It's all analytics. Part II, Designing an integrated AI, analytics, and data science architecture for your organization - Burk, Scott William, 1961-; Sweenor, David; Miner, Gary (New York : Productivity Press, 2021)
Up to 70% and even more of corporate Analytics Efforts fail!!! Even after these corporations have made very large investments, in time, talent, and money, in developing what they thought were good data and analytics programs. Why? Because the executives and decision makers and the entire analytics team have not considered the most important aspect of making these analytics efforts successful. In this Book II of "It's All Analytics!" series, we describe two primary things: 1) What this "most important aspect" consists of, and 2) How to get this "most important aspect" at the center of the analytics effort and thus make your analytics program successful. This Book II in the series is divided into three main parts: Part I, Organizational Design for Success, discusses . The need for a complete company / organizational Alignment of the entire company and its analytics team for making its analytics successful. This means attention to the culture - the company culture culture!!! To be successful, the CEO's and Decision Makers of a company / organization must be fully cognizant of the cultural focus on establishing a center of excellence in analytics'. Simply, "culture - company culture" is the most important aspect of a successful analytics program. The focus must be on innovation, as this is needed by the analytics team to develop successful algorithms that will lead to greater company efficiency and increased profits. Part II, Data Design for Success, discusses .. Data is the cornerstone of success with analytics. You can have the best analytics algorithms and models available, but if you do not have good data, efforts will at best be mediocre if not a complete failure. This Part II also goes further into data with descriptions of things like Volatile Data Memory Storage and Non-Volatile Data Memory Storage, in addition to things like data structures and data formats, plus considering things like Cluster Computing, Data Swamps, Muddy Data, Data Marts, Enterprise Data Warehouse, Data Reservoirs, and Analytic Sandboxes, and additionally Data Virtualization, Curated Data, Purchased Data, Nascent & Future Data, Supplemental Data, Meaningful Data, GIS (Geographic Information Systems) & Geo Analytics Data, Graph Databases, and Time Series Databases. Part II also considers Data Governance including Data Integrity, Data Security, Data Consistency, Data Confidence, Data Leakage, Data Distribution, and Data Literacy. Part III, Analytics Technology Design for Success, discusses . Analytics Maturity and aspects of this maturity, like Exploratory Data Analysis, Data Preparation, Feature Engineering, Building Models, Model Evaluation, Model Selection, and Model Deployment. Part III also goes into the nuts and bolts of modern predictive analytics, discussing such terms as AI = Artificial Intelligence, Machine Learning, Deep Learning, and the more traditional aspects of analytics that feed into modern analytics like Statistics, Forecasting, Optimization, and Simulation. Part III also goes into how to Communicate and Act upon Analytics, which includes building a successful Analytics Culture within your company / organization. All-in-all, if your company or organization needs to be successful using analytics, this book will give you the basics of what you need to know to make it happen.
Part 1: Designing for Organizational Success Chapter 1: Some Say it Starts with Data, It Doesn't Chapter 2: The Anatomy of a Business Decision Chapter 3: Trustworthy AI Part 2: Designing for Data Success Chapter 4: Data Design for Success Chapter 5: Data in Motion, Data Pipes, APIs, Microservices, Streaming, Events and More Chapter 6: Data Stores, Warehouses, Big Data, Lakes and Cloud Data Chapter 7: Data Virtualization Chapter 8: Data Governance and Data Management Chapter 9: Miscellanea -- Curated, Purchased, Nascent and Future Data Part 3: Designing for Analytics Success Chapter 10: Technology to Create Analytics Chapter 11: Technology to Communicate and Act Upon Analytics Chapter 12: To Build, Buy, or Outsource Analytics Platform
OCLC-licensed vendor bibliographic record.
Keywords: Artificial intelligence; Decision making; Visual analytics; Big data; BUSINESS & ECONOMICS / Management; BUSINESS & ECONOMICS / Leadership; BUSINESS & ECONOMICS / Information Management