(US and Canada) John Bottega, President of the EDM Council, speaks with Robert Lutton, Vice President, Sandhill Consultants, about defensive/offensive data strategy, industries in need of data literacy, the EDM council’s stance on the topic, and how it helps AI and ML.

Bottega starts by acknowledging the defensive data strategy, saying that it fuels the data management concept. Bottega uses the phrase “canary in the coal mine” to explain the necessity of defensive posture. He cites an instance of financial Institutions wherein, playing defensive helped them understand the information before the demonstration to regulatory bodies.

However, he feels that to sustain an organization, adopting an offensive posture is pivotal. By using data offensively, with the modern technology of AI and ML, organizations have improved sales, gotten better at understanding markets, and built better products. In this context, he mentions ESG addressing issues around climate data, carbon emissions and the necessity of good data in the financial space.

Highlighting climate data, Bottega mentions the Cop 26 conference, where he witnessed companies using data offensively to bring reforms by cleaning up ocean bottoms, reforestation, etc. He then states that both the offensive and defensive use of data are necessary.

Emphasizing the data literacy aspect, Bottega affirms that every single industry can reap the benefits of data literacy. He mentions the finance industry, the climate space, and especially the worst-case scenario brought by the pandemic when true information and contact tracing were pivotal to curbing the spread of disease. He adds that all sectors, including energy, medicine, finance and manufacturing, require data literacy for sustainable growth.

Referring to the public sector, Bottega states that data transparency increases the knowledge about the benefits of data management for public good.

Emphasizing EDM Council’s role in promoting the practice of data management extensively, he says that the council fundamentally follows the rule of “data literacy for all.”

Moving on to discuss the ever-evolving AI and ML space, Bottega states that it is data literacy that helps AI and ML and not the other way around. He pronounces AI and ML as fantastic technologies but maintains that if the right data is not fed, then the AI and Ml will have fewer perfect responses. Hence, using data as an asset and having data literacy creates a quality product that fuels AI and ML, Bottega concludes.