Data Analytics Skills for Technical Writers

Introduction

Writing is a basic skill that technical writers have strong expertise in. Technical writers weave their passion for technology into writing; they produce an invaluable artifact called product documentation. A technical writer has picked up skillsets in team management, stakeholder management, and project management. These skills help technical writers effectively deliver their roles and responsibilities. These skills help technical writers thrive in organizations where there is no cohesive approach to documentation and a lack of governance model.

If organizations have a customer support center, it makes technical writers indispensable to customer operations. Without technical writers producing and updating product documentation, chaos will reign!

Types of Data Analytics Skills for Technical Writers

Given the emergence of digital transformation projects and Artificial Intelligence (AI), technical writers need to upskill in data analytics and AI skills. Here are some of the data analytics skills

Data Management skills

Technical writers need to learn the basics of data management and become familiar with DAMA DMBoK frameworks that talk about data lifecycle. This helps technical writers learn about data fundamentals, data lineage, data security, data organization, and data engineering. Understanding data collection methodology is so important while building metrics from the data. Knowing the nuances and underlying assumptions helps technical writers build good metrics from the data and narrate the right story.

Technical writers collate data from a plethora of business systems such as Google Analytics, Google Search Console, CRM, product analytics tools, and so on. It is very important to create relationships between these data such that key events or unique identifiers are created. This helps with data linking leading to richer information. This information can be used to generate right insights that can be actioned. This also helps technical writers communicate clearly to internal stakeholders what data needs to be captured and its purpose.

Basic Data Analysis skills

Basic data analysis skills are required to undertake some analysis to mine good insights. This means that technical writers should learn about basic exploratory data analysis techniques such as correlation, head map, distribution, and so on. In addition to this, technical writers should know how to calculate mean, median, and so on. This assists technical writers in deriving metrics from data for reporting and insights generation purposes. These data skills elevate technical writers to the next level as they can measure and monitor the right metrics to improve the business impact of their efforts. Focus on learning these skills would help technical writers communicate metrics clearly to their decision-makers such as C-level executives

• Basic statistics including average, median, mode, and so on
• Hypotheses testing
• Correlation analysis
• Head map generation
• Distribution and histograms
• Charts

Data Privacy knowledge

Data security and data privacy are also essential skills for technical writers to comply with regulations such as GDPR, SOC 2, and so on. Understanding user consent and more importantly, using the data for the purposes it is collected for is mandatory training for many employees working in enterprises. Technical writers should be aware of data security techniques and data access policies of the organization. Given that technical writers collect data from many business systems, data must be secured accessed, and stored for wider dissemination of the metrics/insights. This helps technical writers maintain statutory requirements as part of their roles and responsibilities.

Also Read: Ideal Organizational Team Structure for Technical Writers

Upskilling

Technical writers should upskill themselves regularly to improve their data analytics skills. This includes attending workshops, training programs, conferences, and events. Data analytics improvement programs can teach a variety of techniques in data analysis including

• Data visualization

Data visualization is essential to produce intuitive and comprehensive charts that help to narrate a story better. This includes picking the right charts for the right data characteristics. Also, the usage of color themes matters to bring consistency across metrics and produce visually appealing charts

• Data analysis methods

Some advanced data analysis techniques such as causal analysis, hypothesis testing, A/B testing can be learnt. This helps technical writers to undertake complex analysis without needing to consult their internal capability teams

• Storytelling

Storytelling is a must-have skillset for technical writers. It helps to build a good narrative to explain what is happening in the documentation using data, and more importantly why it is happening. Then, technical writers can chart a course on what must be done through actionable insights

It is recommended that technical writers take up certification courses from trusted service providers such as Microsoft, Coursera, and so on. Certification provides credibility that the technical writer knows the subject matter. Upskilling also empowers technical writers to advance their careers into managerial roles for wider influence on business operations. Critical thinking powered by data analysis would boost the career prospective of technical writers to be hired.

Also read: Top 11 Tips for Technical Writing

Conclusion

It is important for technical writers to master data analytics skills that help them in data collection, data analysis, and storytelling. These data skills help technical writers to define the right metrics utilizing the right data. These metrics can help organizations continuously measure and monitor the business impact of the technical documentation team. In the ever-changing business environment, technical writers need to upskill for career development. Let’s learn and keep learning.

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