Data Analytics: Coding is Essential—Myth or Fact?
The demand for data-related skills is high among the requirements of today. Data is widely accepted for decision-making, while the questions regarding coding and becoming a data analyst arise among many would-be professionals: Must I learn to code for becoming a data analyst? While some seem to think data analytics is a domain purely for coding, others say coding is not a strong requirement for this field. So is it a myth or a validated fact? Let’s track down the answers.
Understanding Data Analytics
Data analytics include the entire cycle of collecting data, cleaning data, processing data, and interpreting data to derive some meaningful insights. This helps businesses in operations, understanding customer behavior, and predicting future trends. So coding might be a value addition here, but according to this widespread view, it would not be a must. In data analytics, various tools and techniques are used, of which some demand coding knowledge, while others set no requirement or have no/less coding options.
Role of Coding in Data Analytics
When Coding Is a Must
Nevertheless, whenever we think of working with advanced data analysis or automating some of the data analytic processes, perhaps it will always be in use. For instance, people who typically work with big datasets, machine learning models, or build their own custom analytics solutions will use:
- Python and R-The preferred languages for statistical analyses, data manipulation, and ML;
- SQL: A lot of time is spent querying databases and retrieving structured data;
- Scala & Java are used in big data platforms such as Apache Spark and Hadoop.
Consequently, programming is more required if you hope to occupy more of the technical job functions, such as a data scientist or data engineer; coding becomes an essential skills.
When Coding is Not Required
Most of the latest analytical tools today empower professionals to analyze data without writing a single line of code. User interfaces for data visualization, dashboards, and business intelligence simplify the entire data analytics process for professionals without a strong technical background.
Some popular no-code/low-code tools include:
- Microsoft Excel & Power BI: For data analysis, including pivot tables and dashboard visualization.
- Tableau & Looker: Both are strong visualization tools allowing users to create interactive reports.
- Google Data Studio: A free tool for creating data-heavy reports.
- Alteryx & KNIME: No-code platforms for automation of workflows and data processing.
Much of the work related to business intelligence, marketing analytics, or operational reporting jobs can, hence, be done without thorough knowledge of coding.
So, Do You Need Coding?
Coding is not compulsory for data analytics, which is a misconception. Yes, it may help to hone your skills and build opportunities, but coding isn’t a must-have for all data analytics jobs. There are a considerable number of professionals who have achieved success analyzing data using no-code tools, especially for business applications. A working knowledge of SQL and some basics of Python may just come in handy and help in working with the data with more ease. In the end, it all boils down to how one chooses to go about pursuing his or her objectives forward.
How SkillzRevo Can Help
Skillzrevo is a training institute that provides data analytics programs for technical as well as non-technical persons. The courses we provide will prepare you to strive hard in the domain, from SQL and Python-related courses to those relating to business intelligence tools, like Power BI and Tableau, with hands-on training, one-on-one mentoring, and relevant certification. Like NASSCOM Certificate to help you excel in the field.
So, whether you’re a beginner or an experienced professional, data analytics is a field where you can thrive—with or without coding!
