Datalayer Users

As a user, you are looking for agile and low cost iterations during your Data Science Project.

Datalayer targets 3 types of users who can create and/or use cost effective clusters of size they need without prior IT skills.

  1. Standalone Data Scientists.
  2. Small to medium analytics teams of data-driven business.
  3. Small analytics teams of non-data-driven business.

The typical stakeholders of a Data Science project are the Devops, a Data Scientist or a Business.

Figure - Profiles

You may have more than one hat (more than one profile) during the lifecycle of your Data Science project. For those 3 profiles, Datalayer solutions make life easier, more productive, cheaper and bring more business value.

  • Data Scientists use the Explorer to explore and share insights in a visual way, in private or in public (e.g. on Twitter). You also use the Explorer to request cluster resources for a certain period of time.
  • Business review the Data Scientist insights in his favorite environment like Microsoft Office 365 or Google.
  • Devops use the Kuber CLI to create the Kubernetes cluster and deploy the needed Applications. You also get the Kuber UI if you prefer beautiful screens.

This is applicable in Exploration and Alpha environments at every steps of your Projects

Big Data Science adoption trend can be summarized as such.

Big Data Science Adoption
Figure - Big Data Science Adoption

Business Stakeholders read and comment Data Stories.

Data Scientists use their Google drive and publish stories on twitter. They feed and search a Library with:

  • Datasets on HDFS and IPFS.
  • Notes to write, publish and reuse.
  • Models to create, publish and reuse.
  • APIs assembled based on Notes, to be deployed and monetized.

They analyse data and share results with Python, R and Spark on the Datalayer Explorer, a JupyterLab Web Notebook with extensions on a Kubernetes cluster.

Devops use a Datalayer to setup, secure and operate the distributed components that build up the Kubernetes platform.

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