MIS – 3030 Business Technologies Social Media & Conversation Big Data

Social Media Social media are computer-mediated tools that allow people to create, share or exchange information, ideas, and pictures/videos in virtual communities and networks. Social media is defined as "a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of user-generated content." Furthermore, social media depend on mobile and web-based technologies to create highly interactive platforms through which individuals and communities share, co-create, discuss, and modify user-generated content. They introduce substantial and pervasive changes to communication between businesses, organizations, communities, and individuals.These changes are the focus of the emerging field of technoself studies.

Technoself Technoself studies, commonly referred to as TSS, is an emerging, interdisciplinary domain of scholarly research dealing with all aspects of human identity in a technological society focusing on the changing nature of relationships between the human and technology. As new and constantly changing experiences of human identity emerge due to constant technological change, technoself studies seeks to map and analyze these mutually influential developments with a focus on identity, rather than technical developments. Therefore, the self is a key concept of TSS. The term "technoself” broadly denotes evolving human identity as a result of the adoption of new technology, while avoiding ideological or philosophical biases inherent in other related terms including cyborg, posthuman, transhuman, techno-human..

Conversation Prism

Business Impact/Implications 1. Americans spend most of their time online on social network and blogs 2. Seventy percent of active online adult social networkers shop online 3. Fifty-three percent of active adult social networkers follow a brand—only 32 percent follow a celebrity 4. Sixty percent of social media users create reviews of products or services 5. The number of mobile Internet users is up 47 percent from last year

New Business Horizons Big Data

Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. The term often refers simply to the use of predictive analytics or other certain advanced methods to extract value from data, and seldom to a particular size of data set.

Big Data Characteristics ¤ Volume – The quantity of data that is generated is very important in this context. It is the size of the data which determines the value and potential of the data under consideration and whether it can actually be considered Big Data or not. The name ‘Big Data’ itself contains a term which is related to size and hence the characteristic. ¤ Variety - The next aspect of Big Data is its variety. This means that the category to which Big Data belongs to is also a very essential fact that needs to be known by the data analysts. This helps the people, who are closely analyzing the data and are associated with it, to effectively use the data to their advantage and thus upholding the importance of the Big Data. ¤ Velocity - The term ‘velocity’ in the context refers to the speed of generation of data or how fast the data is generated and processed to meet the demands and the challenges which lie ahead in the path of growth and development.

Big Data Characteristics ¤ Variability - This is a factor which can be a problem for those who analyze the data. This refers to the inconsistency which can be shown by the data at times, thus hampering the process of being able to handle and manage the data effectively. ¤ Veracity - The quality of the data being captured can vary greatly. Accuracy of analysis depends on the veracity of the source data. ¤ Complexity - Data management can become a very complex process, especially when large volumes of data come from multiple sources. These data need to be linked, connected and correlated in order to be able to grasp the information that is supposed to be conveyed by these data. This situation, is therefore, termed as the ‘complexity’ of Big Data.

Big Data Opportunities ¤ Data Mining - the computational process of discovering patterns in large data sets ¤ Data Visualization - the creation and study of the visual representation of data ¤ Predictive Analytics -analyze current and historical facts to make predictions about future ¤ Data Scientist - integrate big data technology into both IT departments and business functions ¤ Data Architect - define how the data will be stored, consumed, integrated and managed