Next Level BI

Leverage AI-Generated Realtime Reports

In today’s data-driven world, businesses increasingly rely on insightful reports to inform decision-making and drive growth. However, getting BI tools to produce the results you want or crafting complex SQL statements to extract relevant data can be a daunting task, especially for those without a technical background. Enter DataWeaver - AI-generated reports - a powerful feature that enhances your business intelligence capabilities.

Understanding the Need for Business Progress Reports

Business progress reports are essential for tracking KPI’s (key performance indicators), understanding market trends, and making informed strategic decisions. These reports often require data from multiple sources, including sales, marketing, finance, and operations.

To compile data, it may be necessary to create complex SQL statements. Traditionally, this process has required a solid understanding of SQL syntax and database structures or expensive BI tools. However, AI technology combined with modern no-code applications is opening up new possibilities and change the way business applications are built, the way data from different sources is consolidated, and the way users can interact with data.

Understand the Underlying Problems of AI

Artificial Intelligence is great. It is, without a doubt, one of the most ground breaking technological advancements of our time. However, it comes with some problems that should be addressed.

Privacy: Feeding an AI with your data can cause problems in two ways. First, sharing data outside the EU without a legal basis is a violation of GDPR. In addition, few people are aware of whether they have a data processing agreement with the AI ​​company. Second, data will often be reused to train the AI, thus forever becoming part of a huge data cluster.

Hallucination: Large Language Models all have the inherent flaw that they sometimes make up their own false conclusions. The error rate for the best models is less than 2%, but that is still way too high in case we make decisions based on AI output. The problem is that hallucinations in natural language responses can be very hard to detect, and needs to be done by humans (or other AI’s).

How it Works

The AI-based DataWeaver analyses user queries and translate natural language requests into report definitions. This capability allows users to specify what data they want without needing to understand the underlying database structure or SQL syntax. Here’s how the process typically works:

1. Natural Language Input: The user describes, in natural language, the data they want insight into, such as; "Show me the sales trends for the last quarter by product category.”
2. AI Interpretation: The AI parses the request in conjunction with data model metadata. The AI has no access to data values, but returns a query that can be transcribed by the TS Report Engine.
3. Query Verification: The generated query is executed against real-time data, retrieving the desired information. Essentially, this step catches hallucinations, because the results from the AI will fail to process correctly.
4. Data Visualization: The results can be presented in user-friendly formats, such as charts or tables, making the information easy to understand and interpret. With a single click, the report can be added to an existing dashboard in the application.

Benefits of Using DataWeaver

Besides the obvious benefits of gaining greater insights into your data without the need for SQL skills and data analysis experience. Here are the core benefits of using DataWeaver:

1. Security: Unlike other AI-based tools like Microsoft Copilot, Tableau, etc. TS’ DataWeaver does not allow the AI (ChatGPT) to access your data. It is only allowed access to meta data (i.e ID’s and System Names).
2. Accessibility: By eliminating the need for advanced SQL knowledge, or expensive BI tools, DataWeaver makes data accessible to a wider range of users, including those in non-technical roles.
3. Time Efficiency: Generating SQL statements manually can be time-consuming. DataWeaver can produce accurate reports in seconds, significantly speeding up the process of building reliable, real-time reports.
4. Error Reduction: Manually written SQL can be prone to errors, especially in complex queries. AI-generated SQL reduces the risk of syntax errors and logical mistakes.
5. Flexibility: Users can quickly adapt their queries based on changing business needs or new questions that arise, ensuring that reports remain relevant.
6. Insights: With easier access to data and better understanding of the relationship between different factors, businesses can explore more complex analyses and generate deeper insights to drive strategic initiatives.

Real-World Applications

Businesses across industries can leverage DataWeaver for generating AI-based SQL queries to improve the quality and speed of advanced business reporting.

• Sales Analysis: Sales teams can quickly retrieve reports on sales performance, customer acquisition, and product profitability.
• Marketing Insights: Marketing departments can analyze campaign performance, customer engagement metrics, and ROI calculations.
• Financial Reporting: Finance teams can generate detailed financial statements, budget vs. actual analyses, and cash flow forecasts.
• Operational Efficiency: Operations can track supply chain metrics, inventory levels, and production efficiency to optimize processes.

And most importantly, businesses can make use of these real-world applications safe in the notion that none of their data is transferred or otherwise accessible for the AI. This means that information security and compliance is intact.

Choosing the Right Tool

The ability to efficiently query and manipulate databases is important for organizations of all sizes, but selecting the right tool is crucial to ensure information security and ease of use.

SQL (Structured Query Language) is the primary language used to interact with relational databases. However, crafting complex SQL statements can be challenging, particularly for those who may not have a deep understanding of database schema or SQL syntax. When selecting an AI tool for generating reports, businesses should consider:

• Information Security: Make sure that no matter what AI tool you use, the AI should not get access to your actual data. This is essential to abide by modern privacy laws.
• Ease of Use: The interface should be intuitive, allowing users to query for relevant data points or relationships in data without extensive training.
• Real-time Capability: Working with data from a BI perspective should be based on real-time data. Many BI tools operate as stand-alone applications or external web services that perform queries at a fixed interval. However, meaningful BI should be based on real-time data to give your team the best basis for action and respons..
• Integration Capabilities: The tool should seamlessly integrate with existing databases and preferably encompass data visualization capabilities to avoid yet another layer of transfer.
• Customization: The ability to access, customize, or modify the generated SQL for specific business purposes can enhance flexibility for users with sufficient technical understanding.
• Cost-Effectiveness: Understand the pricing structure—whether it’s a subscription model, one-time purchase, or pay-per-use. Choose a model that aligns with your budget and usage expectations.

Conclusion

In short, using an AI-powered tool to generate real-time reports can streamline your data usage and empower users across your organization. By addressing usability, information security, performance, support, and cost-effectiveness, you can find a solution that not only meets your needs but also improves your data management practices.

DataWeaver can transform the way your team interacts with data. Data becomes more accessible and usable. By simplifying the process, a wider range of employees are empowered to harness the potential of data. This leads to better decision-making and improved business outcomes.