Jump Start Your Big Data Project
If you need a fast, effective launch for big data and machine learning projects, our pre-installed and pre-configured solutions will save both time and effort. Depending on your expertise and requirements, you can simply inject your data into the clusters we have designed for the most demanding requirements, or re-purpose and extend them to fit your specific needs.
Since 2003, Irontec has delivered the assurance that your infrastructures and applications are in good hands. The most award-winning OVHcloud partner in recent years. OpenAwards to the best European provider of open technological solutions.
Grupo Trevenque helps companies to use technology to improve their processes and business models. With more than 25 years of experience, we bring software and cloud solutions to our customers.
In a constantly changing and increasingly connected world, Thales stands by those with great ambitions: to put digital technology at the service of a better and more secure world. To ensure that we can benefit from new technologies with confidence, Thales supports and secures the transformation of information systems and the most critical solutions and protects the entire data lifecycle, from its creation to its exploitation.
Different levels of support for your organisation
What are the typical challenges around big data?
Big data and machine learning projects are rising in popularity, year by year. As it’s clear that big data in business is here to stay, it’s important to understand the challenges involved, before investing time and money in any projects, whether they’re large-scale deployments, or machine learning projects for beginners. This will help avoid any costly mistakes, and also ensure you have plenty of scope to scale up or down in the future.
The first challenge organisations typically face is the sheer volume of data involved. A typical data lake will involve many terabytes of unstructured data from multiple sources. Not only does this present a huge challenge in terms of the required storage capacity, this raw data will need to be processed into a form that can generate the best possible big data business impacts, which requires the use of complex, powerful algorithms.
The second challenge regards hardware, as most existing hardware solutions simply do not possess the raw power that big data demands. This is where grid computing – where multiple resources are interconnected and shared, to support and enhance their respective capabilities – comes in. However, while grid computing can provide the required levels of performance, care must be taken in terms of achieving an efficient deployment, and the best possible price/performance ratio.
Why is securing your large data sets important?
When it comes to big data and business intelligence, robust data security is more important than ever. This isn’t just a question of making your big data projects a success – it’s equally about fulfilling your legal obligations and maintaining customer confidence that their sensitive data is secure (particularly when healthcare or financial data is involved).
This presents a number of distinct challenges when it comes to the storage and availability of large data sets for machine learning projects. Any storage solutions utilised, both virtual and physical, must not only be of sufficient capacity for big data projects, but fulfil all applicable compliance requirements, and have the very highest standard of security. This includes any connections between solutions within datacentres, and connections between external datacentres and your on-premises infrastructure.
Furthermore, with the recent introduction of data protection regulations, such as the GDPR, full reversibility and control over where your data is hosted is also of paramount importance. All of OVHcloud solutions for big data, AI and high-performance grid computing have been designed with this in mind. Whatever solutions you utilise, and however you have interconnected them across any of our datacentres, you will always retain complete control over how your data is hosted and managed.