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Pentaho
Pentaho is a Unified Data Integration and Analytics Platform that addresses the barriers that block an organisation’s ability to get value from all their data. The platform simplifies preparing and blending any data and includes a spectrum of tools to easily analyse, visualise, explore, report and predict. Open, embeddable and extensible, Pentaho is architected to ensure that each member of the team — from developers to business users — can easily translate data into value
Type of content:
Assets
Type of asset:
Platform
Big data potential
Yes
Policy domains:
Innovation, Science & Technology
Phase in the policy cycle:
Policy Design and Analysis
TRL
8
Open license availability
No
Website
Tags:
BI
Data analytics
| SWOT Analysis for Pentaho |
||
|---|---|---|
| Helpful | Harmful | |
Internal |
Strengths• Pentaho lets you manage and process data in hybrid and multi cloud environments and solve business problems by using connectors to streaming data. • Comprehensive software that helps to access, prepare, blend and analyse any data from any source. • Internet of Things Analytics: Expect better business outcomes, from improved customer satisfaction to higher profitability • Big Data Integration and Analytics • Drive maximum value from your data with a complete platform for full data integration and business analytics. • Quickly and easily deliver the best data to your business and IT users without coding or complexity. • Business Analytics: Empower business users with interactive, real-time visual data analysis and predictive modelling, with minimal IT support. |
Weaknesses• No open license availability • Low ease of use • Poorly designed interface • No 24x7 support for standard users • No unified interface for all components • Basic user manual, which does not detail many of the concepts, which hinders the development and deployment of the solution. • User-Profiling is available only in Enterprise edition • Data Integration can be a resource hog when working with large data sets |
External |
Opportunities• Deep learning: More investments are pouring into deep learning after the initial traction on artificial intelligence. As deep learning technologies march on, we will see more of their application on BI software, primarily on image recognition and machine translation. • Internet of Things: It’s a staple of consumer technology fantasy, but internet-of-things is legitimately happening. We can see advances in algorithms, sensors and integration that drum up predictive analytics. The same technology will further enhance OLAP capabilities in BI solutions. |
Threats• Competition • No open license availability • Low ease of use • No 24x7 support for standard users • Poorly designed interface • Basic user manual, which does not detail many of the concepts, which hinders the development and deployment of the solution. • User-Profiling is available only in Enterprise edition • Data Integration can be a resource hog when working with large data sets |
