While organizations may be ready to unlock the full potential of their data for analytics and AI, challenges such as data silos, inefficient workflows, slow analytics, governance risks, scalability issues—and increased costs—are holding many enterprises back.
These difficulties hinder modern analytics and AI readiness by preventing organizations from effectively integrating, analyzing, and enabling data-driven outcomes.
DBTA recently held a webinar, Building a Unified Data Ecosystem for Modern Analytics & AI, with experts who discussed how to build a unified data ecosystem that powers real-time insights, AI-driven innovation, and cross-functional collaboration.
PeggySue Werthessen, vice president, product strategy, Strategy, presented the success factors for AI projects. This includes:
- Engage early with target business users
- Maintain focus on specific workflows
- Invest in AI ready data
- Create continuous feedback loops
- Set realistic expectations of uncertainty
- Evaluate lessons learned
- Share and build upon success
“AI is only as good as the data that fuels it,” she said.
Data that is AI-ready should be searchable, accurate, complete, clean, structured, contextualized, and governed, Werthessen explained.
Melissa Informatics provides software and services for AI-enabled data quality, data discovery, harmonization, integration and research, noted Robert Stanley, senior director of special projects, Melissa Informatics.
Melissa is efficiently achieving high confidence outcomes via AI with LLM/NLP technologies and semantic technologies. Using LLM, NLP, and MR with specialized training and context constraints offers best-in-breed resources and reference datasets, Stanley said.
Jack Smith, principal solutions engineer at Syncari, outlined a real-world use case involving a pharmaceutical company, Syncari recently helped. This company struggled with a fragmented data landscape, inconsistent matching logic, hierarchy mismatches, poor data quality, and manual, resource-heavy processes.
Syncari’s solution was able to deliver unified data, simplified, Smith explained. The solution includes data processing, data activation, governed master records, continuous unification, continuous data quality, continuous distribution, and is AI-ready.
For the full webinar, featuring a more in-depth discussion, Q&A, demo, and more, you can view an archived version of the webinar here.