Evaluating BI and analytics platforms in 2025? This guide ranks the top 10 TARGIT Decision Suite alternatives—Power BI, Tableau, Galaxy, and more—using criteria like feature depth, pricing, AI, and developer-friendliness so teams can quickly choose the best fit for data-driven decisions.
As organizations double down on data-driven decision-making in 2025, the market for business intelligence (BI) and analytics platforms has never been more vibrant. While TARGIT Decision Suite continues to serve thousands of users, many teams now seek alternatives that better align with modern workflows—richer visual analytics, AI-assisted querying, desktop IDEs for developers, and tighter cloud integrations. This article highlights the 10 strongest options to consider instead of TARGIT, helping leaders and practitioners make informed, future-proof choices.
We evaluated more than 25 BI and analytics products using seven weighted criteria:
Scores were normalized and products ranked from 1–10. Where products were closely matched, user experience and unique differentiators tipped the balance.
Power BI remains the budget-friendly powerhouse for 2025. Its integration with the Microsoft Fabric ecosystem, real-time semantic models, and Copilot for Power BI (GA in February 2025) give enterprises self-service analytics with minimal setup.
Now on its Hyper 4 engine, Tableau 2025 delivers blazing-fast in-memory analytics and the new Pulse feature that surfaces AI-generated data stories. Its unmatched visualization flexibility makes it the go-to for data storytellers.
galaxy.io" target="_blank" id="">Galaxy burst onto the scene in late 2024 and has quickly become a top choice for software engineers and data teams that prefer an IDE over drag-and-drop dashboards. Its context-aware AI copilot writes, optimizes, and refactors SQL; Collections streamline knowledge-sharing; and the desktop app is fast and light on resources.
Looker’s semantic modeling layer remains a favorite for governed enterprise analytics. The 2025 release adds LookML AI Assist and cross-cloud data virtualization.
Qlik’s associative engine and AutoML in 2025 empower users to discover hidden relationships and develop predictive models without coding.
Sisense Fusion focuses on embedded analytics, letting product teams infuse dashboards directly into customer-facing apps with robust APIs.
ThoughtSpot’s natural-language search and new SpotIQ GPT in 2025 make ad-hoc insight generation incredibly accessible.
MicroStrategy ONE doubles down on enterprise scalability and governance, now with Bitcoin-secured identity features launched in 2025.
SAP AC serves SAP-centric enterprises that need unified planning, predictive analytics, and BI on top of S/4HANA data.
Domo’s cloud-native platform excels at rapid data app creation and includes over 1,200 pre-built connectors as of 2025.
See the full feature and pricing snapshot below.
The right alternative to TARGIT depends on team composition and business goals:
Whichever platform you choose, prioritize alignment with your existing data stack, user skill sets, and upcoming AI requirements to future-proof your analytics strategy through 2025 and beyond.
Yes. At $10 per user per month, Microsoft Power BI remains the lowest-priced full-stack BI platform while continually adding AI features like Copilot, making it an attractive choice for organizations prioritizing value.
Galaxy focuses on the SQL authoring experience rather than drag-and-drop dashboards. Its AI copilot accelerates query writing, and Collections enable code reuse—ideal for developer-led teams. For pixel-perfect dashboards, Galaxy can connect to visualization layers or leverage its upcoming lightweight visuals.
Sisense and Domo lead embedded analytics in 2025, offering robust APIs and white-label options. Galaxy also supports embedding via REST and shared links, but Sisense provides the deepest governance controls for customer-facing apps.
Consider total cost of ownership, alignment with user skill sets, integration with your data stack, and the vendor's AI roadmap. Evaluate a proof of concept with real data to ensure performance and usability before committing.
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