Human and Machine Learning

March 17, 2019

Business Inteligence Event

Read in 2 minutes

I had the opportunity to attend the 2019 Gartner Data & Analytics Summit at London. Here is a wrap up of some notes I took during the sessions.

Few years ago, AI was a subject of fear for the future. Now it’s a fact, Machine Learning is part of the present. We are not anymore in a challenge Humans vs Machines, goal is to free human resources for higher end tasks. Humans and Machines…

You still have a problem with terms like Artificial Intelligence, Machine Learning? No worries, just replace them with “Augmented“.
Augmented Analytics, Augmented Data Management, Augmented Data Integration…

2019 will be Augmented. Not Human versus Machine but Human and Machine Learning at the service of a better Data World.

The new tools will let you operate as you used too but, in the background, will run Machine Learning algorithm to suggest you new vizualisations, unexpected facts, correlations, to save you from repetitive task…

  • All your integration flows have a common pattern, your augmented tool will detect it and propose you to create a new template automatically.
  • You select a set of analytics, your augmented tool will propose a cool vizualisation.
  • You want to prepare a dataset, your augmented analytics will automatically suggest formatting corrections, data mapping and learn from your choices.

If you plan to buy a new tool this year, be sure this is part of the roadmap.

Any other trends for 2019?
Many other trends were presented by Gartner, here are a couple of recurring ones during the sessions :

  • NLP. Natural Language Processing, new tools should be able to accept natural language as input (which allow vocal input from Alexa, Cortona…).
  • DataOps. No-one will deny Data is a subject where requirements evolve quickly. This is thus a choice area to apply agile development methods. DataOps is a specialized version of DevOps practices. This fits perfectly in an augmented world where most repetitive tasks should be automated.

On a non-technical side :

  • Data Literacy. Being a good technician is not enough if you work in the data world. You need to understand data, how they are and can be presented. Your ability to communicate around the data is as important as your ability to manage them. This is what include the data literacy skills. Some training exists on the web, a must for any consultant.

And many more you can find on Gartner web site or at future events.

Enjoy 2019 with machines.13 Rue de la Libération, 5969 Itzig, Luxembourg


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