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Geared for large enterprises with a substantial budget, IBM Cognos Analytics delivers a robust data mining platform for organizations looking to extract value from diverse sets of data. It focuses on self-service visualizations and dashboards—and it includes strong artificial intelligence and machine learning functionality.
This approach helps users spot patterns and behavior that might otherwise not be visible. The system also allows users to pose questions and explore data using a natural language-powered AI assistant. Ideally, this approach reduces the time required for data preparation and processing.
Clearly, IBM has is a heavyweight in the world of business intelligence and analytics. Recently, the company updated and rebranded its flagship BI and analytics offering, now IBM Cognos Analytics, to reflect the changing requirements of organizations. This includes combining production reporting tools with more powerful self-service dashboards—and a more unified platform for reporting and analytics.
In short, if your company can afford it, this is a market-leading tool with next-gen features.
IBM’s focus is on delivering the right information to the right people at the right time. In order to achieve this objective, IBM Cognos Analytics includes tools for importing diverse sets of data, identifying missing data, incorrect data and misleading information.
Using AI, it examines data sets and offers insights into how the data can be best displayed and used. The built-in AI component provides smarter self-service capabilities than in the past. What’s more, the platform is designed to deliver self-service data exploration and visualizations that are appropriate to a user’s role. The product is available on-premise as well as in the cloud—with a single interface for desktops, laptops and mobile devices. It includes scheduling and subscriptions to data. Users report that the platform has become more intuitive and easier to use since it was updated to look more like IBM Watson Analytics in 2015.
Overview and Features
Business analysts, power developers, data scientists. However, the platform can present challenges for casual users.
Graphical drag-and drop.
Support for extract, transform and load (ETL) processes, integration with data warehouses, and support for other data integration and SQL tools. Accepts multidimensional and relational data sources.
- Ad Hoc Analysis
- Ad Hoc Reporting
- Predictive Analytics
- Customizable dashboard
AI and Machine Learning Support
IBM has a 3.9 rating at Gartner Peer insights.
Trial version of the premium edition is free. Premium edition running in a multi-tenant cloud costs $70 per user per month. Enterprise edition cost available directly from the company.
|Focus||Strategic management through guided data discovery.|
|Key features and capabilities||Strong ETL and reporting tools. Powerful machine learning and AI. Contextualized smart searching and data modeling based on keywords and customized requirements.|
|User comments||Mature platform that offers a high level of flexibility. Some concerns about stability and self-service functions.|
|Pricing and licensing||Trial version of the premium edition is free. Premium edition running in a multi-tenant cloud costs $70 per user per month. Enterprise edition cost available directly from the company.|