如果说2018年因欧盟《通用数据保护条例》（GDPR）生效而被称为世界数据治理元年，那么2019年就是延续与反思之年。从美欧到中国，从立法到执法，全球数据治理格局呈现“不变中的变化”与“变化中的不变”。

Smart labels are becoming one of the most popular technologies across the retail, healthcare, and logistics sectors, among others, and are viewed as an ideal means to achieve greater efficiencies and profitability, while providing the authenticity of an item and its traceability from the warehouse to the distribution center throughout the supply chain. These labels are used as a tool to enable smart supply chains and are also playing a vital role in the marketing and advertising of consumer products, which can be achieved through the provision of product information, as well as the analysis of consumer buying patterns that can be accessed from the data collected by these labels. Cost cutting over the supply chain, to be closer to the nearest level of efficiency, by manufacturers, has been a critical factor that has augmented the demand and prompted the proactive adoption of these solutions to gain the first mover advantage in the individual end-user industry.

Predictive analytics offers companies actionable insights based on data. It delivers estimates about the likelihood of a future outcome. Companies are using these statistics to get a forecast of the future developments. Moreover, the foundation of predictive analytics is based on probabilities. Prescriptive analytics uses techniques and tools such as business rules, algorithms, machine learning (ML) and computational modelling procedures. This kind of technique is applied against input from many different data sets including historical and transactional data, real-time data feeds, and Big Data. The businesses and enterprises that are already using some sort of descriptive analytics tools and solutions are better positioned for predictive and /or prescriptive analytics solutions adoption. The presence of historical data to forecast from and run algorithms makes them use these solutions more effectively. The demand for business intelligence has been on the rise, in recent years, with enterprises and organizations planning to enhance productivity and increase sales by adopting automated solutions. Therefore, BI tools have witnessed a tremendous rise in its adoption across various industries around the world. Additionally, predictive and prescriptive analytics is helping in boosting the demand for business analytics among the BI professionals, as Big Data is becoming the focus of analytics processes that are being leveraged not only by the big enterprises, but also by the small and medium-sized businesses alike. Moreover, the development of better visualization tools, as well as incorporation of NLP and voice input capabilities have further added to use ease of use.

The advancements in information and communication technologies are forcing the educators and learners to move past the constraints of time, space, and environment. While traditional classroom education is well-known learning systems outside the classroom, especially those enhanced through technology, are still being discussed. Massive open online courses (MOOCs) represent the final stage in distance education, as these offer open educational resources to the students all around the world. MOOCs are designed to be scalable to large online masses, with free participation and without formal requirements to provide opportunity to learn through hundreds of public and private universities or organizations for millions of individuals around the world. However, since MOOCs became mainstream in 2012, their completion rates remain a highly debated subject, ranging from 0.7% to 52.1%, the median value being 12.6%. The first-generation MOOCs (cMOOCs) were connectivist, student-driven, chaotic, and open-ended. cMOOCs have continued throughout the years through examples, such as CCK08 (2008), PLENK2010 (2010), MobiMOOC (2011), etc. Unlike cMOOCs, xMOOCs or AI-Stanford-like courses are based on cognitive-behaviorist and social constructivism approaches and are web pages, in which the instructor provides video-based courses to a large number of learners.