fbpx

Is The Pace Of AI Development Slowing Down?

By Sachin Andhare

Got Data Science Platform, Visualization, and MLOps Tools, yet struggling with scaling AI? Feature Engineering holds the key to faster development! Data science, analytics, and BI leaders in disparate industries such as financial services, retail, and manufacturing have been spending heavily on AI tools, upgrading data infrastructure, augmenting BI with ML. Your organization may already have an AI Center of Excellence (CoE) to support LoB’s where the teams are building predictive applications that can predict churn, detect fraud, and forecast inventory.  Yet, for the vast majority of enterprise customers, the AI development has been slow, AI initiatives have not scaled according to expectations. What can you do to scale AI development, accelerate adoption and propel innovation?  You need to step back, analyze the data science process and focus on three core buckets in the  development workflow - Data Preparation, Feature Engineering, and Machine Learning. More specifically, answer three critical questions: Who…

Take Advanced Analytics into Overdrive with AutoML 2.0

By Walter Paliska

The term “Advanced Analytics” was coined by the Gartner Group and is defined as the “...autonomous or semi-autonomous examination of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI), to discover deeper insights, make predictions, or generate recommendations.” Advanced analytics, by definition, requires the use of advanced techniques like data mining, machine learning, pattern matching, and other sophisticated manipulation of data in an effort to gain greater insights. The most broadly used category of advanced analytics is also known as predictive analytics. Predictive analytics itself is not new, but has traditionally been the exclusive domain of data scientists and highly skilled statisticians due to the extremely complex mathematical models required to effectively build predictive dashboards. While many organizations can benefit from predictive analytics, only a few are able to create and deploy dashboards powered by predictive algorithms, due to the high cost of…