Like many organizations, UnidosUS has a wide range of data needs and data sophistication across teams within its organization. Some teams track data at a very cursory level whereas others are able to do more sophisticated analytics. We have both qualitative text data and quantitative tabular data collected at different frequencies with different tools.  

Over the last couple of years we've transformed from an overreliance on spreadsheets to more structured operational databases feeding a centralized enterprise data infrastructure. Recently, we've introduced Generative AI tools that are helping to meet people where they are in order to scaffold them up the data value chain and de-silo our knowledge management so our information becomes a strategic asset rather than solely a team-level tactical resource.

All this means is that when we are trying to transform to be a more data-driven enterprise, we must keep in mind that we must move at different speeds. In this session, we will go over the framing of that work to help locate each identified data gap within a larger evolutionary framework to help determine what we need to do in order to move to the next level of data sophistication for that particular need.

Speaker: Andrew Patricio

Andrew Patricio leads the AI and Analytics work at UnidosUS, the largest Latino advocacy organization in the United States. He is responsible for ensuring that data innovation is effectively used to advance our mission. He has improved data effectiveness by replacing manually intensive efforts with tools that allow programs to track and report on data in a more streamlined fashion, freeing up capacity for staff to spend on more value-adding data activities.  

He has spearheaded our enterprise data strategy via the creation of our centralized data infrastructure in the form of a data lake/data warehouse hybrid.  He has driven innovation via the development of a custom Generative AI tool that allows our staff to generate synthesized summaries from our vast collection of internal documents in a controlled manner and directly addresses the hallucination/bias, privacy, and visibility issues inherent in similar commercial tools.  

Prior to joining UnidosUS, Andrew led technology teams at numerous District of Columbia government agencies. He is the former Chief Data Officer/CIO of the District of Columbia Public Schools where he led the implementation of the district’s first reporting data warehouse and the successful multi-million dollar replacement of the core student information system. He also ran a consulting firm advising multiple clients from the non-profit and commercial startup sectors on how to make more effective use of their data.