The Benefits of a Unified Data Management Approach

Artificial intelligence (AI) offers a lot of promise to companies, but deploying AI can be complex with many considerations and pitfalls. Data is the necessary asset to make AI work, and your organization is probably swimming in it.

But how well-managed is your data? The answer hinges on whether your company will be successful in its AI efforts.

Data management is the behind-the scenes workhorse that makes AI work. A robust management program allows data to be ingested from everywhere it needs to be, cleaned and transformed to enable AI model training, made easily available to users, and meticulously governed to ensure security, privacy, and compliance.

In this article, we’ll explore several ways a data management platform can help with your AI efforts.

Proprietary AI

As your business scales, the number of receipts, invoices, contracts, and other printed documents scale, too. And when all those documents aren’t digitized, think of the number of hours it will take an employee to catalog it.

It’s possible to use AI to automate this process. A proprietary engine scans and processes documents, extracts meaning from them, and outputs the data in a format that’s handy for reports, dashboards, and business intelligence apps.

Some benefits of using proprietary AI to scan and process documents are:

• It can translate multiple languages. A large language model (LLM) can be trained to make sense of any specific document formats that your company may have.
• Accurate data helps with decision-making. Data can be extracted from third-party platforms, enrich it, validate it, and output it to dashboards accessible throughout the company.
• Identify issues with customers earlier. Algorithms aggregate and analyze user data, spotlighting any issues with customers early on to prevent customer churn. Or to spotlight when a loyal customer is ready to grow with your company.

Retrieval augmented generation

Things that work well in a controlled environment with a carefully curated data sample don’t always work in a real-world environment. One such situation is with retrieval augmented generation (RAG), the engine that LLMs rely on to give accurate facts. But if RAG is relying on legacy data that wasn’t prepared adequately, your AI solution is going to underperform.

A data management program makes sure the basic, but vitally important, tasks are covered — data is cleaned, engineered, structured, and complete. Some tasks it can do are:

• Implement meta-intent branching for handling different types of queries.
• Develop verified quotes and see-it-in-source features for transparency.
• Monitor and balance token consumption.
• Improve data quality through semantic data scrubbing.

Research and development

Traditional research and development methods can be time consuming and expensive. Applying AI to the process can help reduce the cost and release products to the market faster. Reliable products help retain customers, boost the company’s reputation, and grow profit margin.

High-quality data is needed to make it all work. A data management program can help with the following tasks:

• Automate manual processes. Automating helps to lower errors and inefficiencies, and accelerates quantitative research by navigating unstructured data. Business decisions get made faster.
• Verify and vet output. One system can generate formulas or prototypes for new products; a secondary one can automatically evaluate, compare, and check them for compatibility and other parameters.
• Enhance new network implementations and diagnostics. AI can create potential scenarios for the design and deployment of new systems. It can create hypotheses to pinpoint problems and suggest solutions.

About the book

Wiley has recently published AI Data Management For Dummies, Keboola Special Edition. It includes insights from Snowflake and Capgemini that will help your organization integrate best practices and advanced technologies into your data strategy, what the future of AI development looks like, and more use cases.

Download AI Data Management For Dummies, Keboola Special Edition by Andy Mott, Dan O’Riordan, and Rithesh Makkena to open the door to AI success.