Data analytics is currently one of the sectors experiencing the fastest growth. As the amount of information on the internet grows, so does the volume of data being transferred across it, necessitating the services of highly skilled individuals. A field that helps companies worldwide solve their problems by identifying the underlying causes and data patterns utilizing various data analysis methods, such as quantitative and statistical models. If you still need a foundation in data, you can pick up the necessary skills from Data Analytics Courses in Hong Kong.
What is Data Analytics?
Before going ahead with what are the different Data Analytics Courses in Hong Kong, let’s first understand Data Analytics. Analyzing raw data to find patterns and offer solutions is the definition of data analytics, which covers a wide range of topics. However, it comprises a variety of tactics with a variety of goals.
The data analytics process only requires a few stages to handle multiple projects. By combining these factors, a smart data analytics application will show you clearly where you are, where you have been, and where you should go.
Is There a Distinction Between Data Science and Data Analytics?
“Data science” and “data analytics” are often used interchangeably. However, they represent two distinct fields and two distinct professional paths. Additionally, they all affect the company or organization exceptionally differently. Data scientists and analysts differ greatly in two key ways: their actions with the data and the outcomes they produce.
A data analyst will try to address specific problems that have been identified and are well-known inside the organization. They achieve this by looking for trends and patterns in huge databases. Dashboards, graphs, and charts are used to “visualize” the findings after that. On the other hand, a data scientist considers the questions the business should or could be asking.
They construct algorithms, create prediction models, create new data modeling techniques, and do specialized analyses. For instance, they may create a machine to use a dataset and automate particular tasks depending on that data; they would then, through continuous testing and monitoring, improve and optimize that machine as much as possible as new patterns and trends emerge.
In summary, data scientists design tools to automate and optimize the organization’s overall operation, whereas data analysts focus on specific problems regarding data and solve them frequently upon request. This results in insights that other stakeholders can act upon.
Another important difference is the equipment and skills required for each activity. Employers prefer data analysts who are proficient with the Excel program and, occasionally, with programming and querying languages like Python, R, SAS, and SQL. Analysts must be at ease with these tools and languages to perform data mining, statistical analysis, database management, and reporting.
On the other hand, data scientists might need to know Hadoop, Java, Python, machine learning, and object-oriented programming in addition to software development, data mining, and data analysis. Despite their differences, it’s critical to understand how data science and data analytics complement one another and how both significantly impact business.
You can read more about the distinctions between a data scientist and a data analyst in this guide, and we’ll go into more detail regarding the data analyst role in section three.
What Are the Types of Different Data Analytics?
Before delving into the hunt for Data Analytics Courses in Hong Kong, you must have an overview of the types of data analytics. In a word, analytics is the process of turning data into knowledge to improve decision-making. Data analytics aims to obtain actionable insights that lead to wiser decisions and improved business outcomes.
Therefore, a data warehouse or Business Intelligence (BI) architecture that offers a flexible, multifaceted analytical ecosystem geared for quick ingestion and analysis of extensive and varied data sets is essential to design and build.
The different types of Data Analytics are:-
- Predictive (forecasting)
- Descriptive (business intelligence and data mining)
- Prescriptive (optimization and simulation)
- Diagnostic analytics
1. Predictive Analytics: Predictive analytics transforms data into valuable, practical knowledge. Data is used in predictive analytics to calculate the likelihood of a disease developing or the anticipated outcome of an event. Predictive analytics uses several statistical approaches to anticipate future events, from modeling to machine learning, data mining, and game theory. The following methods are employed in predictive analytics:
- Linear Regression
- Time Series Analysis and Forecasting
- Data Mining
There are three fundamental cornerstones of predictive analytics:
- Predictive Modeling
- Decision Analysis and Optimization
- Transaction profiling
2. Descriptive Analytics: Descriptive Analytics examines data and analyses prior events to understand how to approach future events. Analyzing historical data examines previous performance and calculations performed to determine what caused past success or failure. This analysis is used in almost all management reporting, including sales, marketing, operations, and finance.
For example, the descriptive model quantifies relationships in data to categorize consumers or prospects into groups. Descriptive analytics uncovers a variety of interactions between the client and the product, in contrast to predictive models that concentrate on forecasting the behavior of a specific customer.
- Data Queries
- Descriptive Statistics
- Data dashboard
3. Prescriptive Analytics: To produce a prediction, prescriptive analytics automatically combines extensive data, mathematical science, business rules, and machine learning. They then propose a choice alternative to capitalize on the prediction. Prescriptive analytics goes beyond forecasting outcomes by recommending actions that will benefit from the forecasts and outlining the implications of each decision option for the decision maker, in addition to predicting what will happen and when prescriptive analytics also considers why it will happen.
Additionally, prescriptive analytics can recommend options to seize a future opportunity or lessen a future risk and explain each option’s implications. Prescriptive analytics, for instance, can improve strategic planning in the healthcare industry by utilizing analytics to harness operational and usage data mixed with external data.
4. Diagnostic Analytics: In this study, historical data is typically preferred over other data to provide an answer or resolve a query. We look for any dependencies and patterns in the past data related to the specific issue. For instance, businesses employ this analysis since it provides excellent insight into a problem. They also maintain extensive information about their disposal because otherwise, data collecting could be time-consuming and individual for each issue.
The following are typical methods for diagnostic analytics:
- Data Mining
- Data Discovery
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The Top 5 Data Analytics Courses in Hong Kong are:-
Rank #1. Data Analysis Courses in Hong Kong
Take unique IBM-sponsored Data Analytics Courses in Hong Kong to advance your data analysis profession. The instructor for this course is a renowned authority in applying data to address practical issues. This data analyst course covers Tableau, Python, Hadoop, Spark, and R tools.
According to the Forrester Wave survey conducted in September 2018, IBM was recognized as the second-largest global provider of machine learning and predictive analytics solutions. This data analyst course aims to give students the tools they need to succeed as analysts and problem solvers.
One of the top cloud platform providers in the world, IBM is headquartered in Armonk, Hong Kong. In addition to holding ten inductions into the U.S. Inventors Hall of Fame, IBM is a technology innovator and a market leader in consulting services.
What can you anticipate from this IBM-developed data analyst course?
First, students will receive certifications from IBM and Simplilearn after completing these Data Analytics Courses in Hong Kong. The certifications will serve as proof of your expertise in data analysis. Additionally, you will have constant access to IBM cloud platforms that house various technologies in addition to IBM Watson.
Industry-recognized Simplilearn Master’s degree in data analysis. What more can you anticipate from the IBM and Simplilearn-created Data Analyst program? Once you have finished your Data Analytics Courses in Hong Kong, IBM and Simplilearn will award you a certificate of completion.
You’ll be on the fast track to success after you receive your certificate proving that you passed the Data Analytics Courses in Hong Kong offered by Simplilearn. In addition, if you complete the course, you will also have these things with you:
- Access to IBM cloud systems that include software such as IBM Watson.
- Simplilearn’s industry-recognized Master’s degree in Data Analyst.
- IBM cloud credits of USD 1200 are available for you to use for practical experience.
- What are the goals of this program?
By taking the IBM-sponsored data analyst course, you can enhance your knowledge and analytical abilities. Data extraction, regression analysis, data blending, descriptive and inferential statistics, hypothesis testing, and forecasting are all topics covered in this Hong Kong data analyst course.
With the aid of this course, you can quickly become an expert in data analytics if you have a basic comprehension of mathematical concepts.
Rank #2. Data Analysis Courses in Hong Kong
Data extraction, regression analysis, data blending, descriptive and inferential statistics, hypothesis testing, and forecasting are all topics covered in their Data Analytics courses in Hong Kong. Experience or academic background is optional to prepare for a new job in the rapidly expanding field of data analytics.
However, you will receive specialized training created by Google and have the chance to network with leading employers. With a $74,000 median entry-level income, there are 380,000 data analytics job openings in the United States. The process of gathering, transforming, and organizing data to make inferences, forecasts, and guiding well-informed decisions is known as data analytics.
Learn in-demand skills to help you land an entry-level job throughout eight courses. You’ll gain knowledge from Google employees whose careers in data analytics started with solid foundations. You can finish this program within six months if you work at least ten hours weekly.
You’ll get ready for careers such as database administrator, junior or associate data analyst, and more. After earning the certificate, you can apply for positions directly with Google and more than 150 U.S. companies, such as Walmart, Best Buy, and Astreya.
- What’s unique about this program?
With the help of this program’s more than 180 hours of instruction and hundreds of practice-based tests, you’ll be able to practice the real-world data analytics situations essential for professional success. Highly interactive, only Google workers with extensive data analytics knowledge created the content.
In addition, you will learn about analysis tools and platforms and the essential analytical abilities needed for an entry-level position through videos, exams, and hands-on laboratories.
- Data cleaning, problem-solving, critical thinking, data ethics, and data visualization are skills you’ll learn.
- You will gain knowledge of platforms and tools like presentations, spreadsheets, SQL, Tableau, and R programming.
- You’ll complete a case study that you can share with potential employers to highlight your new skill set, expert training, and practical assignments. Acquire valuable skills that top employers are currently looking for.
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Rank #3. Data Analysis Courses in Hong Kong
3. Hong Kong Baptist University
While checking out for Data Analytics Courses in Hong Kong, you can check out the Master of Science (MSc) in Data Analytics and Artificial Intelligence (Approved Programme under UGC’s Targeted TPg Programmes Fellowships Scheme). The curriculum offers three topics for advanced information systems and focuses on the theories and practices of information systems (namely, Data Analytics, Artificial Intelligence, and Intelligent Information Systems).
Students learn solid concepts and gain hands-on skills in these themes to apply these concepts and skills to solve real-world information system problems. On completion of this program, you will be able to achieve the following program-intended learning outcomes (PILOs):-
- You will become adept with the fundamental ideas and techniques of intelligent information systems, artificial intelligence, and data analytics.
- You will Apply data analytics, AI, intelligent information systems, and related technologies to applications and problem-solving.
- Describe the business needs and the methods for converting them into information systems using data analytics, artificial intelligence, and other relevant technologies.
Rank #4. Data Analysis Courses in Hong Kong
4. Intellipat Data Analytics Course
While looking for Data Analytics Courses in Hong Kong, you can get the upper hand in data analytics with this Intellipaat and CCE, IIT Madras training program. You will learn business domain knowledge, data transformation, storytelling, how to use algorithms to solve complex business challenges, optimization strategies, data science project execution strategy, and data visualization in these online data analytics courses.
What can you expect from this course?
- Excel for Data Analysis in Microsoft
- Analysis of Data Using SQL
- Introduction to Statistics and Data Science
- Presto (SQL Query Interface) (SQL Query Interface)
- Data Science, Project Life Cycles, and Data Analysis in practice.
- Techniques for project rollout, experimentation, and evaluation.
- Business case studies with Power BI
- Approaches for Machine Learning
- The Capstone Project in Data Science
- Non-IT professionals work in finance, marketing, sales, and human resources.
- BI Specialists
- Data Analytics Specialists
- Project Directors
- Software Professionals
- Architects of Information
- Undergraduates and Recent Graduates CanApply For The Course
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Rank #5. Data Analysis Courses in Hong Kong
5. Data Analytics Courses from Edx
While checking out Data Analytics Courses in Hong Kong online, you can learn data analysis through online courses and obtain a data analysis credential. Of course, data analysis classes will differ depending on the provider’s objectives, the industry they are targeting, and other elements. However, at Edx, they push students to anticipate learning fundamental knowledge like:
- The Entire Data Analysis Process, Including Data Collecting and Distribution of the Main Conclusions.
- Data Sources, File Types, and Data Structures.
- Instruments for collecting, managing, mining, and interpreting data
- Data Visualisation to Communicate Insights from Data Analysis to Stakeholders.
The usage of particular data analysis tools is also necessary for aspiring data analysts, and this can be taught through various courses. Start by using the following essential data analysis tools: Microsoft Excel: spreadsheet software that allows you to collect, clean, organize, and analyze data sets.
An advanced data analysis course can also be an option for those with a focus. For instance, a comprehensive data analysis course can equip analysts with the skills to understand sizable, varied data sets to support wiser business decisions.
A student might also be drawn to a particular field of data analysis, like bioinformatics, which focuses on interpreting biological data for scientific endeavors like medical research. Many data analysis courses are devoted to this field of study and other specializations.
Why is Data Analytics important?
Business-to-consumer applications require data analytics (B2C). Organizations compile information gleaned through their consumers, enterprises, economy, and experience. Following the data collection, it is processed, classified according to the needs, and then analyzed to examine purchase trends, among other things.
The goal is to understand your data, analyze it, and share improved company possibilities for the near future. The best way to do this is by using analytics techniques. In data science, trends, patterns, and relevant information are extracted from existing data that would only be useful with analysis.
It is a type of business intelligence that is now applied to increasing earnings and improving resource utilization. Additionally, this might enhance managerial processes and propel organizations to new heights. If not correctly analyzed, this data will be squandered. Still, properly diagnosed can help us uncover the potent enough knowledge to change how business is currently operating or is going.
Consider a source of information that has been released; you still need to delve in to grasp it. With the data, your company can use it as a competitive advantage and achieve great things. This will draw out information that will give a company or organization a competitive edge in the market. Data and information are increasing, and the information we will have access to shortly will be unforeseeable.
FAQs About Data Analytics Courses in Hong Kong
1. What is Big Data Analytics?
The often challenging process of analyzing large amounts of data to find information might assist businesses in making wise decisions about their operations, such as hidden patterns, correlations, and markets. Big data analytics includes customer preferences and trends. Organizations can use data analytics technologies and procedures to examine data sets and discover new insights. Business intelligence (BI) queries answer fundamental questions about the operation and performance of businesses. Big data analytics is a subset of advanced analytics, incorporating features like predictive models, statistical algorithms, and what-if analysis supported by analytics tools.
2. Why start a career in the field of Data Analytics?
Taking any of these Data Analytics Courses in Hong Kong will boost your career. Businesses of all sizes repurpose themselves for the internet marketplace. Therefore, adopting big data is the top goal of the company, opening doors for growth in telecommunications, banking and insurance, healthcare, and other industries. Improved marketing, B2B market connections, and coordinated operations and manufacturing were all part of the transition. The future of big data analytics is significantly brighter because of the constantly changing data and its fruitful results. The need for more individuals with the necessary skill set: Despite the industry booming with data analytics job profiles, there is a substantial talent gap between available data analysts and qualified individuals.
3. What are the programming languages required for Data Analytics?
There are many different programming languages available, but if you’re just getting started and have your heart set on being a data analyst, it is recommended to learn Python and SQL. Additionally, you will learn Python and SQL as part of the Data Analyst Career Path to provide you with the tools you need to succeed in entry-level employment. Finally, consider learning R if you are already comfortable with Python for data analysis. Naturally, you can learn more languages and libraries to expand your knowledge, but it’s a good idea to start with the fundamentals and become familiar with these three.
4. What is the average salary of a Data Analyst?
The amount of experience is one of the main variables affecting your pay. You may anticipate making more money as a data analyst the longer you work in the field. According to Glassdoor, the experience might affect your data analyst salary: Senior Data Analyst: 2 to 4 years: $98,682, Senior Data Analyst IV: 5 to 7 years: $112,593, and Principal Data Analyst: 8+ years: $138,031. In addition, your earning potential can increase even more if you take a leadership position. According to Glassdoor, analytics directors make $180,392 a year, while analytics managers make an average of $129,076.
5. What are the different types of Data Analytic tools?
It doesn’t matter which course you choose; Data Analytics Courses in Hong Kong: will assist you with the expertise in several tools a data analyst needs. However, you’ll need to be skilled in at least some of the tools listed below if you want to work as a data analyst. Using formulae in a spreadsheet, Microsoft Excel is a software that lets you arrange, format, and calculate data. Data analysts may use Microsoft Excel to run basic queries and create pivot tables, graphs, and charts.
Excel comes with a macro programming language called Visual Basic for Applications (VBA). The popular data analytics and business intelligence program Tableau is primarily used as a tool for data visualization. Tableau helps analysts visualize raw data in dashboards, workbooks, maps, and charts. By making the data more understandable and accessible, data analysts can communicate their findings and suggestions better.
A command-driven software program called SAS performs sophisticated statistical analysis and data visualization. A software program called RapidMiner is used for text mining, machine learning, predictive analytics, and data mining (finding patterns). With the help of the business analytics tool Power BI, you can share insights throughout your organization and display your data.
The discipline of data analysis is expanding every day. Data analysis is used by all firms, which is why this position pays quite well. This field has enormous potential because it requires significantly fewer workers than there are now on the market. Enrolling in online or offline Data Analytics Courses in Hong Kong can open the door to a prosperous and bright future. The course is also becoming increasingly popular among working people because it can be completed online and helps their careers.