Online Events

Due to time zones, events presented by American speakers will be spread over more days, and will take place in the afternoon from 2 pm to 6 pm Italian time

Data Quality: A “must” for the Business Success

ONLINE LIVE STREAMING

Apr 08 - Apr 09, 2024

By: Nigel Turner

Designing, developing and deploying a Microservices Architecture

ONLINE LIVE STREAMING

Apr 12, 2024

By: Sander Hoogendoorn

Practical Guidelines for Implementing a Data Mesh

ONLINE LIVE STREAMING

Apr 15 - Apr 16, 2024

By: Mike Ferguson

Embedded Analytics, Intelligent Apps & AI Automation

ONLINE LIVE STREAMING

Apr 17, 2024

By: Mike Ferguson

Artificial Intelligence, Machine Learning and Data Management

ONLINE LIVE STREAMING

Apr 18 - Apr 19, 2024

By: Derek Strauss

Business Architecture Best Practices

ONLINE LIVE STREAMING

May 06 - May 09, 2024

By: Roger Burlton

Introduction to Generative AI for Java Developers

ONLINE LIVE STREAMING

May 13 - May 14, 2024

By: Frank Greco

Chatbot and LLM Bootcamp

ONLINE LIVE STREAMING

May 15 - May 16, 2024

By: Ivan Reznikov

Building a Competitive Data Strategy for a Data-Driven Enterprise

ONLINE LIVE STREAMING

May 17, 2024

By: Mike Ferguson

Free article of the month

Febbraio 2024

Upcoming events by this speaker:

April 8-9, 2024 Online live streaming:
Data Quality: A “must” for the Business Success

June 10-11, 2024 Online live streaming:
Data Governance: A practical Guide

Data quality and artificial intelligence The alliance for business success

Artificial Intelligence (AI) & Machine Learning (ML) have become the focus of global news headlines over the past months.  Pessimists fear that the growth of AI/ ML poses a serious threat to the future of humanity, invoking Terminator style doomsday scenarios. Optimists claim AI/ML can be the saviour of humankind, a vital tool in helping us identify and avoid impending future problems and disasters, often before we are aware of them. 

The reality is, as always, somewhere between the two.  Like any new set of technologies AI/ML has the potential to benefit us all if applied ethically and intelligently.  A growing library of use cases is already beginning to appear which show how AI/ML can identify and help to create new opportunities and resolve problems in areas such as government, retail, banking, insurance, manufacturing, travel etc.  But if used wrongly or for morally questionable purposes such as the dissemination of political misinformation AI/ML could cause intended or unintended harm.  So what can we do as data management specialists to play our part to ensure that AI/ML is a force for good, and not a force for evil?

One key way is to recognise and promote the fact that AI/ML, like any set of technologies that relies on data is only as good as the data it is given to work with.  However carefully the algorithms that drive AI/ML are constructed and applied, they will invariably produce false outcomes if the source data is not a true reflection of the reality that data is supposed to represent.  Put simply, AI/ML critically relies on good data quality.  Feeding AI/ML with inaccurate and incomplete data inevitably results in it generating outcomes, decisions and actions that are inaccurate, unreliable, misleading and potentially downright dangerous.

Continued to read…

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