Business processes (BPs) refer to a sequence of actions or a set of processes logically related to each other. A business process contains a series of activities.
An enterprise might have a number of interrelated processes, which serves a particular result or goal that may include M2M/IoT data acquiring, storing, organizing, and transactions using the stored data.
BPs may be of several types, for example, operational, support, service and management. A BP is a representation or process matrix or flowchart of a sequence of activities with interleaving decision points.
A process matrix has a number of processing elements. For example, Internet of RFIDs enables a BP called “tracking of RFID labelled goods”, which also enables inventory control processes.
Contents
Business Intelligence
Business Intelligence (BI) is a process that enables a business service to extract new facts and knowledge, and then make better decisions.
The new facts and knowledge follow from the earlier results of data processing, aggregation and analyzing those results. As an example we can consider Automatic Chocolate Vending Machines (ACVMs).
Integration and Enterprise System
Following are the standardized BPs as defined in the Oracle’s application integration architecture:
- Integrating and enhancing the existing systems and processes
- Business intelligence
- Data security and integrity
- New business services/products (web services)
- Collaboration / Knowledge management
- Enterprise architecture / Service Oriented Architecture (SOA)
- E-commerce
- External customer services
- Supply chain automation / visualization
- Data center optimization
A number of BPs orchestrate, which means they run in parallel and some in a sequence. Process matrix provides the decision points, which indicates which BPs must run in parallel and which must run in a sequence.
M2M/IoT Data Analytics Architecture
Analytics architecture consists of the following layers:
- Data sources layer
- Data storage and processing layer
- Data access and query processing layer
- Data services, reporting and advanced analytics layer
Following figure shows an overview of Berkeley Data Analytics Stack (BDAS) architecture as a reference model for the analytics:
BDAS consists of data processing, data management, and resource management layers.
Knowledge Management
Information in a given context is an answer to the query or set of queries. Visualization or analytics of data gives information. Knowledge is shareable information and understanding about a subject or context.
IoT data sources continuously generate data, which the applications/services/processes acquire, organize and integrate/enrich using analytics.
Knowledge discovery tool provides the knowledge at a particular time as more and more data are processed and analyzed.
Knowledge management functions include:
- Managing the knowledge as new knowledge is regularly discovered
- Processing and storing that knowledge
- Provisioning for replacing the earlier gathered knowledge
- Managing the life cycle of stored knowledge
Sensible and reasonable decisions are made using advanced tools which enable wise wisdom. Wisdom is the ability to use the experience and knowledge in order to make sensible and reasonable judgment and decisions.
Following figure shows knowledge management reference architecture and its correspondence with the ITU-T four layer reference model and IETF’s reference model
Suryateja Pericherla, at present is a Research Scholar (full-time Ph.D.) in the Dept. of Computer Science & Systems Engineering at Andhra University, Visakhapatnam. Previously worked as an Associate Professor in the Dept. of CSE at Vishnu Institute of Technology, India.
He has 11+ years of teaching experience and is an individual researcher whose research interests are Cloud Computing, Internet of Things, Computer Security, Network Security and Blockchain.
He is a member of professional societies like IEEE, ACM, CSI and ISCA. He published several research papers which are indexed by SCIE, WoS, Scopus, Springer and others.
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