Birst vs DataRPM comparison

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Executive Summary

We performed a comparison between Birst and DataRPM based on real PeerSpot user reviews.

Find out what your peers are saying about Microsoft, Tableau, Oracle and others in Reporting.
To learn more, read our detailed Reporting Report (Updated: March 2024).
765,234 professionals have used our research since 2012.
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Pricing and Cost Advice
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    Information Not Available
    Ranking
    32nd
    out of 50 in Reporting
    Views
    225
    Comparisons
    165
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    Views
    9
    Comparisons
    4
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    Buyer's Guide
    Reporting
    March 2024
    Find out what your peers are saying about Microsoft, Tableau, Oracle and others in Reporting. Updated: March 2024.
    765,234 professionals have used our research since 2012.
    Comparisons
    Learn More
    Overview

    Birst Networked BI and Analytics eliminates information silos. Decentralized users can augment the enterprise data model virtually, as opposed to physically, without compromising data governance.

    A unified semantic layer maintains common definitions and key metrics.
    Birst’s two-tier architecture aligns back-end sources with line-of-business or local data. Birst’s Automated Data Refinement extracts data from any source into a unified semantic layer. Users are enabled with self-service analytics through executive dashboards, reporting, visual discovery, mobile tools, and predictive analytics. Birst Open Client Interface also offers integration with Tableau, Excel and R.

    Birst goes to market in two primary ways: as a direct sale, for enterprises using Birst on internal data to manage their business; and embedded, for companies who offer analytic products, by embedding and white-labeling Birst capabilities into their products.

    Birst’s is packaged in 3 available formats: Platform and per-user fee; by Department or Business Unit; by end-customer (for embedded scenarios).

    DataRPM delivers a Cognitive Predictive Maintenance (CPdM) Platform for Industrial IoT. DataRPM uses Meta-Learning technology, integral component of Artificial Intelligence to automate predictions of asset failures. CPdM is a full stack platform available on cloud or on premises that connects to the data lake and then automatically runs multiple Machine Learning experiments, finds patterns & anomalies in data, identifies influencing factors & predictors, and builds an ensemble of predictive models to automate Predictive Maintenance. Not only does CPdM platform delivers descriptive, predictive, prescriptive analytics through Natural Language Discovery module but also provides a closed loop system by integrating these actionable insights through APIs to ERP, CRM, and CMS systems. 

    Sample Customers
    Citrix Systems, Jive Software, SunnyD, Toshiba Medical Systems, Cisco OpenDNS, RB, Sunny D, Vertafore
    Cisco, Micropact, Orange, Jaguar, Transaction Network Services
    Top Industries
    REVIEWERS
    Healthcare Company25%
    Retailer17%
    Insurance Company8%
    Computer Software Company8%
    No Data Available
    Company Size
    REVIEWERS
    Small Business14%
    Midsize Enterprise33%
    Large Enterprise52%
    No Data Available
    Buyer's Guide
    Reporting
    March 2024
    Find out what your peers are saying about Microsoft, Tableau, Oracle and others in Reporting. Updated: March 2024.
    765,234 professionals have used our research since 2012.

    Birst is ranked 32nd in Reporting while DataRPM is ranked 7th in Anomaly Detection Tools. Birst is rated 7.4, while DataRPM is rated 0.0. The top reviewer of Birst writes "The dashboards and Visualizer are valuable". On the other hand, Birst is most compared with Microsoft Power BI, Alteryx and ThoughtSpot, whereas DataRPM is most compared with .

    We monitor all Reporting reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.