Librería Portfolio

Master the full BI project lifecycle including requirements, project management, data modeling, architecture, data integration, BI applications, and analytics. Learn how to build out the data architecture framework that will incorporate data warehousing and Big Data elements.



Key Features

Provides practical guidelines for building successful BI, DW and data integration solutions.
Explains underlying BI, DW and data integration design, architecture and processes in clear, accessible language.
Includes the complete project development lifecycle that can be applied at large enterprises as well as at small to medium-sized businesses
Describes best practices and pragmatic approaches so readers can put them into action.
Companion website includes templates and examples, further discussion of key topics, instructor materials, and references to trusted industry sources.
Description

Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors' tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, Big Data is belittled - projects flounder, are late and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers.
After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget - turning the deluge of data into actionable information that fuels business knowledge. Finally, you'll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success.
Readership

data/technical/BI/ETL architects, consultants, developers, project managers. data modelers, IT managers, business power users. graduate CS students in BI, predictive analytics, DW, data integration, data architecture courses



Concepts and Context
1 Introduction
Business and Technical Needs
2 Justifying BI (Building Business and Technical Case
3 Defining Requirements - Business, Data and Quality
Architectural Framework
4 Architecture Introduction
5 Information Architecture
6 Data Architecture
7 Technology and Product Architectures
Data Design
8 Foundational Data Modeling
9 Dimensional Modeling
10 Advanced Dimensional Modeling
Data Integration Design
11 Data Integration Processes
12 Data Integration Design & Development
BI Design
13 BI Applications
14 BI Design & Development
15 Advanced Analytics
16 Data Shadow Systems
Organization
17 People, Process and Politics
18 Project Management
19 Centers of Excellence