AI at Work: A Step-by-Step Guide to Using our AI assistant

Alexander Kirpichny

Chief Product Officer, Ispirer Systems

Errors are all around us. Even the most polished database migration process will contain errors. But what can be done to reduce errors as much as possible? That's what the error-handling process is for.

In this article, we will examine error handling in the context of database migration, learn how AI can help simplify this process, and discuss tools that can help with this.

Why is error handling so important?

Once your migration is complete, it's easy to feel like you've crossed the finish line. However, one of the most critical phases begins - post-migration error handling. Let's explore why you can't skip this step.

Common Issues After Migration

Even with the best planning, some issues tend to pop up after migration:

• Data integrity issues – inaccurate or inconsistent information stored in databases.
• Incorrect data mapping - causes mismatched columns, and suddenly, "Name" appears in the "Phone" field
• Lost dependencies – relationships between tables or modules are disordered.
• Performance lags – slow database operation.

Impact of Unresolved Errors

Now, imagine ignoring these little gremlins. Here's what could happen:

• System stability – Mistakes can escalate into system failures and periods of unavailability.
• User experience – Nobody enjoys using faulty software or losing data, and irritated users may decide to abandon it.
• Long-term costs — Those "minor" glitches escalate, becoming costlier to rectify later—moreover, poor data results in poor decision-making.

Fixing mistakes after data migration is vital for running your new system smoothly. Data corruption, partial transfers, or compatibility problems sometimes appear after migration. Correcting these errors ensures your data is accurate and your system works well.

Catching and fixing these problems helps prevent glitches that could disrupt your business operations, security, or compliance. Good post-migration error handling makes the transition seamless and minimizes downtime, saving your organization from expensive disruptions.

Today, AI is a great help in error correction. Let's examine how it can help in post-migration tasks.

What AI Brings to the Table

AI doesn't just help in post-migration—it's like having a digital assistant that never sleeps. Here's how AI can step in:

• Detecting errors – AI scans your migrated system for data mismatches or integrity problems faster than any human could.
• Refactoring code — AI looks for opportunities to improve your code and suggests refinements automatically. It's like a spell-checker for your database scripts.
• Enhancing conversion – It is much easier to delegate the issue of improving conversion to AI than
• Generating documentation – AI helps generate comprehensive documentation for the migrated objects, providing clear explanations of the migration logic, expected inputs, and outputs.

Benefits of AI in Post-Migration

Here's why AI is a game-changer in post-migration processes:

• Increased accuracy. Humans can miss things, but AI is hyper-focused and incredibly thorough. It can conduct millions of evaluations every second, pinpointing minor discrepancies or concealed glitches that could require hours (or even days) for a person to discover. The outcome? Reduced mistakes, diminished redundancy, and enhanced overall data quality.
• Reduced time. Depending on your system's complexity, AI can cut post-migration work by 80%. Traditional post-migration testing, error checking, and optimization methods require manual labor and expertise. AI, on the other hand, can perform these tasks simultaneously. This allows teams to focus less on small debugging and more on essential projects.
• Consistent results. AI doesn't get tired or overlook minor errors. It works the same way every time, ensuring consistent quality across all processes. Whether you're migrating one database or a hundred, AI will apply the same level of care and precision.

SQL Wizard AI Assistant: 4 Simple Steps to Use It

SQLWays Wizard recently received a significant capability update: integration with Gemini. Our blog explains its capabilities for post-migration processes. Now, let's see how to use the SQLWays Wizard AI assistant.

Step 1: Review errors

As we have already said, errors may occur during the automatic migration. Let's look at an example of an import error and see how AI resolves it. The screenshot shows a function conversion error highlighted in red. Click on the pencil to edit.

After you finish the conversion or both conversion and import, you can edit the object. Just click the "Edit" icon. The system will open a new tab to display the converted code, allowing you to modify it manually.

Step 2: Use AI

In the new window that opens, you can examine the error in detail and use AI to solve it.

The system highlights errors in the code in red. To use the AI assistant, you need to click the Use AI button.

Please note that you should use your Gemini account to use the AI assistant in SQLWays Wizard.

Step 3: Configure AI assistant

At the moment, only Gemini is available for use. In the future, you will be able to choose the appropriate AI at this step. Follow the updates on our blog.

You can also adjust Gemini's temperature. Temperature is a parameter that controls the creativity of the AI's responses. Google's documentation explains how this works.

Step 4: Fix errors

Once you enter your API key and hit "Connect," a new tab will pop up with the AI assistant chat. Here, you can chat with the AI to sort out import errors or review your code.

Simply ask it to fix a specific error. You can send a request like this: "Please fix the error [Error_message] in the code [code_with_error]." The AI will send back the corrected code, which you can then copy, paste into your editor, and save.

Check results

Once you have pasted the code generated by the AI assistant, you can rerun the import and see the result.

As you can see in the screenshot, we fixed the error, and now there are no conversion errors.

Wrapping up

As we look ahead, the future of database migrations with AI is both exciting and promising. AI cannot fully take over the entire database migration process yet. However, it is a valuable asset. Think of AI as a trusted sidekick in the migration journey—providing indispensable support in the post-migration phase. AI's strengths shine brightest in refining and optimizing post-migration processes. AI helps improve error handling and refactor code. It also suggests ways to boost performance and creates detailed documentation. AI is here to make these important tasks easier and faster.

In the changing world of database migrations, AI can be a vital tool that greatly improves efficiency. It can also lower manual work and make transitions easier. Integrating AI into your migration strategy means you're not just keeping up with the future—you're actively shaping it. Embrace this technological ally and let it assist you in making database migrations more precise and effective.