Can one obtain knowledge of the great repositories of information and use this to improve business? How can one make use of this knowledge provided by Artificial Intelligence (AI) and automatic learning (machine learning) based on these technologies? What are the expected benefits and performance measurement issues related to Big Data in business? Is Big Data a mere hype or is it truly necessary? How does one measure the result in terms of return on investment? What about Small Data?
Confidentiality: Is it possible to work with data assuring both the security and the confidentiality of the data? It can be clearly seen that the use of learning algorithms permit a greater confidentiality of the original information, much more than with any other technology based on BI tools. Artificial Intelligence is able to work with curbed data which is impossible in BI because there comes a moment when the data are in plano.
Automation: Knowledge is automatically extracted from the sources of information, creating predictive models and self-adjusting to changing realities. The flow of knowledge coming from the data, not from the expert towards the data, empowers experts and brings about the possibility of automation.
- Business Knowledge Data Discovery and Deep Learning; a practical approach using “Big Data” Sub-title: Using the Data, Small and Big Data, for improving business.
- Business Artificial Intelligence, Neural Networks and Deep Learning using available “Big Data” It involves “training a computer system” to learn how to distinguish between different classes of information into grouped categories, providing results about the future that will help in business decision making.
a. Improving business through the construction of intelligent systems based on available “Big Data”
b. Develop a business system that takes user inputs about dislikes and likes to recommend new products to consumers (recommender systems)
c. FMCG: Automatic deciphering of patterns in consumer behavior taking advantage (of what?) to improve business decisions and practices.
Chief Information Officers (CIO), Chief Technology Officers (CTO), Senior Management in E-Business, Fraud and Risk Management Executives (in banks, telecommunications firms, insurance, etc.), Client Services Executives