A complete guide to data platforms by Xomnia

A modern data platform is a stack of tools designed to facilitate extracting business value from data, and which can be developed on a cloud platform. In the sections below, Xomnia's data engineers answer the FAQs about data platforms that leaders and decision-makers of data and analytics teams need to know.

What is a cloud platform, and how does it differ from a cloud service?

Cloud platforms in general are a suite of cloud services (or an online toolbox), that form the building blocks for implementing business applications on the cloud. Cloud platforms are offered by cloud providers such as AWS, Azure or Google Cloud Platform (GCP). Generally speaking, a company will have its product(s) and its data platform in the cloud.

A mature data and analytics platform built on a cloud platform is composed of various data ingestion services, data storage services, machine learning pipelines and BI layers.

Are all data platforms cloud platforms?

No, they are not. A modern data platform is a stack of tools designed to facilitate extracting business value from data. A data platform can be developed on a cloud platform. Vendors of cloud platforms have developed a large number of services to facilitate the development of a data platform.

However, it is also possible to build a data platform outside of a cloud platform. Having said that, it’s important to note that most services, especially the open-source offerings, are available to host in a non-cloud data center. For example, one can use Apache Airflow, Kubernetes and Apache Druid to create an on-premise modern data platform.

  • Common processes carried out by  a data platform are:
  • Connecting to data source systems
  • Orchestrating data ingestion tasks to make sure that all company data ends up in the unified data platform
  • Processing and transforming incoming data streams
  • Storing data in blob-storage
  • Storing (processed) data in use-case specific storage, e.g. relational databases, NoSQL storage, Big-Data Engine
  • Providing components to extract value from data, for example, machine learning models or dashboards
  • Ensuring the security and authorization of data flows

A major advantage of using cloud platforms to implement your data platform is that cloud services turn managing the cloud infrastructure into an abstract problem. In other words, the difficulty of managing complex infrastructure, like servers and networks, is eliminated. In contrast, managing an on-premise data platform is a laborious task that requires a lot of expertise.

Build your data platform with Xomnia

What are the benefits of a data platform?

Case: Xomnia creates a robust and scalable data ingestion system for The Ocean Cleanup

How do you create a data platform?

Centralize all data sources in one place with Xomnia's expertise

What components are a part of the cloud infrastructure for the platform?

Seeking advice from an experienced data engineer?

What makes a strong data platform?

Question about data platforms? Get in touch

What are the challenges when creating or migrating to a data platform?

How to make your data platform future proof?

Case: TATA Steel creates a single source of truth of data using a data lake

How can I utilize my cloud data platform for machine learning?

Continue reading: All you need to know about migrating to the cloud
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