The 5 Must-Have Data Skills
for 21st-Century Workers

Ever since the dawn of the information age and the rise of the internet, companies of all types have rushed toward digitization. In the process, they've reinvented the ways that they did business and retrained their workforces to support those new workflows. The result was a drastic increase in efficiency and, in many cases, profitability. As it turns out, though, that wasn't the most important consequence of the shift.

Instead, the most important outcome for most companies was a dramatic increase in the types and quantities of data they began to accumulate. That data has enabled a new analytics revolution that's remaking the economies of the 21st century – leading to business leaders declaring that data is the new currency.

The question for businesses now is how best to spend that currency.

Although the answer for individual companies varies, there's one thing that does not. It's the fact that to place data at the heart of everything they do, businesses need employees with the right data skills to handle, interpret, and safeguard data. That makes data skills among the most critical for job-hunters and career-builders to master. To help them do that, here are the five must-have data skills for every worker in the 21st century.

1. Data Extraction and Preparation

   Since data has become such a critical commodity for businesses, one of the most important data skills that workers of all kinds should develop is data extraction and preparation. It's a skill set that allows workers to identify valuable data as they encounter it in their daily work and to preserve it or enter it into an appropriate database in a usable format. This process is often part of a broader workflow known as extract, transform, and load (ETL).

   In the realm of business, the ability to access and analyze relevant data is paramount for informed decision-making and strategic planning. Companies rely on data to gain insights into market trends, customer behaviours, and industry competition. Understanding how to acquire relevant data using various techniques, for example, is crucial for enhancing marketing efforts and broadening outreach.

   To support that process, it's beneficial for workers to gain familiarity with the following types of technologies and workflows:

   • Spreadsheet Software (like Microsoft Excel or Google Sheets): This includes entering data accurately, categorizing it effectively using functions and formulas, cleaning data (removing duplicates, correcting errors), and exporting it into standard formats like comma-separated value (CSV) files for use in other data applications.

   • Database Query Languages (like SQL): Understanding common SQL query structures (SELECT, FROM, WHERE, JOIN) allows users to retrieve specific information from relational databases, which store vast amounts of business data.

   • Scripting Languages (Optional but beneficial): For more advanced data manipulation or automation, an understanding of common scripting languages like Python (with libraries such as Pandas) or R can be highly desirable, making data handling skills broadly applicable across different platforms and tasks.

   Mastering product data syndication processes is also essential in certain sectors, ensuring consistent and accurate product information is distributed across multiple online channels, making it a critical skill for data professionals in e-commerce and retail environments.

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2. Trend Identification and Basic Analysis

   Within most businesses, complex, high-level data analysis is typically the domain of specialized data scientists or analysts. However, this doesn't mean that other employees can't perform valuable work by identifying basic trends and patterns within the data relevant to their roles. Developing the ability to carry out fundamental trend identification is therefore another must-have data skill.

   Here again, common tools like spreadsheet software (Excel, Google Sheets) are key starting points. Excel, for example, has a good mix of built-in trend analysis tools (like creating charts, adding trendlines, using basic statistical functions) that provide an excellent foundation for learning. These tools cater to a wide range of users, allowing even novices to begin exploring data visually and identifying simple patterns, while remaining useful for more advanced analysis. Understanding how to spot upward or downward trends, seasonal variations, or outliers in sales figures, customer feedback, or operational metrics can provide valuable insights for improving performance or flagging potential issues within one's area of responsibility.

3. Data Visualization

   Part of the reason data has become so valuable is its potential to inform decision-making that drives results. However, raw data is often difficult to interpret. The biggest hurdle many organizations face in embracing data-driven decision-making is presenting data and its conclusions in a clear, digestible format that stakeholders can quickly understand and act upon. This makes skills in data visualization – turning numbers into meaningful charts, graphs, and dashboards – among the most valuable data skills workers can possess.

   The good news is that there are common data visualization tools and platforms used across many businesses, allowing workers to develop relevant skills. Since many rely on similar principles (selecting appropriate chart types, labeling axes clearly, using color effectively), learning one tool often builds transferable skills. Some widely used tools include:

   • Tableau: A very popular and powerful platform known for its user-friendly interface that allows creating interactive dashboards without extensive programming knowledge. Public versions are often available for learning.

   • Microsoft Power BI: Another leading business intelligence tool, particularly strong within the Microsoft ecosystem, used for creating reports and dashboards from various data sources.

   • Google Charts / Looker Studio: Google offers tools ranging from simple chart creation libraries for web developers to more comprehensive business intelligence platforms (Looker Studio, formerly Data Studio) that integrate well with other Google services.

   • Spreadsheet Software: Excel and Google Sheets also offer robust charting capabilities suitable for many basic and intermediate visualization needs.

   Developing the ability to choose the right visualization for the data and the message, and creating clear, uncluttered visuals, is key to communicating insights effectively.

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4. Website Analytics Fundamentals

   One primary reason businesses have access to so much data today is the ubiquity of websites and digital platforms. Nearly every business, regardless of industry, has an online presence. These websites generate vast amounts of useful data every time a customer or potential customer visits – tracking page views, click-through rates, time spent on site, conversion paths, traffic sources, and much more. Understanding the basics of website analytics is therefore an increasingly essential skill for many roles, not just dedicated marketers. Key concepts include sessions, users, bounce rate and conversion rate.

   This skill set is particularly valuable because it intersects with several key business functions, including sales, marketing, customer service, and overall business intelligence. Workers who possess a solid grasp of fundamental web analytics concepts (like sessions, users, bounce rate, conversion rate) and familiarity with common tools (like Google Analytics) can better understand customer behavior online, measure the effectiveness of digital initiatives, and contribute to data-informed decisions. This knowledge can provide a significant advantage for career advancement across various industries, transforming what was once a niche technical skill into a broadly valuable competency.

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5. Data Security Awareness

   If data is the new currency, then protecting it is paramount. Businesses face significant risks if their data is lost, stolen, or misused. A data breach not only results in the loss of a valuable asset but can also lead to severe financial penalties (due to regulations like GDPR), reputational damage, and loss of customer trust. The costs associated with data breaches can be substantial, encompassing investigation, remediation, legal fees, and regulatory fines.

   Consequently, businesses increasingly expect *all* employees, not just IT specialists, to be responsible stewards of company and customer data. Developing strong data security awareness and habits is therefore invaluable for every worker. This includes:

   • Understanding Basic Security Principles: Knowing the importance of strong, unique passwords, recognizing phishing attempts, understanding the risks of using unsecured Wi-Fi, and being cautious about sharing sensitive information.

   • Adhering to Company Policies: Following established protocols for data handling, storage, access, and disposal.

   • Reporting Suspicious Activity: Recognizing potential security threats (like unusual emails or system behavior) and knowing how to report them promptly.

   • Data Privacy Awareness: Understanding the basics of data privacy regulations relevant to the business and customer data they handle.

   Individuals who demonstrate a proactive approach to data security are highly valued. Businesses often invest in training existing employees in this area, so arriving with these skills already developed positions you favorably compared to peers and demonstrates responsibility and trustworthiness.

Further Reading from Skills You Need

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The Skills You Need Guide to Jobs and Careers: Getting a Job

Develop the skills you need to get that job.

This eBook is essential reading for potential job-seekers. It covers the entire process from identifying your skills through the mechanics of applying for a job and writing a CV or resume, to attending interviews.

Conclusion

Seeing a list of data-related skills might seem intimidating, especially as they touch upon potentially complex concepts and technologies. However, building foundational competence in these areas need not require becoming an expert overnight. The key is to develop a broad understanding of how data is collected, handled, analyzed, visualized, and protected within a business context.

Gaining practical experience, even at a basic level, with common tools like spreadsheets and understanding fundamental concepts like trend analysis and data security provides a solid starting point. These foundational skills can open doors to numerous opportunities and serve as a springboard for more specialized learning as required by specific roles. What is certain is that data literacy, encompassing these core skills, is rapidly becoming an expected competency for almost every worker in the 21st century. Investing time now in developing them is a valuable step towards future career success.