1st Edition
by Neal Fishman (Author), Cole Stryker (Author), Grady Booch (Foreword)
Organizations can make data
science a repeatable, predictable tool, which business professionals use
to get more value from their data
Enterprise data and AI
projects are often scattershot, underbaked, siloed, and not adaptable to
predictable business changes. As a result, the vast majority fail.
These expensive quagmires can be avoided, and this book explains
precisely how.
Data science is emerging as a hands-on tool for
not just data scientists, but business professionals as well. Managers,
directors, IT leaders, and analysts must expand their use of data
science capabilities for the organization to stay competitive. Smarter Data Science
helps them achieve their enterprise-grade data projects and AI goals.
It serves as a guide to building a robust and comprehensive information
architecture program that enables sustainable and scalable AI
deployments.
When an organization manages its data effectively,
its data science program becomes a fully scalable function that’s both
prescriptive and repeatable. With an understanding of data science
principles, practitioners are also empowered to lead their organizations
in establishing and deploying viable AI. They employ the tools of
machine learning, deep learning, and AI to extract greater value from
data for the benefit of the enterprise.
By following a ladder
framework that promotes prescriptive capabilities, organizations can
make data science accessible to a range of team members, democratizing
data science throughout the organization. Companies that collect,
organize, and analyze data can move forward to additional data science
achievements:
- Improving time-to-value with infused AI models for common use cases
- Optimizing knowledge work and business processes
- Utilizing AI-based business intelligence and data visualization
- Establishing a data topology to support general or highly specialized needs
- Successfully completing AI projects in a predictable manner
- Coordinating the use of AI from any compute node. From inner edges to outer edges: cloud, fog, and mist computing
When
they climb the ladder presented in this book, businesspeople and data
scientists alike will be able to improve and foster repeatable
capabilities. They will have the knowledge to maximize their AI and data
assets for the benefit of their organizations.
