With enterprises relying more on big data, jobs in data visualization are falling under the fastest-growing category. Here is a look at popular data visualization jobs and the skill sets needed to succeed in these jobs.
Find Jobs in data visualization. Source: Pexel
Data is the New Fuel!
Every business nowadays has lots of data and information within its data warehouses. However, without a way to comprehend the data, it becomes useless.
Therefore, the demand for jobs in data visualization is growing.
Let’s explore further the potentials of a data visualization career and see which job suits you most!
Why does every enterprise need data visualization? Source: Pexel
So first, why does every enterprise need data visualization?
Most people are not mathematically oriented and hardly see anything useful in raw data such as patterns, trends, and correlation.
Meanwhile, data is crucial in business and is used to map out marketing, sales, and consumer service.
A good representation of data enables decision-makers to keep track of the sales performance and understand complex insights, detect business patterns, and allowing them to make accurate decisions according to the facts and figures rather than subjective judgments.
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Why Should You Consider Jobs In Data Visualization?
Data Visualization Is A Great Career Choice.
Data visualization is a new buzzword in the tech world, with lucrative salaries and promising career advancement. All reports, dashboards that contain data in them need data visualization to understand the analytics. This includes text visualizations, scientific visualizations, etc. Thus, every company needs someone to make sense of this data.
Data Visualization Is Growing Due To Several Forces
The first one is data-driven journalism or DDJ.
DDJ is the future. It is a journalistic process using data to create compelling stories. Data visualization is used as a way to tell stories in news agencies/services. BBC and The New York Times have been embracing this news reporting style.
The second motive force is that web standards and applications such as Canvas, SVG, HTML5, WebGL have stimulated the development of data visualization tools. Nowadays, we can get access to powerful tools like D3.js, P5.js, and many others to facilitate heavy data-processing tasks.
The final driving force is the rise in cartography or map-making. This has long been an essential industry.
The geospatial domains witness more spatial data than ever is generated recently. Some tools that have popped up are Leaflet, Open Street Maps, CartoDB, Mapbox, Google Street Maps, and many many many others.
Data Visualization is growing due to several trends. Source: Pexel
Jobs In Data Visualization You Should Consider
Here are some jobs in data visualization we want to recommend to you:
Data Visualization Analyst
Demands for data visualization analysts are skyrocketing, and it has been considered the most sought-after career option in 2021.
Data visualization analysts use visualization tools and software to visualize data in a way that makes business reports easier to capture critical insights, such as performance and market trends.
You can be a data visualization specialist, but it is only a part of a data analyst or data scientist job. To be more specific, this is the daily task of a data visualization analyst:
- Manipulating and consolidating data sets to support analyses.
- Transforming data sets, quantitative and qualitative analysis into captivating graphics including presenting data in maps, charts, and graphs.
- Making large and complex data more accessible, coherent, and usable.
- Transforming, improving data accuracy, and integrating data, depending on the requirements
What Kind Of Business Needs Data Visualization Analysts Most?
- Banks
- Public sector organizations
- Specialist software development companies
- Telecommunications companies
- Consulting firms
- Social media agencies
Requirements
This role requires an independent self-starter with a strong affinity with numbers and quantitative data.
You typically need a degree relating to analytical skills, such as maths, statistics, and computer science, and a few data analyst apprenticeships to gain additional qualifications.
Employers usually seek those with 3+ years of experience in data visualization and skillful tools such as Tableau or Qlik.
Besides, the ideal candidates should be proficient in Access, Excel, SQL, and other data manipulation tools.
Strong analytical, organizational, interpersonal, verbal, and written communication skills are what recruiters seek in a potential applicant.
Last but not least, you should have the ability to prioritize numerous tasks under time pressure and changing priorities.
Average salary: $74,918
The chart below shows the Top 10 Highest Paying Cities in The US for Data Visualization Analyst Jobs according to Ziprecruiter.com.
Highest Paying Cities in The US for Data Visualization Analysts. Source: Ziprecruiter
Data Visualization Engineer
Data visualization engineer jobs are not purely technical; they have a strong design element and require visual communication skills.
Regardless of technology, successful data visualization engineers should understand design principles, both graphics and, more generally, user-centered. They should be able to:
- Design, develop, and maintain user-friendly data visualizations and dashboards using complex datasets from mixed inputs.
- Manage and integrate the various data sources and organize them into tables and views for optimal data analysis.
- Debug applications, trace code, find and fix bugs.
- Design, write and test analytics code.
- Implement the most relevant technology solutions to ensure UX-smooth and consistent dashboard designs.
Requirements
- Practical experience in analytics solution design, configuration, and reporting.
- Experience working with large, complex data sets.
- Experience in data analytics and statistics.
- Have a bachelor’s degree or Data governance/validation certificate.
- Experience in Data design and development, methodologies, tools, processes, and best practices.
- Ability to build dashboards and reports using Google Data Studio, Tableau, or other business intelligence and data visualization tools.
- Experience with Looker, Big query, SQL, Data Studio, GCP Data Flow, Tableau, R, Python, NiFi.
Average salary: $91K – $169K
Data Visualization Developer
In this position, you will collaborate with end-users and colleagues as a data analytics team to develop and implement collaborative solutions to data and analytics problems using Alteryx and Power BI tools.
You will be responsible for delivering effective data structures to enable data visualization solutions to support the data-driven decision-making process.
It is essential that you minimize downtime and keep data clean and healthy by aligning with the technical department and other related functions.
Data visualization developers are expected to have experience in front-end web development languages such as HTML5, ES6, TypeScript, JavaScript, and CSS.
Salary range: $50,000-$120,000
Requirements
- You should obtain a bachelor’s or Master’s degree in Computer Sciences, Business, Analytics, or a similar discipline; or an equivalent combination of demonstrated skills and experience.
- Employers highly value developers with 4+ years of professional experience and 2+ years of Alteryx experience.
- Developers should have the ability to compose complex SQL queries and understand data architecture.
What does a Data Visualization Developer do? Source: Pexel
Business Intelligence Analyst
Quick definition!
Business Intelligence (or BI) is one of the key spines for companies’ growth and success.
It is a technology-driven process that helps businesses convert the raw or unstructured data into knowledge delivered to the stakeholders to help them analyze and make appropriate decisions to optimize business performance.
Business Intelligence Analyst Career Path
Business intelligence analysts often move into higher-level jobs within 10 years. Here is the ideal career progression:
- Business intelligence lead
- Business intelligence manager: manage more resources or being responsible for more important projects.
- BI & Analytics Director: you are responsible for more systems and tools.
- The path can continue to VP, Chief Data Officer, Chief Analytics Officer, Chief Technology Officer.
Besides, obtaining an MBA can get you into a higher position.
Business intelligence helps the company in decision-making. Source: Pexel
A business intelligence analyst is a person who analyzes the data used by a business or the organization.
He or she is responsible for reviewing data to produce financial and market intelligence reports.
With the help of data analysis, data visualizations, and data modeling techniques, the BI analyst can identify patterns and trends that may influence a company’s operations and future goals.
Requirements
To become a good business intelligence analyst, equip yourself with several hard skills such as data modeling, programming, and statistics. Also, you are required to have a bachelor’s degree in business, computer science, economics, mathematics, accounting, or any other related field.
Roles And Responsibilities
- Keeps a check on customer data
- Performs data profiling
- Implements the practical data analysis techniques
- Create or research new data processing programs
- Review customer documents to audit data collection and utilization
Besides this, you need to have soft skills such as analytical thinking, strategic planning, and problem-solving. You need to understand the business in a big-picture view.
Factors That Help You Get Jobs In Data Visualization
Factors that help you get jobs in data visualization. Source: Pexel
You Enjoy Working With Numbers
Working with data requires two desired skills: knowing how to read statistics and telling a story with it. You should see data like a mystery or puzzle; and you want to solve it by applying your math skills.
You should enjoy and master mathematical fields such as linear algebra, calculus, statistics, and probability to do the modeling. They help you to understand the underlying behavior of the algorithm you are using.
While you can learn programming languages, do keep in mind that these languages evolve every few years, so you need to keep updating. However, you should have math skills initially as they are the foundation to expand to other technical fields.
We highly recommend you study the fundamental algorithms and math behind your preferred tools, such as Python. It’s almost impossible to work with data without a master’s degree if you do not possess a tech or data background.
There are three fundamental questions you should ask yourself. We believe that these questions can help you consider whether you are suitable for working with data, and you are likely to be asked in the job interview:
- What is your data visualization philosophy?
- What data visualization tools that you use?
- Tell me about a data visualization project that you are proud of?
Your answers can help you to choose new topics to learn about.
Fluent In Multiple Programming Languages
As you read above, knowing how to code is the crucial step on ”how to data visualization.”
For data visualization workers, SQL is the standard language to manipulate data.
Besides, there are other valuable options you can be proficient in:
- Python
- Spark, a fast, easy-to-use, and general engine for processing a huge data volume.
- Cloud-native and analytics platforms software. For instance: Looker, Tableau, and Microsoft Power BI.
- R: is essentially a programming language; it is used to analyze data and do statistical analysis. This language is becoming a preferred option among statisticians and data miners.
- Hadoop is designed to process a massive volume of data.
- Cloud data warehouses, such as Microsoft Azure, Amazon Redshift, Google BigQuery, Oracle Autonomous, and Snowflake
Data visualization engineers need to know how to code. Source: Pexel
Communication Skills Are Just As Crucial As Math Skills
Indeed, jobs in data visualization are technical-heavy. But analysts are also required to communicate the meanings of a project or even to pitch the project themselves.
Communication skills cover numerous components.
Do you have a design sense to visualize data in a meaningful manner? Can you explain smoothly with non-technical colleagues?
Coding can be pretty long, abstract, and complex. It can consume lots of time to digest if you don’t document it precisely and clearly.
Besides, other teammates do not have much time to investigate every line of your code. So it is essential that you explain well what you have done.
Many Daily Tasks Won’t Be Written In The Job Description
You may grasp an intuitive idea about jobs in data visualization, but what you imagine might look different from what you actually spend your time at the office.
While you need to get a significant knowledge of statistics and programming, you will usually spend lots of time cleaning real-world data before representing it.
Data cleaning includes:
- Detect clear errors that are poorly coded or exhibit transcription problems.
- Convert input data into a consistent and insightful format
A Constant Thirst For New Knowledge
Data science is constantly evolving, and there will be new algorithms to update every year. A curious attitude is what employers look for.
It’s impossible to know everything in the data science field, so a healthy, humble mixed with a self-starting curious attitude is the right combination.
Much of what you’ll do won’t be written in the job description. Source: Pexel
Sum Up
Data visualization has become so ingrained in our daily lives that we hardly notice it. From the weather maps to the audio levels, workout machines and alcohol fermentation, etc., these are all sneaky ways data visualization crept into our lives.
Today the barriers between us and visualizations are not as evident as it was 5 or 10 years ago when only a handful of people had the skills to do so. Any front-end or mobile engineer can now render a chart; any designer can sketch one.
Meanwhile, you should be aware of the details and choices before pursuing a career in visualization. We hope that this article has given you more insights into the data visualization potentials and prepared you for the career you choose!
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