Cloudera partner in Paris, France

Deploy real-time Big Data analytics on public-private clouds with a privacy-first architecture.

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Discover Cloudera with Adaltas

With the objective to promote Cloudera in your company, we offer 2 days of consulting to our new customers.

Contact us for a detailed presentation of the Cloudera platform and its potential impact in the context of your projects.

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Combine public and private clouds

Cloudera is leading the Hybrid Data Cloud battle in the IT department and building new, easy-to-use cloud solutions.

Public Cloud

Public Cloud

  • Support for the major Cloud provider, AWS, Azure, and GCP.
  • Cloud infrastructure agnostic and easily portable applications.
  • One platform to serve all data lifecycle use cases with a unified security and governance model
Discover past work and don't recreate the wheel

Build a unified Analytics practice.

  • For data science, data engineering and analytical use cases
  • Accessible to technical and business users
  • Collaborate inside a compresensive platform
Discover past work and don't recreate the wheel

Innovate with Big Data & AI.

  • Simplify the data architecture
  • Eliminate the data silos
  • Work across teams and innovate faster

Methodology and roadmap for success

Adaltas works with your team to leverage the Databricks platform with a comprehensive Methodology. Our experts are certified with Databricks as well as with the major Cloud providers including Microsoft Azure, Amazon AWS and Google GCP.

Qualify the use case

  • What is the business challenge today.
  • What is the business outcome and value you are hoping to achieve.

Qualify the data

  • Is the data in the cloud?
  • Describe the data: type, size, format, speed, ...
  • Understand the complexity of the Big Data the client is working with.

Qualify the solution

  • Describe the current technology ecosystem and data pipeline architecture.
  • Who are the data users? (data scientits, data engineers, business users)

State-of-the-art platform for analytics and AI in the cloud

The extensive Spark ML libraries and integration with popular frameworks such as Tensorflow, PyTorch, etc. make Databricks the market leader among AI platforms. Additionally, the introduction of MLFlow has made managing the machine learning lifecycle easy and productive.

Don't recreate the wheel

Discover past work and don't recreate the wheel

  • Building models is a very iterative process and most gains are incremental
  • Almost all Data Scientist teams regularly recreate work and therefore won't get as far as they could by refining past work. It is also a waste of money.
Collaboration between DS

Collaboration between DS

  • There is value to also sharing past work or working together on diffrent parts of the problem. Having a system of record for how work is done makes things easier and increase satisfaction.
  • Collaborate with business users, data engineers and analyts.
Easy reproducibility

Easy reproducibility of own and other works

  • If a model is not reproducible, it is worthless
  • It is also a cornertone of collaboration. Two individuals need to be able to reproduce others results.

Articles related to Databricks

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We are a team of Open Source enthusiasts doing consulting in Big Data, Cloud, DevOps, Data Engineering, Data Science…

We provide our customers with accurate insights on how to leverage technologies to convert their use cases to projects in production, how to reduce their costs and increase the time to market.

If you enjoy reading our publications and have an interest in what we do, contact us and we will be thrilled to cooperate with you.