision making and competitiveness
  • Have the ingredients to know how to modernise your data warehouse to improve agility, reduce cost of ownership, facilitate easy maintenance
  • Understand modern data modelling techniques and how to reduce the number of data stores in a data warehouse without losing information
  • Understand how to exploit cloud computing at lower cost
  • Understand how to reduce data latency
  • Know how to migrate from a waterfall-based data warehouse and data marts to a lean, modern logical data warehouse with virtual data marts that integrates easily with other analytical systems
  • Know how to use data virtualisation to simplify access to a more comprehensive set of insights available on multiple analytical platforms running analytics on different types of data for precise evidence-based decision making
  • Understand the role of a modern data warehouse in a data-driven enterprise

 

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