Datapunk does not exist (yet)

It may be a disappointment, but datapunk is not a reality and our April 1st article was just a set of answers from GPT Chat (under the pseudonym Guy-Philippe Turbot) to a few well-directed questions.

This experiment, which we hope made you smile, demonstrates two points.

The first one is that one should be wary of the ability of conversational artificial intelligences to produce completely fictitious, but very credible content. Chat GPT answers efficiently to the questions asked, without really being able to include a precise definition of datapunk (and for good reason!), but by chaining relevant generalities around the concepts of data exploitation: data visualization, confidentiality, ethics... a few more or less sourced studies that underline the growing importance of data processing, in general.

The second is that, even if all this lacks a little coherence, the subject of data exploitation has generated enough articles on which GPT chat has been trained for this conversational artificial intelligence to be able to produce an article rich in relevant thoughts.

The valorization of data is nevertheless topical

The valorization of data is indeed currently particularly worthy of interest.

On the one hand, the amount of data generated by our digital ecosystems has become colossal and must be organized from a structuring point of view between :

Transactional databases, which are manipulated by the applications we use on a daily basis and are the main source of data creation.

Data Lakes, which allow the archiving, in a generally less structured form, of data from transactional databases, when they are no longer relevant.

Data Warehouses, which house the data from the two previous types of storage, after it has been refined for use in analysis, the creation of dynamic reports and decision support.

On the other hand, this data contains real value that is just waiting to be exploited, by automating reactions to transactional data. These automations can be based on the predictive recommendations of machine learning engines trained on the data from the data lakes or on algorithms whose rules have been decided on the basis of the analyses enabled by the data warehouses.

This is precisely the type of mission that the teams at Synotis, the Smile group's data specialists, are carrying out.

Data at the heart of Digital Experience Platforms

A concrete example of the use of this type of data-driven device is the deployment of Digital Experience Platforms. These platforms consist of:

A digital content management or ecommerce element, which we will call CMS (Content Management System), which will be the interface of your users (visitors, users or customers) with your digital ecosystem.

A customer knowledge aggregation engine, which we will call CDP (Customer Data Platform), which will aggregate data from the CMS and from your internal IT system, or from third-party sources, to define user segments.

And activators, which can launch marketing actions (we talk about Marketing Automation tools) or trigger personalization within the CMS, based, in real time, on the segments, defined in the CDP, for each user.

This type of digital marketing suite is exactly what our publishing partners, whether Acquia (using Drupal for the CMS part), Adobe, Ibexa or even Liferay, offer through software whose integration is our core business.

Of course, since this example deals with the handling of customer data, it must be deployed in compliance with the legislative and regulatory framework that imposes an ethical approach to personal data.

The final word?

Even if we would have loved to implement datapunk devices for you (this name having been chosen for our April fool's joke, only for its phonetic proximity with the artistic genres, cyberpunk, steampunk or solarpunk) you will have to be satisfied with our expertise in terms of strategic data consulting, DXP deployment or RGPD compliance. Let's face it, it's a good start!