BIG DATA, 3 Key Elements !

Data governance

No artificial intelligence without data! I will say even more, no good I.A. without the necessary amount of data. Then there arises the problem of their integrity . The solution to this equation inevitably passes by processes, frames, standards ... in short, regulations.

Therefore, the first element to consider in the near future of Big Data is data governance. As a result, it is easy to imagine that the EU's GDPR (General Data Protection Regulation) will continue to gain prominence, as will related security-related themes or data catalogs.

" As IoT projects move away from cloud-centric approaches...

Finally, one can wonder what risks we are facing with the implementation of the 5G. This is the fifth generation of wireless telecommunications technology. In fact, it's about sending and receiving very high volumes of data (up to ten gigabits per second). This power will be used to support Big Data or IoT (Internet of Things) and will offer ever greater performance to users. On the other hand, one can wonder about computer control vis-à-vis the volume of data to be stored, managed and secured.

Big Data

Open Source

The incredible growth recorded by open source programs is the real proof that this is the future of Big Data. Companies powered by open source solutions include Amazon, Facebook and even IBM.

If we believe the experts, "the market will double with open source technologies." Let's mention the Cloudera / Hortonworks merger as one of the many mergers / acquisitions that support this vision.

Companies that are making real progress in the data world are also the ones pushing open source solutions the most. This not only proves their effectiveness, but also indicates the direction of financial choices.

" the market will double with open source technologies."

Dremio co-founder and CEO Tomer Shiran said: "By using open source projects, open standards and cloud-based services, companies will soon be delivering their first data-as-a-service iterations to consumers of data in the cloud. critical business sectors ".

The past, present and future of Big Data are strongly rooted in open source technology and it is its greatest strength in the long run. It also means businesses and individuals will have easy access to efficient, up-to-date solutions without fear of paying a premium.


However, according to Karthik Ramasamy, founder of Streamlio (Apache Pulsar, Heron and Bookkeeper), "the tensions will be exacerbated as the major providers of cloud computing platforms will turn to the open source ecosystem Large cloud providers will undermine communities and open source providers by launching their own open source cloud-based services without contributing to these communities. " Beware, "the extent to which these companies act as 'good citizens' in open source deserves to be monitored."


Edge Computing

What is Edge Computing? We are mainly referring here to computing capabilities, especially around the Internet of Things (IoT) and AI, far from the cloud, in the field, where the sensors are. This technological innovation aims to reduce the latency between data collection in the cloud, their analysis and the measures to be taken.


Sastry Malladi, FogHorn's Technical Director: "As IoT projects move away from cloud-centric approaches, the next step in the evolution of artificial intelligence and IoT will be to convert algorithms to work on the periphery in a considerably reduced space. "


According to Stephan Ewen, co-founder and technical director of Data Artisans, it is "an excellent complement both for pretreatment of data on devices or gateways, and for the execution of a logic event in edge mode" .


Edge computing delivers better performance than cloud computing because it uses less inbound and outbound network data for lower costs. Businesses can also reduce storage and infrastructure costs if they choose to delete collected but unnecessary data.