Data analytics English - Tài liệu tham khảo | Đại học Hoa Sen

In the increasingly digital age, data has become a valuable asset and plays an important
role in making smart decisions. In the coming years, the field of data and data analysis
is forecast to continue to grow strongly and bring many new opportunities.
In fact, according to a survey by Forbes, the amount of data created worldwide will reach 175 zettabytes by 2025.
According to a few other statistics from Precedence Research, the global data analytics
market size is shown at 41.39 billion USD by 2022 and is expected to exceed about 346.33 billion USD by 2030.
These huge numbers can partly demonstrate the development trends of the Data
Analytics industry in the next 5 years
So the question is what opportunities will the development trend of Data Analytics
bring to businesses in the next 5 years:
1. Enhance data collection capabilities:
With the rise of internet-connected devices (Internet of Things - IoT), companies and
organizations can collect large amounts of data from different sources such as
machines, mobile devices, sensors ... This allows them to have a more comprehensive
view of their operations and thereby apply smart strategies to optimize performance.
Data Visualization - Data visualization is the process of representing complex data in
the form of images or graphs. Data visualization tools help display complex data in an
intuitive and easy-to-understand manner such as Google Data Studio, Tableu,
Infogram. Data visualization helps businesses understand and analyze data quickly and
easily, thereby making smart business decisions.
2. Using artificial intelligence (AI) in analysis:
AI has come a long way in processing and understanding different types of data.
Artificial intelligence can help organizations quickly and automatically analyze data,
thereby generating critical information to support decisions. Machine learning and
deep learning algorithms will also be widely applied to mine knowledge from data.
a. Machine Learning:
• ChatGPT: known as the smartest artificial intelligence in the world. This tool can
chat, fluently answer all the questions you ask about general knowledge, no matter
what the field is. According to statistics from Swiss Bank UBS, ChatGPT has 100
million users after only 2 months of launch.
ChatGPT's attraction to market trends in the coming years cannot be denied
Chatbot: Also One of the extremely prominent applications of Machine Learning is
Chatbot, which is used in a more personalized way based on the programming of each
different business to automatically answer questions and provide support. customers continuously.
Chatbot helps reduce customer waiting time and provides 24/7 service. (even if you're
a consultant but busy going to Blackpink's concert. Nice!!) Future
According to an article by Stanford University, in 2019, the number of articles on
machine learning and artificial intelligence increased 20 times compared to the
previous 20 years. That can predict the trend of Machinlearning in the next 5 years
In addition, I also know another application of AI is computer vision.
b. Computer Vision: Machine vision will further develop technologies for Image
recognition and analysis, Quality management, Security monitoring, Augmented reality (AR) and virtual reality (VR)
Tesla is a leading computer vision company that has made breakthroughs in the field of
autonomous driving and has almost made the idea of fully self-driving cars a reality.
This can be safer than letting people drive their own cars.
c. Process Optimization and Automation:
Workflow automation tools and software include:
Robotic Process Automation (RPA) Simulation optimization
. If in the past, manual work prevailed in production processes and sometimes
unnecessary errors were unavoidable, then in the present and future trends there will be
the help of AI in the production process. Process optimization and automation will
operate more efficiently and with greater accuracy based on scientific foundations.
3. Enhance security and data management:
With the collection and storage of large amounts of data, information security is an
extremely important issue. In the coming years, companies will focus on building
advanced security measures to protect customers' personal information and prevent cyber attacks.
1. Data security: With the collection and analysis of more and more data, information
security becomes a top issue. Companies and organizations will focus on building
superior security systems to ensure the safety of customer, employee and business data.
Using advanced technologies such as encryption, access control, continuous
monitoring and attack prevention will be a priority.
2. Comply with data management regulations: With the application of new
regulations such as GDPR (General Data Protection Regulation) in Europe or CCPA
(California Consumer Privacy Act) in the US, businesses must strictly comply
requirements for personal data management and protection. Data analytics will play a
key role in helping organizations comply with these regulations by identifying,
classifying and controlling personal data.
3. Risk monitoring and prevention: Data analytics can be used to monitor network
activity, detect unusual behavior and potential cyber attacks. By applying machine
learning and AI techniques, data analytics has the ability to analyze billions of data
points to identify potential risk patterns and deploy timely preventive measures.
4. Supply chain management: Data analytics can be applied in supply chain
management to optimize business operations. From tracking information about product
origins to optimizing storage, transportation and inventory management, data analytics
helps businesses capture important information and make decisions based on key data. corpse. 4. Real-time analytics:
The ability to analyze data in real time will become an increasingly higher priority.
Having the ability to monitor, detect and react quickly to new trends or unexpected events
helps businesses adjust their business strategies flexibly and effectively. In the field of
data analytics, real-time data analysis is becoming an important trend. This is the process
of analyzing data immediately as it is generated, allowing organizations and businesses
the ability to make decisions and take action in near real time. Here are some examples of
the importance of real-time data analytics:
1.Business Monitoring: Real-time data analytics allows companies to monitor
their business activities in a more effective way. By tracking continuous metrics and
information, such as daily revenue, number of products sold or customer interactions,
companies have the ability to quickly adapt to adjust business strategies.
2. Incident detection and event handling: With real-time data analysis, companies
have the ability to identify and detect problems immediately. For example, in the
industrial sector, monitoring parameters such as pressure, temperature or energy
consumption can help detect machinery failures and prevent adverse consequences from occurring.
3. Business Process Optimization: Real-time data analytics enables companies to
find opportunities to optimize their business processes. By continuously
monitoring and analyzing information, companies can identify inefficiencies in
their operations and take action to increase productivity or reduce costs.
4. Customer Interaction: Real-time data analytics allows companies to track and better
understand their customers. By collecting information from interactive channels such as
websites, social networks or email marketing, companies are able to come up with
personalized marketing strategies and interact with customers quickly and effectively. .
5. Integrate data from multiple sources:
In the future, integrating data from many different sources will become a popular trend.
Combining different data sources such as social data, geographic data and traffic data will
help create a comprehensive view of the business and social environment. The above are
just some general trends in data and analytics in the near future. The application of new
technologies to this sector will bring many new opportunities for businesses to accelerate
their growth and improve their performance.
a.Equipped with specialized knowledge of Business and Commerce: Apply well
academic knowledge of economic and commercial activities to modern trends to
meet the strict requirements of businesses and organizations.( Follow the media
for example VTV1, ... participate in workshops, ....)
b. Mastering technology: AI was born to help people move to other roles and
positions at work. In the future, knowledge about AI seems to become more
necessary, so understanding trends and learning how to use them is an ideal way
for students to adapt to the needs. labor market
• When AI is born and develops strongly, what do you need to equip yourself with?
• Dung will say: now I am proficient in basic skills such as office information
technology.... But in the next 5 years there will be AI or more developed technology, and ……..
c. Data management and analysis skills:
Understand and apply data analysis, exploit information from data to make smart
and business-oriented decisions, etc. To achieve those skills, students can refer to
and self-study. Practice through YouTube channels like Maz Hoc Data, Ha
Blogging - students who are not majors share extremely useful tips for learning
how to analyze and visualize data.
d. Logical thinking and problem solving skills: Learning through participating in
projects as well as workshops on business trends, etc.
Overall, data analytics will continue to grow in the coming years, bringing many new
opportunities for organizations to understand customers, optimize business operations
and make smart decisions. However, data security and management are also
indispensable factors to protect personal information and maintain customer trust.