Data Visualization: 8 Ways To Improve It In Singapore

In the past year, the world of data visualization has experienced an explosion in popularity.

With the rise of TikTok – and the subsequent data dump that came with it – people have found a whole new way to engage with data. Thanks to the interactive nature of TikTok, data has never been more accessible to the average person.

In fact, the platform’s popularity has made it the most used social media platform globally, according to Statista.

As a result, professionals in data visualization have enjoyed a steady increase in demand, with the job market experiencing a 24% growth in 2019.

But this increased demand has not come without challenges. As with any other professional field, gaining hands-on experience is the key to success in the data visualization job market.

Unfortunately, traditional schooling does not always provide adequate training for students seeking to break into this rewarding industry.

Therefore, many people are forced to seek out more learning opportunities on their own. Luckily, there are numerous proven ways to gain statistical knowledge, which this article will list.

• Take A Class

One of the most efficient ways to gain experience is to take a class. Even if you aren’t interested in pursuing a career in statistics, you can always take a peek into the field and see what it’s all about. The best part about taking a class is that you will most likely be introduced to various tools and concepts that you can then incorporate into your own work.

But even if you aren’t looking to pursue a career in statistics, these classes provide an excellent opportunity to learn more about data analytics and how to apply it to real-life problems.

• Join A Society

Being a member of a society is often considered the best way to learn, as it provides you with the opportunity to connect with accomplished professionals. When joining a society, you will typically be provided with access to various journals, publications, and other forms of content that you can then refer to as a resource. In return, societies typically offer their members a discount or even provide additional benefits (such as access to online libraries, career services, and scholarships) as an enticement to join.

In addition to providing you with the opportunity to learn more about data visualization, joining a society can also provide you with the opportunity to network and make contacts that can further your career.

• Earn Your Bachelor’s Degree Specialty In Statistics

Depending on what area of statistics you are interested in, you can tailor your studies to earn a bachelor’s degree. If you are looking to enter the field as a data analyst, for example, then you can gain entry with a bachelor’s degree in biostatistics. Once you graduate, you will then be qualified to take the Certified Data Analyst (CDA) exam from the American Association of Advertising Agencies (4A’s) or the Certified Statistical Analyst (CSA) exam from the American Statistical Association (ASA).

After successfully passing the exam, you will then be able to find employment as a data analyst in almost any field, including government, pharmaceuticals, and finance. In these areas, you will usually be required to have a mathematical background, along with strong programming skills.

• Understand The Data Collection Process

Data collection is an integral part of any study or project, as it provides the foundation for all future analyses. Without good-quality data, you cannot have meaningful analysis or conclusions. When it comes to gathering data for analysis, there are various methods and procedures that you need to follow, depending on the type of study you are conducting.

For example, if you are performing a clinical trial and you need to gather data from patients, then you will need to follow the proper protocols for recruitment and data collection. Without understanding these processes, you cannot claim you are an effective practitioner.

• Develop A Research Plan

When you have a specific research question in mind, you can develop a plan to address it. A research plan is simply a document that establishes the procedures you will use to collect data for your study.

There are four basic steps you will need to follow to develop a research plan:

• • identify your hypothesis,
  • devise a research question to test it,
  • create a plan for data collection, and
  • conduct a literature review to validate your hypothesis.

By following these steps, you will create a solid foundation for your research project, allowing you to better interpret and analyze the data you collect. You also need to ensure that you follow all proper ethics protocols when conducting your research.

• Learn How To Program

If you are looking to enter the field as a data analyst, programmer, or server administrator, then you will need to learn how to program. While there are many different programming languages, each one has its own unique syntax that you will need to learn.

Once you learn the basics, such as how to add, subtract, and compare numbers, you can begin to build useful applications and tools that can assist you in your work. Whether you are working on a budget computer game or analyzing Twitter data to track consumer sentiment, learning how to code can open a whole new world of opportunities that you didn’t previously consider.

Learning how to program will not only allow you to enter the field but can also provide you with extra income as a freelancer, independent contractor, or business owner. Popular programming languages include:

• • Python,
  • R, and
  • Java.

• Join A Society Of Analysts

If you are looking to enter the field as a statistics analyst or data scientist then you can join a society of analysts. These societies will provide you with various networking opportunities, as well as the opportunity to learn from experts in the field.

As a member of society, you can attend various meetings and conferences, where you can present and network with other professionals in the field. In most cases, you will be expected to pay an annual fee to join a society, as a way of acknowledging your commitment to continuing education and professional development.

• Reading Is Fundamental

One of the most important things you can do as a statistics student is to read. You must be able to read academic texts in order to be able to understand and analyze the data. While there are many free online resources available, you should also be considering purchasing books, as this will provide you with the opportunity to educate yourself on many different topics. By continually learning, you will ensure that you maintain your professional knowledge and skill set.

Each text you read will provide you with new information, allowing you to advance further down the path to mastering data visualization and analytics. It is important to note here that you should only consider purchasing books from reputable publishers, as a poorly produced or packaged book can severely hurt your educational experience and even damage your professional prospects.

Data Visualization: Why It Is One of The Top Data Skills For 2023

Flowing Data

As data becomes more accessible and less regulated, organizations can gain a competitive advantage by analyzing and visualizing large amounts of data. This can be used for marketing, sales, or operations.

Data visualization is the process of taking raw data and using software, algorithms, and design principles to develop an understandable picture of the data. The resulting image can then be used to easily convey complex information to multiple decision-makers. This forms the backbone of business analytics in the future.

Pro-Active Role

A data visualization specialist examines business data and identifies the information most relevant to the organization.

This will play a pivotal role in the analytics function, as they will analyze the data, look for patterns, and find the information that can most benefit the company. This proactive role forms a bridge between business and technology and empowers decision-makers to take a more active role in the future of their company.

Scalable

Data visualization is easy to learn and can be used to answer a wide range of questions. As businesses grow, so does the demand for data visualization specialists.

Even a small business with limited resources can have significant data sets that can be visualized and analyzed to gain useful information. A data visualization specialist with solid foundations in statistical analysis and data visualization can scale up or down as needs change. This makes them invaluable resources for any size organization.

5 Must-Have Data Visualization Skills

Data visualization is one of the most in-demand skills in today’s digital world. Businesses and organizations across all industries need someone who can create compelling and insightful data visualizations in order to better understand and present their data, products, and services to stakeholders.

What’s more, is that someone who is proficient in data visualization knows exactly what attributes make for a successful and in-demand employee.

If you’re looking for data visualization jobs, you’ve landed on the right page. Here are five essential data visualization skills that you need to have in order to be qualified for an in-demand job.

1. Skill In Data Exploration

Data exploration is the process of finding interesting data, identifying key insights, and identifying potential new questions and areas for further research. A data exploration strategist should be equipped with the tools and knowledge to efficiently identify key insights from large amounts of complex data that may exist in various forms (structured and unstructured).

A well-versed data exploration professional should be able to efficiently find, sort, and analyze data, as well as determine the best approach and the best tools for presenting their findings. In order to be able to do this, they should have a basic understanding of the following tools:

• Microsoft Excel
• R
• Tableau
• Power Query
• SQL

These tools, and others like them, provide knowledge workers with the ability to quickly and easily analyze vast amounts of data. Whether you’re digging into data to find a competitive advantage in your business or you need to better understand consumer behavior or perform market research, having access to these tools gives you the capability to explore any type of data you need.

2. Skill In Data Preparation

Data preparation is the process of taking raw data (such as numbers from surveys, statistics from trials, or even inferences from raw text documents) and transforming it into a presentable format so that it can be analyzed. When preparing data for analysis, there are three important things to keep in mind:

• The data should be in a compatible format
• The data should be clean – free of errors
• The data should be well-labeled

When transforming raw data into a presentable format, there are a variety of methods that you could use. For example, you could create charts, graphs, or maps from the data in order to show key trends and highlights. You could also perform more advanced analysis, such as finding correlations and establishing cause-and-effect relationships between variables.

If you use commercially available software to prepare your data, you should ensure that it meets the standards of the American Statistical Association (ASA) and other reputable statistical bodies.

This way, you can be sure that your data will be properly compiled and interpreted when it is finally analyzed. If you’re not sure exactly what standards the software you’re using is following, you should ask the developers of the software for help or look up the documentation for the software package.

3. Skill In Data Management

Data management is the process of creating and maintaining information systems that can be used to store, sort, and analyze data. This includes things like database management, document management, and email management. A data manager should be able to effectively work with clients to plan and carry out data-driven projects and understand exactly how different types of databases and software work together.

When interacting with clients, a data manager should be able to present information in a clear and concise manner, using the right language and the appropriate tools. Furthermore, they should be able to respond to inquiries quickly and accurately and be able to set up and maintain meetings and conferences with minimal assistance.

If you’re looking for a position that requires data management, make sure to check out the job descriptions for the following roles:

• Data Architect
• Data Analyst
• Data Exploration Analyst
• Data Mining Analyst
• Operations Research Analyst
• Pricing Analyst

Each of these positions requires a particular blend of technical skills and domain knowledge, as well as the ability to effectively communicate with people from diverse backgrounds.

4. Skill In Data Analysis

Data analysis is the process of taking raw data and using statistics and math formulas to uncover patterns, make predictions, and derive conclusions. A data analyst should have expertise in a variety of statistical packages, including but not limited to:

• Microsoft Excel
• SQL
• R
• Tableau
• Power Query

A data analyst should be able to perform common statistical tasks, such as mean calculation, mode identification, and distribution fitting. Furthermore, they should be able to create analytical databases and perform complex analyses on large sets of data. In order to be able to do this, they should have a good understanding of the following concepts:

• Significance testing
• Hypothesis testing
• Basic Regression Analysis
• Time Series Analysis
• Correlation Analysis
• Cause-and-effect Analysis
• Panel Data Analysis
• Survival Analysis
• Markov Chain Analysis
• Network Analysis
• Bayesian Analysis

If you’re looking for jobs that require data analysis, make sure to check out the job descriptions for the following positions:

• Data Manager
• Data Scientist
• Operations Research Analyst
• Pricing Analyst
• Statistician (Advanced)

Each of these positions requires a particular blend of technical skills and domain knowledge, as well as the ability to effectively communicate with people from diverse backgrounds.

5. Skill In Presentation

Presentation is the process of structuring information for human comprehension. A good presentation should be concise, contain no spelling errors, and be equipped with visual aids and contextual information as necessary. The most effective presentations are those that use interactive methods such as whiteboards, flip charts, and visual tools such as PowerPoint and Prezi.

A good presenter should be able to guide a conversation by presenting relevant information in a clear and concise manner, using graphs, charts, and diagrams where appropriate. Furthermore, they should be able to engage with their audience by using eye-catching headings, subheadings, and bullet points. When structuring information for human comprehension, there are three important things to keep in mind:

• Use concise language
• Make the language relevant
• Present the information clearly

These three items will help establish a pattern of behavior for the audience, making you memorable and ensuring that they understand and retain what they’ve heard. Think of the perfect (albeit quick) summary of an important point you made during a presentation:

“X is the best because of Y, Z, and V.”

“A vs B: A is better because B uses a different technology and has additional features.”

“The data shows that blah blah blah.”

You get the idea. The point is that you want the person reading or listening to your summary to remember what they’ve just heard – and for the information to still be relevant later on.

If you want to be able to do this, you need to practice presenting information in different ways, using different mediums, and checking your work. You should also be prepared to give some thought to the language you use, ensuring that it is appropriate for the situation at hand. With a little effort, anyone can become a good presenter.

If you’re looking for a position that requires presentation, make sure to check out the job descriptions for the following roles:

• Product Manager
• Sales Manager
• Business Analyst
• Operations Supervisor
• Financial Analyst
• HR Generalist
• Project Manager

Each of these positions requires a particular blend of technical skills and domain knowledge, as well as the ability to effectively communicate with people from diverse backgrounds.