Domo and Birst are both competing in the business intelligence platform category. Based on the current analysis, Domo seems to have an advantage in terms of ease of use and integration capabilities, whereas Birst is favored for more complex data models and scalability suited for enterprise-level needs.
Features: Domo offers real-time data visualization through its robust dashboard, enhancing decision-making speed. It supports seamless teamwork with excellent collaboration tools integrated into existing applications. Birst is known for strong data governance, ensuring security and compliance. It stands out with its advanced analytics, catering to intricate data insights. Domo's simplicity and integration are highlights, while Birst focuses on powerful data management and scalability.
Room for Improvement: Domo could improve in offering more advanced data modeling capabilities to compete with the likes of Birst in handling complex data structures. Enhancements in scalability might also benefit Domo to better support larger enterprises. On the other hand, Birst needs to work on improving user-friendliness, as its complexity can be daunting for less technical users. Additionally, reducing initial configuration effort and simplifying its interface could make Birst more appealing to a broader audience.
Ease of Deployment and Customer Service: Domo’s cloud-based model assures rapid deployment with a scalable infrastructure and is praised for its responsive customer service that delivers effective solutions. Birst, with its hybrid deployment options, offers flexibility for cloud and on-premise requirements but might involve more initial configuration. Its competent service team is well-regarded for handling technical queries. Domo excels in deployment speed, whereas Birst offers adaptable solutions for complex setups.
Pricing and ROI: Domo's pricing structure aligns with its extensive features, promising high ROI for companies leveraging its analytics. Birst, despite a potentially higher cost, justifies its price with detailed analytics and scalable solutions, targeting enterprises seeking long-term benefits. Domo offers an attractive cost-benefit ratio for immediate use, while Birst is attractive to enterprises with intricate needs and a focus on long-term return.
While they eventually provide the correct answers, their support for smaller customers could be improved.
Sigma, which is written for Snowflake, scales more easily than Domo.
End users require a license to run their own reports and dashboards, which are fairly expensive.
Domo is expensive compared to other solutions.
I have been using it for four years and have been able to extract the information I need from it.
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).
Domo is a cloud-based, mobile-first BI platform that helps companies drive more value from their data by helping organizations better integrate, interpret and use data to drive timely decision making and action across the business. The Domo platform enhances existing data warehouse and BI tools and allows users to build custom apps, automate data pipelines, and make data science accessible for anyone through automated insights that can be shared with internal or external stakeholders.
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