DataOps

Beyond the algorithm, the realities of operationalizing AI – A podcast interview with Elizabeth Press

The AI mystique might be the biggest obstacle to AI adoption. The artisanal data scientist who works on an alchemy of code output the magical algorithm impedes discussion on what is needed to commercialize and scale AI solutions. AI needs to be treated like a product and an item to be manufactured and scaled on an industrial level.

Data strategy is a part of corporate strategy

Matt Brady, Founder of Zuma Recruiting and I talked about Data Strategy. We will start by covering data strategy and roadmaps before discussing how to treat data, data roles and where data should sit in an organization. Data teams add the best value to their organization when they are part of a holistic company strategy discussion and work as strategic partners with the stakeholders.

Operational KPIs that will let you know your Data Team is creating impact (rather fixing & firefighting)

Data teams are usually busy, but are they impactful? Just because your data team is burning through tickets does not mean that they are creating impact, especially if they are stuck fixing and firefighting. Impact can be broken down into prioritization, coverage and quality. KPIs such as the statistical re-do rate, analytical throughput rate and effective analytical throughput rate that will help you quantify the impact of your data organization. This framework, along with external validation from stakeholders, is helpful to root cause and make business cases to invest in improvements.

Topography of a social media listening project

Social media monitoring has received a huge amount of attention in the past year following the explosive popularity of social media platforms coupled with the high-profile predictions in the US presidential elections. I have worked with numerous clients who wanted to build social media listening capabilities. This is an overview of what a social media listening project entails.