InAppBI icon
InAppBI icon

InAppBI

Use SQL, mash up data using Javascript, visualize and embed using JavaScript SDK within your SaaS application, customize using HTML and JS editor, proactively embed insights within your application.

Cost / License

  • Paid
  • Proprietary

Platforms

  • Mac
  • Windows
  • Linux
  • Android
  • iPhone
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Features

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  1.  Embedded apps
  2.  Embeddable
  3.  Data visualization
  4.  Visual analysis

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InAppBI information

  • Developed by

    InAppBI
  • Licensing

    Proprietary and Commercial product.
  • Alternatives

    11 alternatives listed
  • Supported Languages

    • English

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InAppBI was added to AlternativeTo by amit1 on and this page was last updated .
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What is InAppBI?

InAppBI is a platform which empowers enterprise applications with affordable analytics. Connect to multitude of data sources (including Relational, No SQL, Big Data and API’s), query and transform data using SQL and full scripting support, build dashboards using host of visualization libraries and embed right within your applications using plain HTML and Javascript SDK's. Proactively Push Insights within and outside application by scripting complex business logic. Embed predictive insights right within your application using Machine Learning algorithms which analyze your data.

InAppBI advantage:

  1. JavaScript SDK, HTML and CSS based Application Embeddebility. Adds tons of flexibility to make embedded analytics part of your application
  2. Push based Contextual Insights
  3. Native SQL Query Support for underlying relational data source, native query support for NoSQL options like MongoDB, ElasticSearch etc
  4. Avoid ETL by querying directly to the single source of truth
  5. Out of the box Site: Create a website with built in authentication and authorization in 1 click
  6. Easily integrate Multi-Tenant Support within your SaaS application into InAppBI.
  7. Let the users of your application compose dashboards from standalone visualizations, save and share.
  8. Simplified Ad-hoc query Interface embedded within your application
  9. Push predictive insights from ML models into your application

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