Recently, the field of Data is increasingly being interested by many young people and wants to pursue their career path. However, there are many small areas related to Data that can be confusing: Data Science vs. Business Intelligence. Generally speaking, in order to interpret the situation accurately, two aspects should be considered: similarity and differences between data science and business intelligence. Prior to this article, most people think that "data science" and "business intelligence" are completely different roles. However, if you carefully analyze these different positions, it turns out that this view is not absolutely accurate! For example, some products use the technology of artificial intelligence-based data mining for mining raw data; In addition to the raw data storage platform without processing requirements (storage), a typical processing platform can only manage a single kind of work release experience management system; Other cloud applications may have greater functionality or integration options such as real time processing or mobile interface capabilities But by its nature, compared to traditional methods such as statistical analysis mathematical model analysis on large amounts of historical data It should be noted that due to its high computational requirements This type of application has nothing to do with traditional business intelligence (BI) platforms available today
Read more ...Direct marketing is welcomed by people when it makes sense.
Read more ...Diabetes is a disease that can affect anyone at any age, and is the leading cause of blindness, heart attack, kidney failure and stroke. In fact, over 400 million people worldwide have diabetes but as many as 46% remain completely undiagnosed and untreated. According to The World Health Organization, diabetes is a growing global health problem. In fact, diabetes accounts for 12% of the world’s health expenditure through the vast amount of research, analysis, and treatments, conducted and required today. The field of Artificial Intelligence (AI) and its applications such as Machine Learning (ML) are promising significant breakthroughs in diabetes care. Using data from our research, we focus on the role of social networks in a health system. We bring together people from all over the world to share their expertise and passions through our website, meetups, and conferences. Our community translates research into action, solving real-world problems faced by patients, care providers and caregivers
Read more ...If you think the best thing about social media marketing is how easy it is to get started, think again! The ability to connect with people on a truly personal level has opened up so many new doors for brands. But to be successful, that communication needs to be real. And that means being authentic, flexible and scalable – all of which are difficult when social media marketing first starts out.
Read more ...The use of Information Communication Technology (ICT) within marketing has swept the world.
Read more ...In this paper, we describe the concept of social business intelligence (SBI) in order to describe its scope and aim. The applicability of SBI was explained, followed by an outline of its benefits and drawbacks. Moreover, we discuss topics as the main component of a topic hierarchy and outline its challenges. Afterwards, we introduce a reference architecture for SBI that has been formulated based on the core concepts outlined above. We illustrate the utilization of our proposed architecture by describing two particular implementations specific to query performances and to our meta-star approach. Finally, some experimental results are presented for topic queries within our system as well as for various query executions performed with different volumes of textual data available for aggregation in a real context (Filipino auctioning sites).
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