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How can you test SQL queries for financial databases?

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SQL is a powerful and widely used language for querying, manipulating, and analyzing data in relational databases. However, writing SQL queries for financial databases can be challenging and error-prone, especially when dealing with complex data models, calculations, and business logic. Therefore, it is essential to test your SQL queries before deploying them to production, to ensure they are correct, efficient, and secure. In this article, we will discuss some best practices and tools for testing SQL queries for financial databases, such as:

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Manasa Savanur
Reimo Reisberg
Victor Baciu

Managing Partner @ Deodata | Helping FP&A Pros Generate Better Insights??| Finance Platform Expert

1 Use a test database

One of the first steps for testing SQL queries is to use a test database that mimics the structure and data of your production database. This way, you can avoid modifying or damaging the real data, and also isolate the effects of your queries from other users and applications. A test database should have enough data to cover different scenarios and edge cases, but not so much that it slows down your testing process. You can create a test database by copying, restoring, or generating data from your production database, or using a tool like SQL Data Generator.

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Reimo Reisberg
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If you are using production database as a source for testing database it is really important to use different masking techniques to avoid different privacy issues.

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Victor Baciu

Managing Partner @ Deodata | Helping FP&A Pros Generate Better Insights??| Finance Platform Expert
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Before creating a test database, define what characteristics/dimensions/attributes you want to analyze. Ideally you should be using objects that are commonly outputted in the source systems you want to work with. Start by creating a simple table with those objects as the header values, and create a randomized set of variables for each column. At first all of your data will be clean so it should be easy to manipulate. Understand what your ultimate output needs to be - is it a specific format that needs to be used in other tools, or are you simply re-organizing the data in a different way? Once you have a sample data-set created, try and find as many other data-sets from similar tools and compare them to what you've created.

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2 Write unit tests

Unit tests are small and specific tests that check the logic and functionality of a single query or a part of a query. For example, you can write unit tests to verify that your query returns the expected results, performs the correct calculations, handles null values, or follows the business rules. Unit tests can help you detect and fix errors early, and also document your query's behavior and assumptions. You can write unit tests for SQL queries using frameworks like tSQLt, SQLUnit, or pgTAP.

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Manasa Savanur
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Identifying errors early in the development process is extremely crucial. It saves a lot of time and makes life easy later on in the process. Testing in parts allows you to identify and fix issues in specific SQL code snippets without affecting the entire database or application. This leads to improved code quality and makes it easier for others to understand and work with the code too. A real life saver!

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3 Perform integration tests

Integration tests are larger and more comprehensive tests that check how your queries interact with other queries, data sources, or applications. For example, you can perform integration tests to verify that your queries work well with the database schema, constraints, triggers, indexes, or views, or that they support the data flows and requirements of your financial reports, dashboards, or analytics. Integration tests can help you ensure that your queries are consistent, compatible, and scalable. You can perform integration tests for SQL queries using tools like SQL Test, DBFit, or SQLCover.

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Victor Baciu

Managing Partner @ Deodata | Helping FP&A Pros Generate Better Insights??| Finance Platform Expert
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The key to an effective integration is that your input file is manipulated in such a way that the output is consistent. Most tools will need their own version of an output file, and so you should have a way to generate those files consistently depending on the tool you need to integrate with. This means you'll need to run integration tests across a variety of tools, and will likely need to tweak each one as time goes on. Context is also important - just because data is ingested properly doesn't mean it's going to be usable. You need to ensure that the end-users are able to effectively match the integrated data-set into their own schema.

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4 Optimize performance

Performance is a critical factor for SQL queries for financial databases, as they often involve large amounts of data, complex calculations, and time-sensitive operations. Therefore, you should optimize your queries to make them run faster and use less resources. You can optimize your queries by following some best practices, such as using appropriate data types, avoiding unnecessary joins or subqueries, using indexes or partitions, or applying filters or aggregations. You can also use tools like SQL Server Profiler, SQL Monitor, or SQL Tuning Advisor to measure and improve your query's performance.

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Reimo Reisberg
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Using appropriate data types is ignored too often by many developers. I have seen dates as VARCHAR(10), VARCHAR(4000) for a field with short titles with no more than 160 characters and files stored in the database rather than add just a mapping between filesystem and database with the calculated hash to provide integrity.

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5 Secure sensitive data

Security is another important aspect for SQL queries for financial databases, as they often deal with sensitive data, such as personal information, transactions, or accounts. Therefore, you should secure your queries to prevent unauthorized access, modification, or leakage of data. You can secure your queries by following some best practices, such as using parameters or stored procedures, encrypting or masking data, applying roles or permissions, or auditing or logging activities. You can also use tools like SQL Data Mask, SQL Data Compare, or SQL Audit to protect and monitor your data.

By following these best practices and tools, you can test your SQL queries for financial databases more effectively and confidently, and deliver high-quality and reliable data solutions for your financial technology projects.

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Reimo Reisberg
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Using database views can also provide extra layer for security. If you enable reading only to views and inserting and updating to tables it make more difficult to attacker to manipulate your system. Row level security is really powerful tool provided by many relational database systems.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Victor Baciu

Managing Partner @ Deodata | Helping FP&A Pros Generate Better Insights??| Finance Platform Expert
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Understanding the end-result and user-context is paramount. Often many tools require data to be formatted in highly-specific ways, and that's because each object will interact differently across an application. As an example - if you're looking to take a financial database and transform it into a PowerBI-usable format, you need to ensure that the dimensions match the way you'd like your end-users to visualize and report on that information.

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How can you test SQL queries for financial databases?

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3

4

5

6

1 Use a test database

2 Write unit tests

3 Perform integration tests

4 Optimize performance

5 Secure sensitive data

6 Here’s what else to consider

Financial Technology

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How can you test SQL queries for financial databases?

1

2

3

4

5

6

1 Use a test database

2 Write unit tests

3 Perform integration tests

4 Optimize performance

5 Secure sensitive data

6 Here’s what else to consider

Financial Technology

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