When scale, structure and reliability matter, relational databases and SQL offer more

Why SQL and Relational Databases Still Matter in Data and Accountancy

When people ask about important tools for working with data, SQL often comes to mind. It’s not the newest or flashiest technology, but it has proven to be one of the most consistently useful. Especially when working with structured data in professional environments, a solid understanding of relational databases and SQL provides a strong foundation for analysis, reporting and decision-making.

This is particularly true in fields like finance and accountancy, where accurate, reliable and well-organised data is essential. Learning SQL and understanding how relational databases are structured can make daily tasks more efficient and improve the quality of insights.

Relational Databases, their Structure and Stability

Relational databases have been a cornerstone of business data systems for decades. They organise data into clearly defined tables, each with columns and rows and allow for relationships to be established between them. This structure mirrors many real-world processes. In accountancy, for example, you might work with tables for transactions, clients, departments, expense categories or ledger entries. Each of these datasets can be linked by common identifiers like account numbers, client IDs or dates.

The main strength of relational databases lies in their consistency and integrity. They are designed to avoid duplication, enforce data rules and support multiple users interacting with the same information. This is ideal for tasks like financial reporting or auditing, where the accuracy and traceability of data are essential. For example, rather than storing employee information repeatedly across multiple files, a relational model stores it once and links it to other relevant data, such as salary records or tax submissions.

Relational systems also make collaboration easier. Because all users are accessing a shared source of truth, discrepancies are reduced and communication becomes clearer across teams.

A Practical Tool for Working with Data

Structured Query Language, or SQL, is the standard language used to interact with relational databases. It allows you to select, filter, sort and aggregate data, as well as join multiple tables together to explore relationships.

In many data-related roles, including in accountancy and finance, SQL becomes particularly useful when you need to work directly with large datasets or automate repetitive reporting tasks. For instance, if you want to calculate monthly totals for different expense categories, or find which clients have outstanding invoices, SQL enables you to do so efficiently.

Rather than being highly technical or complex, SQL is designed to be readable and logical. Queries are written in plain syntax that resembles spoken language—“SELECT this FROM that WHERE condition”—which helps reduce the learning curve for those without a programming background. It also encourages careful thought about how data is organised and how best to retrieve it.

What sets SQL apart is its wide applicability. It is supported by nearly all major database systems and is often embedded in financial software and enterprise platforms. Because of this, SQL skills tend to transfer well across different roles and industries.

Why Use SQL Instead of Google Sheets?

For small, ad hoc tasks, Google Sheets is incredibly accessible and easy to use. However, as soon as your data scales, or you need to maintain integrity across multiple sources, SQL and relational databases quickly become more appropriate.

Sheets lack robust version control, have limited capacity for concurrent users and can become sluggish or unstable with larger datasets. More importantly, they don’t support complex data relationships well. You may end up duplicating data across tabs, introducing inconsistencies and errors.

Relational databases offer stronger structure, more reliable performance at scale and better tools for managing access, enforcing rules and keeping everything synchronised. SQL gives you the power to retrieve and manipulate data dynamically, which is far harder to do with nested formulas in spreadsheets.

Practical Benefits in Accountancy

In an accountancy context, SQL can make many tasks easier, more accurate and more transparent. Take, for example, the process of reconciling financial records. Rather than manually comparing values across spreadsheets, SQL allows you to define precise queries that automatically highlight inconsistencies. You can trace every value back to its origin, whether it’s an expense, revenue entry or adjustment.

SQL also supports timely decision-making. With access to the underlying database, you’re not limited to static reports generated weekly or monthly. You can produce tailored summaries or ad hoc insights as needed—such as identifying a sudden spike in costs or tracking the impact of new policies.

In regulated industries, where accountability and auditability are non-negotiable, SQL provides a clear advantage. Queries can be saved, reviewed and refined. You can document the steps taken to produce a result, which is vital when preparing financial statements or justifying figures to stakeholders.

Moreover, using SQL directly helps reduce reliance on exported reports and spreadsheets. This not only cuts down on version control issues but also reduces the risk of errors that come from manual handling of data.

What Is ACID and Why Does It Matter?

One of the reasons relational databases are so reliable is because they follow a set of properties known as ACID: Atomicity, Consistency, Isolation and Durability.

Atomicity ensures that a series of operations within a transaction either all happen or none happen. This prevents partial updates from corrupting data
Consistency means the database moves from one valid state to another, enforcing rules and constraints that maintain accuracy
Isolation ensures that transactions running at the same time do not interfere with each other, avoiding conflicts or incorrect results
Durability guarantees that once a transaction is committed, it will not be lost—even in the event of a crash or power failure.

For accountancy and financial systems, these principles are fundamental. They help maintain accuracy across large numbers of entries, support auditability and protect the integrity of sensitive financial data under all conditions.

Complementing Other Tools

While SQL is a valuable tool, it’s important to see it as part of a broader toolkit. Many tasks also involve using spreadsheets, visualisation tools, or more advanced statistical software. Languages like Python and R offer additional capabilities for data transformation and modelling, especially when the work involves more complex logic or machine learning.

However, the strength of SQL lies in its ability to retrieve and structure the data that feeds these other tools. It helps ensure that the right data is in the right format, ready to be used. For professionals working in accountancy, where the data is often relational and transactional, SQL sits comfortably between data collection and more detailed analysis or reporting.

Long-Term Relevance

Relational databases and SQL have remained relevant because they offer a balance of clarity, efficiency and scalability. Despite the rise of newer technologies and frameworks, many systems still rely on relational data storage. This includes everything from government financial systems to private accounting software and cloud-based business platforms.

Understanding how relational data is structured, and knowing how to write basic queries, provides a long-term benefit. These are skills that don’t quickly become obsolete and often serve as a stepping stone to more advanced data work.

Conclusion

For anyone beginning their journey in data, particularly those with an interest or background in accountancy, learning SQL and understanding relational databases is a sensible and rewarding investment. It helps build confidence when working with systems, promotes clearer thinking about how information is connected and allows for more independence in day-to-day analysis.

While it may not be the most exciting skill to learn at first glance, its value becomes clear as soon as you start using it in real-world settings. And once you’ve mastered the basics, it’s a tool you’ll return to again and again.

In short, SQL is not about being a software developer. It’s about thinking logically, understanding data structure and being equipped to ask the right questions—and get reliable answers—in a language that systems understand.

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