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DataRPM vs Sisense comparison

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Progress Software Logo

DataRPM

6 views|3 comparisons
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Sisense

Read 39 Sisense reviews
1,811 views|1,638 comparisons
95% willing to recommend
Featured Review
Use DataRPM?
FernandoMorote
Business intelligence solution that has improved automation and provided meaningful insights
We did not have a BI tool previously. We used spreadsheets, complicated pivot tables and macros. Using Sisense, we were able to get rid of those... Read more →
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  • "This solution is more expensive than Tableau, Qlik and Dundas. It is an expensive tool. They charge $75,000 while Tableau is $45,000."

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    What do you like most about Sisense?
    Top Answer:The solution's technical support team is good.
    Read all 5 answers   →
    What needs improvement with Sisense?
    Top Answer:Sisense is good in terms of visualization, but it has some drawbacks. For example, it doesn't have any way to sort or filter tables directly on the server side. Also, you can't have multiple tabs; it… more »
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    What is your primary use case for Sisense?
    Top Answer:We use the solution to centralize all processes.
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    Ranking
    7th
    out of 7 in Anomaly Detection Tools
    Views
    6
    Comparisons
    3
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    17th
    out of 108 in BI (Business Intelligence) Tools
    Views
    1,811
    Comparisons
    1,638
    Reviews
    5
    Average Words per Review
    373
    Rating
    7.4
    Comparisons
    Learn More
    Progress Software
    Sisense
    Overview

    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. 

    Sisense is an end-to-end business analytics software that enables users to easily prepare and analyze large, complex datasets. Sisense’s Single-Stack BI software includes data preparation, data management, analysis, visualization and reporting capabilities.

    Sample Customers
    Cisco, Micropact, Orange, Jaguar, Transaction Network Services
    Ebay, WIX, Wave Accounting, ESPN.com, Magellan Luxury Hotel, Paylogic, Sony, Merck, EDA, One Hour Translation, NASA, Plastic Jungle, Philips, Yahoo
    Top Industries
    No Data Available
    REVIEWERS
    University17%
    Media Company13%
    Leisure / Travel Company8%
    Retailer8%
    VISITORS READING REVIEWS
    Financial Services Firm25%
    Computer Software Company16%
    Healthcare Company6%
    Media Company5%
    Company Size
    No Data Available
    REVIEWERS
    Small Business57%
    Midsize Enterprise17%
    Large Enterprise26%
    VISITORS READING REVIEWS
    Small Business26%
    Midsize Enterprise14%
    Large Enterprise60%

    DataRPM is ranked 7th in Anomaly Detection Tools while Sisense is ranked 17th in BI (Business Intelligence) Tools with 39 reviews. DataRPM is rated 0.0, while Sisense is rated 8.8. On the other hand, the top reviewer of Sisense writes "Business intelligence solution that has improved automation and provided meaningful insights". DataRPM is most compared with , whereas Sisense is most compared with Microsoft Power BI, Tableau, Apache Superset, Qlik Sense and Amazon QuickSight.

    We monitor all Anomaly Detection Tools 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.