Blockchain Technology for Advanced Analytics in Business Production

This report examines the use of blockchain technology in conjunction with advanced analytics to enhance business production capabilities. It highlights how modern tools like SAS, Tableau, and Python enable firms in the IT and services sectors to innovate in blockchain management. The study emphasizes the reliance of online and e-commerce businesses on big data analytics for understanding consumption patterns and improving customer engagement. Furthermore, the incorporation of big data analytics enhances logistics and inventory management, while data mining from open sources provides additional business development opportunities. The integration of these technologies not only improves resource utilization through IoT but also strengthens relationships with stakeholders and suppliers, ultimately increasing security and efficiency in business operations. Desklib provides access to similar solved assignments and past papers for further study.

USING BLOCK CHAAIN
FOR ADVVANCE
ANALYTICS

Introduction and
Purpose
• Using the development of block chain and the advanced analytics will
automatically increase the production ability that will automatically
increase the development of the business. The main purpose for the
development of this study is going to face the development in the
production function if the company is using innovative method using
the big data analytics that will allow the development of the business
in an effective way
• Through the development of the business it is possible for the
companies to deal with the development of better innovation in the
technologies will bring the better development of the business.

Data Analysis and Results
• The managers who have taken part in the qualitative analysis, has
stated the fact that using the modern tools in the form of SAS, TABLEU,
PYTHON will enable the firms that are dealing with the IT and services
sectors to bring in enough innovations in identifying the block chain
management.
• A bigger section of online and e-commerce business is depending
heavily on the big data analytics. They helps in the development of
consumption patterns and the big guns can get the data from the
website visits of the customers. They tend to give the customers the
goods that are required to do the development of the business.
• Through the incorporation of big data analytics, the innovations in the
logistics of the company is using the involvement of better
accommodation that will increase the capacity of the business by
expanding the inventories

Discussion and
Implications
• On the other hand, the development of analysing power of the data mining
will be enabling the development of the business even from the open
sources of the data that are available from the third party
• Using the tools that are being mentioned above will be looking to increase
the development of the business that will increase the involvement of
better relationship with the stakeholders of the company and the suppliers
of the raw materials
• Through the introduction of innovation process this will increase the level
of the security. It has been implied that using the developed level of IOT, is
going to increase the resources utilisations that will not only increase the
resources but will also allocate the resources in an effective manner

Reference list
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performance using big data analytics capability and business strategy alignment?. International
Journal of Production Economics, 182, 113-131.
• Banafa, A. (2019). Secure and Smart Internet of Things (IoT): Using Blockchain and AI. Stylus
Publishing, LLC.
• Herrmann, M., Petzold, J., & Bombatkar, V. (2018, September). Blockchain-backed analytics.
Adding blockchain-based quality gates to data science projects. In 2nd International Conference
on Advanced Reserach Methods and Analytics (CARMA 2018) (pp. 1-9). Editorial Universitat
Politècnica de València.
• Iyengar, A., Kundu, A., Sharma, U., & Zhang, P. (2018, July). A trusted healthcare data analytics
cloud platform. In 2018 IEEE 38th International Conference on Distributed Computing Systems
(ICDCS) (pp. 1238-1249). IEEE.
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