IoT Big Data – IoT Analytics Solution, Pentaho


What is Pentaho? Pentaho is a complete analytics solution that enable enterprises to provide customers and partners with equipment and device intelligence in the context of existing applications and business processes. It provides the ability to blend operational data with data from your IT systems of record and deliver intelligent analytics to those stakeholders who need them most.

How is this accomplished by this solution
  • Using compelling visualizations, interactive reporting, ad hoc analysis, and tailored dashboards for internal use or embedding into your applications and portals
  • Using highly customizable web-based user interface to match your application’s branding, look, and feel
  • Using modern, 100% Java platform built on industry standards (e.g. RESTful APIs for easy integration with any web application)
  • Using rich integration with security, authentication, and single sign-on frameworks, as well as flexible capabilities for multi-tenant deployment

Pentaho empowers organizations to integrate, transform, and orchestrate machine and sensor data in a Big Data environment, as well as blend big data with data from traditional information systems.

The process to accomplished this are:

  • Ingest and process machine and sensor data in Big Data architectures from messaging services, web APIs, and data files.
  • Prepare, model, and explore semi-structured and unstructured data sets
  • Native connectivity to leading Hadoop1 distributions, NoSQL stores, and analytic databases.
  • Blend sensor and machine data with data from data warehouses, enterprise applications, social media, etc.
  • Uncover meaningful patterns in equipment and device data with powerful machine learning and data mining tools.
  • Operationalize R models and machine learning functions as a part of the data integration workflow with the Data Science Pack.



Pentaho can be used in the enterprise as a solution to

Accelerate time to value with complete data integration & analytics solutions

  • Quickly integrate and orchestrate data from any source – including data warehouses, enterprise applications, Hadoop, NoSQL, and more
  • Automatically deliver secure, blended data on demand with IT trust to ensure accuracy, compliance, and governance
  • Bridge gap between business and IT with unified solutions for ETL2, business intelligence, and predictive analytics

Deliver scalable analytics with maximum performance and reduced risk

  • Insulate your architecture from the shifting sands of new technologies and versions with Pentaho’s Adaptive Big Data Layer
  • Deploy Pentaho on premise or in the cloud, offering the flexibility to blend data across systems and organizations
  • Achieve precise control with a full breadth of administrative tools, including detailed performance monitoring, analytics content distribution, job management, and more

Open standards and architecture

  • Extend the analytics to customers and partners by embedding the solution in your existing applications, portals, and processes
  • Easily customize Pentaho’s look & feel, integrate with security hierarchies, and connect to 3rd party charts and reports
  • Create a completely tailored interactive analytics experience for end users with a powerful toolset for custom visualization
  • Empower developers with a straightforward framework for creating platform plug-ins



Pentaho is one of several IoT Analytics solution in the market to help companies to manage IoT big data, analytics and predictive analytics, in the context of existing applications and business processes.


1 Apache Hadoop is an open source software framework that enables large data sets to be broken up into blocks, distributed to multiple servers for storage and processing. Hadoop’s strength comes from a server network – known as a Hadoop cluster – that can process data much more quickly than a single machine.

2 Extract, Transform, Load (ETL) refers to a process in database usage and especially in data warehousing that performs: Data extraction – extracts data from homogeneous or heterogeneous data sources.



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