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Periscope Data (Sisense)

About Periscope Data (Sisense)

Periscope Data by Sisense is a comprehensive business intelligence and data analytics platform designed to empower data teams within large enterprises. It enables users to connect, analyze, and visualize complex data sets from multiple sources in a unified environment, facilitating data-driven decision-making across organizations. The platform supports SQL, Python, and R, allowing data scientists and analysts to build sophisticated models and custom visualizations.

Targeted primarily at enterprise-level organizations with mature data strategies, Periscope Data offers robust data integration, advanced analytics, and collaborative features that streamline workflows between data teams and business stakeholders. Its primary value lies in accelerating the analytics lifecycle, improving data accuracy, and enabling scalable insights that drive operational and strategic outcomes. The platform’s SaaS deployment ensures ease of access and scalability without the overhead of managing infrastructure.

How to evaluate BI & Data Visualization

This is how the CIOPages Research Team evaluates this category. It is not an assessment of Periscope Data (Sisense). It comes from our Business Intelligence & Analytics buyer guide.

25%
Semantic Layer & Governed Metrics
How metric definitions are authored, versioned, and certified; whether the model is tool-locked or interoperable (LookML, dbt/Cube via SQL or MCP); row- and column-level security inheritance; lineage; and prevention of conflicting definitions across content
20%
Self-Service & Analytical Depth
Authoring experience for analysts vs. business users, drag-and-drop vs. spreadsheet vs. search paradigms, calculation expressiveness (DAX, LookML, set/associative logic), depth of ad-hoc exploration, and how far a non-technical user gets without IT
15%
AI & Natural-Language Analytics
Quality of NL-to-query and agentic features (Copilot, Pulse, Spotter, Qlik Answers, Gemini, Joule), whether answers are grounded in the governed semantic layer, explainability and citation of results, hallucination guardrails, and forecasting/insight automation
15%
Data-Platform Fit & Performance
Live query-down vs. in-memory extract behavior on your warehouse (Snowflake, Databricks, BigQuery, Fabric/OneLake), concurrency at your real user count, caching/acceleration, freshness, and whether one governed copy of data is preserved
10%
Embedding & Extensibility
White-label embedding, multi-tenant isolation and per-tenant row-level security, developer SDKs and REST/GraphQL APIs, infrastructure-as-code for content, and headless/API access for products you ship to customers
10%
Governance, Security & Administration
SSO/SAML/SCIM, granular RBAC, certified-content workflows and usage analytics, deployment options (multi-cloud, sovereign, on-prem), audit logging, and the operational burden of capacity, version, and content sprawl management
5%
Total Cost & Ecosystem Alignment
Licensing unit (per-user vs. capacity vs. consumption) and how it scales to thousands of viewers, bundling with an incumbent cloud, migration and retraining cost, and lock-in to a single vendor’s data stack

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Quick Facts

www.sisense.com/periscope-data
CategoryData & Analytics
SubcategoryBI & Data Visualization

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