I have not published any article for more than 2 months.  It was extremely busy for the re-work on different project schedules and additional administrative work due to the coronavirus crisis.   For this time, I would like to share an article planned to published by the end of January 2020.  It’s about the coming trend for the hot items in Data Science.

I do believe that there are several big things for data science in the coming future.

1. Artificial Intelligence
2. Data to Action
3. Natural Language Processing
4. Data Security
5. Booming on IoT & Edge Computing

Artificial Intelligence (AI)

In the past few years, many AI experts are coming out in the market.  There is no point to discuss whether they are real experts.  With the continuous development of cloud services with AI features, it is easier for organizations to access AI features easily to apply on their business needs.  However, the biggest barrier for the AI application is still owing to lack of experts in the market.  Unfortunately, I am not an AI expert but been working in around 10 machine learning & deep learning projects with NLP and Computer Vision.  It is expected to have more exciting AI related projects with the 5G and IoT.

Data to Action (Automation)

After insights are being discovered, the next step is the automation for the results being applied to real-world applications.  There are more & more robot traders in the stock market and other applications.  To take an example, our team is building a robot for the wine industry for robotic investment advisory and trading.  It is expected to have more application like mobile App integrated with Big Data platform or working on Data Analytic results.  The digital age is always demanding for instant result and data related automation should be the answer.  So, the only question is which organization is doing better and faster in their own industries.

Natural Language Processing (NLP)

NLP is one of the key elements for the Customer Relationship Management today.  It is vital for every corporations to understand the feeling of their customers in order to meet the tough requirements of the customers in the highly competitive market.  Acquiring a new customer is cost extremely high and the churn is too painful for all business.  Customer retention is based on the continuous improvement in services with the help from Customer Profile 360 and other technology.  By now, the NLP is very matual in English and some European languages but it is expected the technical issues should be solved in the coming future on Asian languages like Cantonese.

Data Security

Once we are having more & more data in place for analysis, the data with value is the target of hackers to capture information especially personal data.  This is being more challenging with the growth of cloud services running different data science and/or Big data solutions.  Data is being exchanges across cloud(s) and on-premises servers.

There are different areas of data security protections, such as:

• Database / Big Data Encryption
• Network Encryption
• Row / Column level security
• Access Control on Sensitive data

This is an area expected to have significant growth in investments.

Booming of IoT & Edge Computing

In this year, it is a 5G year and 5G service is available in Hong Kong since April 2020.  With 5G, there are lots of new opportunities in terms of collecting new data and leading to further growth on IoT (Internet of Things) with more sensors and cameras being installed everywhere.  With the significance increase in the number data points, it is not feasible for every devices to connect to a cloud service at the same time.  Thus, some local pre-processing or summarization of data should be a must and leading to the increase in demand for edge computing.

Conclusion

I hope I can give you a general picture of my thought for the future development in the Data Science field.  Nevertheless, the crisis of Coronavirus in 2020 will cause significant uncertainties for the business environment.  The demand for new technology solution will be dropped and the growth for the data science is expected to be slow down.