What is DataOps? Definition and implementation
“DataOps is a collaborative data management practice focused on improving the communication, integration and automation of data flows between data managers and data consumers across an organization. The goal of DataOps is to deliver value faster by creating predictable delivery and change management of data, data models and related artifacts. DataOps uses technology to automate […]
5 Mistakes Preventing Data Lab Projects From Being Implemented
To help you succeed in your Big Data/Artificial Intelligence project, here is our fourth article on the subject. If you have been following us since the beginning, you now know how to set up a Data Lab, sometimes spelled Datalab, you know all about the pitfalls of POC, and understand the importance of putting the […]
What’s Computer Vision?
This week, we are delighted to chat with Augustin Marty, CEO of Deepomatic. It is a software editor specializing in computer vision. How does computer vision support us in our daily tasks? Find out more here! Tell us the story of Deepomatic Deepomatic is a company that grew out of a company called Smile, which […]
Experts give their visions on the future of data factory
Two weeks ago, we had the chance to organize a webinar about the Future of Data Factory with Arnold Haine, CTO at BVA Group, and Barthélémy Longueville, Data expert in the industrial sector, Founder at Tolmay. If you weren’t able to attend, here is what you need to remember! Some introductive figures First of all, […]
What is overfitting and how to solve it in machine learning?
This article explains the phenomenon of overfitting in data science. It is one of the most recurrent problems in machine learning. We give you some clues to detect it, to overcome it, and to make your predictions with precision. A definition of overfitting You have probably already experienced, in the age of big data and […]
What are the keys to launch your data project?
Is it possible to deploy a data project, from scoping to large-scale deployment, in 10 weeks? Let’s take a closer look at the keys to accelerating this type of project, which can sometimes take up to 18 months to generate value. Before starting anything, it is essential to know fairly quickly whether there is a […]
Which technologies for your data projects?
You can easily get lost in the data technology ecosystem. The technological offer in data management being very (too?!) rich, many solutions are available to you according to your needs, data sources, industries, infrastructures, skills, technological situation? This is why we present you with a review and advice on how to choose your analysis tools. […]
5 Best Practices to Adopt for A Data Science Project
Once you decide to develop Data Science projects, you will break new ground, and you will need to get it right from the start. Of course, there are many technological challenges on this path, but you will also find out about cultural issues that will make collaboration hard. Today, we will share some best practices of […]
DataOps: Devops Applied to Data Projects
Only half of all AI projects have been deployed today. Why? Because it often takes longer than it looks – between 12 and 18 months. That is what comes out of the many studies of Gartner, Capgemini or BCG: the need to industrialize. A new emerging concept called DataOps was born from the complexity to […]
Put Open Source in your Data Projects
It has become impossible to talk about Data without mentioning open source. Just take a look at the different platforms that offer Big Data solutions, the vast majority of which are open source oriented. For good reason, technologies such as Cassandra, Hadoop, Apache Spark, Talend and many others now offer high quality services for building […]
How to Bring DevOps Practices into Your Data Science Project ?
Still struggling to make your Big Data / AI project happen? Here is our last piece of advice on the matter, but don’t hesitate to check out our previous articles about the Data Lab and its organisation, the business vision, the POC, the traps and the Data Fabric. Now, let’s find out about the DevOps […]
A Data Fabric to make your Big Data & AI projects happen!
Even though the terms Big Data, Data Science and Artificial Intelligence gain in popularity, few data initiatives do in fact materialize. Various use cases are addressed but struggle to get industrialized. The Data Fabric concept seems a promising solution to get data projects in production. Data Fabrics emerged recently in the specialized press (Forbes, Networkworld…) each with different definitions. In this […]
