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Generative AI as an accelerator in business data management.
Managing a large amount of data, often fragmented between different sources and difficult to navigate, represents a critical challenge for companies. It is no longer enough to have access to data: the real difficulty lies in making them usable, understandable and relevant to strategic decisions. Users, from managers to analysts, need precise and contextualized answers.
In fact, the fragmentation of Data Catalogs and the complexity of data management tools slow down workflows, create bottlenecks and limit productivity. In this scenario, Data Democratization seems like an unattainable goal: data is difficult to obtain and use, creating a gap between the potential offered by data and its usability.
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Gen AI applied to Data Management can become an important ally: based on RAG (Retrieval Augmented Generation) technology, it is possible to create a virtual assistant with which to communicate and request information from the company database through natural language, obtaining consistent answers in a short time.
Thanks to this technology, Target Reply has developed several accelerators to support Data Management: from the virtual assistant that streamlines the user requirements collection phase, to the Data Catalog assistant, up to the automatic generation of SQL queries, allowing direct access to data without technical skills. In this way, data becomes accessible to everyone, promoting the true democratization of business information.
With this assistant, Target Reply wanted to combine its innovative soul with cutting-edge technologies, such as large language models (LLM) and RAG technology, to develop a solution that simplifies the management and use of information within complex systems in large companies.
This solution makes it possible to obtain answers that are increasingly contextualized and relevant to the business environment through the integration of the company's data catalog, from which precise and relevant information is extracted.
RAG technology, combined with Target Reply's know-how, makes it possible to customize LLM models using business data, making the work of those who interact with the data not only easier, but also more efficient and accurate. Thanks to this solution, information is always at hand, allowing for faster and more informed decisions.
Functional field search
Cross-system mapping
Managing FAQs and alerts
Ticket management support
The assistant answers questions about Data Warehouse fields, providing functional and semantic descriptions, facilitating the understanding of the tables and the data contained.
It offers the possibility of comparing and mapping fields and tables between different systems, identifying relationships and differences to simplify data integrations and migrations.
The assistant allows you to quickly compare frequently asked questions and notifications of system changes or divestments, improving knowledge management and internal communication.
If a request is problematic, check for similar tickets, making it easier to retrieve existing solutions. If it doesn't find suitable answers, it automatically proceeds to open a new ticket.