Interview with a machine about Cognos Analytics (AI/ChatGPT/Openai)
What do AI machines know about the new Cognos Analytics Version? We “talked” with OPENAI. The answers from the questions were taken 1-to-1.
In fact, interesting to read. Enjoy:
What are the new features of cognos analytics Version 11.2.4?
- Easy-to-use Natural Language Query
- Intuitive Visualization
- Enhanced Reporting and Dashboarding
- Improved Query Performance
- Faceted Search
- Improved Collaboration Features
- Enhanced Data Discovery and Exploration
- Self-Service Data Preparation
- Advanced Analytics Capabilities
- Improved Security and Governance
What does the future of Cognos Analytics with watson look like?
The future of Cognos Analytics with Watson looks very promising. Cognos Analytics has already integrated its natural language processing technology from Watson to provide users with a more conversational, intuitive experience. This integration has enabled users to ask more complex questions of their data and receive more accurate answers in return. As Watson is further developed and incorporated into Cognos Analytics, users can expect to see even more sophisticated insights being generated from their data. This will enable them to make better, more informed decisions and gain more value from their data.
Why are Cognos Datamodules better than Framework Manager Packages?
Cognos Data Modules are better than Framework Manager Packages because they provide an easier way to develop and deploy data models. Unlike Framework Manager packages, which require a lot of manual work to create and maintain, Cognos Data Modules are generated automatically. They also have an intuitive user interface which makes it easier to explore and manipulate data without needing to understand complex query language. Furthermore, Data Modules are optimized for performance and can be easily shared with other users.
How can query performance be improved in Cognos?
1. Simplify query logic: Simplifying the query logic by using fewer filters and calculations can help improve query performance.
2. Use aggregate table: Using aggregate tables can help improve query performance by retrieving summarized data instead of detailed data.
3. Limit data volume: Limiting the data volume can help reduce the time it takes to process the query.
4. Use query hints: Query hints can help improve query performance by allowing the user to specify certain features like indexes, join order, etc.
5. Optimize the database: Optimizing the database with indexing, partitioning and other techniques can help improve query performance.
6. Use appropriate data types: Using the appropriate data type for each column in the database can help improve query performance.
7. Use caching: Caching can help improve query performance by storing frequently used data in memory.
8. Optimize report design: Optimizing the report design by minimizing the number of objects and using appropriate formatting can help improve query performance.
What is the best tool for data analysis and visualization?
The best tool for data analysis and visualization depends on the type of data being analyzed and the types of visualizations desired. Some popular data analysis and visualization tools include Tableau, Microsoft Power BI, Qlik Sense, IBM Watson Analytics, and SAS Visual Analytics.
Why is Cognos better than Power BI?
Cognos is generally considered to be better than Power BI for larger organizations because it is more comprehensive and can easily scale up to fit the needs of large enterprises. Cognos also offers more sophisticated features such as advanced analytics, data mining, and forecasting capabilities. Additionally, Cognos has more robust security features, allowing organizations to more easily control access to sensitive data.
