What is On-Premises Analytics? Examples and Use Cases

On-premises analytics

Analytics infrastructure hosted within an organization's own servers, offering control, security, and customization compared to cloud solutions.

Definition and Overview

• Core components

  On-Premises Analytics typically comprises data collection agents or JavaScript tracking scripts deployed on your own servers, in-house databases for storage, an ETL (extract, transform, load) pipeline, processing engines, and visualization dashboards. This stack resides entirely within your organization’s network, eliminating dependency on external cloud providers.

  • Data collection:

    Capturing user interactions, pageviews, events, and custom metrics through on-premise tracking scripts or server log ingestion.

  • Data storage:

    Storing raw or processed event data in locally managed databases or data warehouses.

  • Data processing & analysis:

    Transforming, aggregating, and analyzing data using in-house compute resources or on-premise clusters.

Advantages of On-Premises Analytics

• Data control & ownership

  Full control over data collection, storage, retention policies, and processing pipelines without external access.

• Enhanced security & compliance

  Ability to implement and audit security measures in line with specific regulatory requirements and internal policies.

  • Gdpr compliance:

    Keep personal data within EU-controlled infrastructure to meet GDPR data residency requirements.

  • Hipaa compliance:

    Secure and audit protected health information (PHI) within on-premises environments to adhere to HIPAA standards.

• Customization & performance optimization

  Tailor hardware, software configurations, and analytics features to match specific workloads and performance SLAs.

Challenges and Considerations

• Infrastructure and maintenance costs

  Initial capital expenditure on servers, networking, and storage, plus ongoing maintenance, upgrades, and personnel costs.

  • Hardware refresh cycles:

    Plan for periodic server and storage hardware replacements to ensure reliability and performance.

  • Staffing requirements:

    Ensure you have or hire skilled DevOps and data engineers to manage and support the analytics stack.

• Scalability constraints

  Scaling compute and storage resources requires manual provisioning and capacity planning, which can lead to under- or over-provisioning.

• Technical complexity

  Requires expertise to configure, secure, and integrate disparate components, as well as to handle backups, disaster recovery, and high availability.

On-Premises vs SaaS Analytics

• Saas analytics

  Third-party hosted services such as PlainSignal and Google Analytics 4 provide turnkey analytics with minimal setup, automatic updates, and built-in compliance features. However, they involve sending data to external servers and offer limited customization.

• On-premises analytics

  Self-hosted solutions grant full data sovereignty, customizability, and compliance control, at the cost of maintenance overhead and capital investments.

Implementation Examples

• Plainsignal (cookie-free saas)

  <link rel="preconnect" href="//eu.plainsignal.com/" crossorigin />
  <script defer data-do="yourwebsitedomain.com" data-id="0GQV1xmtzQQ" data-api="//eu.plainsignal.com" src="//cdn.plainsignal.com/PlainSignal-min.js"></script>
  

• Google analytics 4 (saas)

  <!-- Google Analytics 4 -->
  <script async src="https://www.googletagmanager.com/gtag/js?id=G-XXXXXXXXXX"></script>
  <script>
    window.dataLayer = window.dataLayer || [];
    function gtag(){dataLayer.push(arguments);}  
    gtag('js', new Date());
    gtag('config', 'G-XXXXXXXXXX');
  </script>
  

• Matomo self-hosted (on-premises)

  <!-- Matomo On-Premises -->
  <script>
    var _paq = window._paq || [];
    _paq.push(['trackPageView']);
    _paq.push(['enableLinkTracking']);
    (function() {
      var u="//analytics.example.com/";
      _paq.push(['setTrackerUrl', u+'matomo.php']);
      _paq.push(['setSiteId', '1']);
      var d=document, g=d.createElement('script'), s=d.getElementsByTagName('script')[0];
      g.type='text/javascript'; g.async=true; g.defer=true; g.src=u+'matomo.js'; s.parentNode.insertBefore(g,s);
    })();
  </script>
  

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