Finding the Right Data Required of Machine Learning

In November, Tejasvi Addagada from Dattamza, published an article espousing strong Data Governance when undertaking AI related projects, so we thought it'd be helpful to co-publish a series of blogs relating this and similar topics. With significant emphasis on Machine Learning these days, we thought it would be valuable if we shared some data quality struggles that our clients face during Machine Learning efforts. Over the next five blogs we'll address challenges we see in the industry and most importantly we'll provide data quality related solutions. The first Data Quality challenge is most often the acquisition of right data for ML Enterprise Use cases. As any data scientist will tell you, developing the model is less complex than understanding and approaching the problem/use-case the right way.