Partial book profile
Successful Business Intelligence: Unlock the Value of BI & Big Data
A practitioner's guide to why some organizations unlock extraordinary value from business intelligence and big data while others flounder, grounded in survey research and in-depth case studies.
The full book profile is not available yet.
What it’s about
Drawing on a survey of 634 BI professionals and in-depth case studies of leading organizations like Netflix, Macy's, Medtronic, FlightStats, Dow Chemical, and Constant Contact, Cindi Howson argues that successful business intelligence is far less about technology than about people, culture, executive support, business-IT partnership, data quality, relevance, and organizational agility. The book demystifies the technical architecture (data warehouses, ETL, Hadoop, analytic appliances, in-memory engines) and front-end tools (dashboards, visual data discovery, OLAP, mobile BI) just enough for business readers, then devotes its core to the human and organizational factors that catapult a BI initiative from moderate to wild success. With its 'LOFT effect' framework (Luck, Opportunity, Frustration, Threat) and ten secrets to success, the book offers both inspiration and practical lessons for anyone struggling to turn data into action and measurable business impact.
The through-line
- Who it’s for
- A BI director, executive sponsor, or business-IT professional who wants to turn their organization's data into measurable business value and competitive advantage.
- The problem
- The organization has amassed data but is not exploiting it; BI usage remains modest and untapped potential is high. They feel frustrated by information overload, organizational obstacles, and the inability to get relevant data to the people who need it.
- The plan
- Measure success in multiple ways, using objective measures when available.
- Use the LOFT effect to identify high-impact BI applications.
- Garner and sustain executive support to foster an analytic culture.
- Align BI strategy with business goals via a strong business-IT partnership.
- Build a solid data foundation and improve it incrementally.
- The payoff
- BI reaches all corners of the organization—up to 100% of employees plus customers and suppliers. · People take action on insights to improve financial performance, customer service, efficiency, and outcomes. · The organization finds insights faster, does more with less, and works in a culture where everyone works as a team.
See our guide
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Additional reading
- The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling · Ralph Kimball and Margy Ross
Provides a foundational guide to dimensional modeling (star schemas), a core concept for designing data warehouses that are understandable and performant for business users.
- Information Dashboard Design: The Effective Visual Communication of Data · Stephen Few
Offers practical advice on how to design dashboards that effectively and clearly communicate information, aligning with the book's principle that a 'picture is worth a thousand numbers'.
- Performance Dashboards: Measuring, Monitoring, and Managing Your Business · Wayne Eckerson
Provides a comprehensive overview of dashboards and scorecards, expanding on the definitions and use cases for these critical BI front-end tools.
- Agile Data Warehousing Project Management: Business Intelligence Systems Using Scrum · Ralph Hughes
Offers a detailed guide on applying agile methodologies specifically to BI and data warehousing projects, which the book identifies as a key success factor.
Featured in these guides
- Ship Analytics, Don't Just Prototype It →Cited source
- Practice Business Intelligence & Data Science →Cited source
- Get The Business To Actually Use It →Cited source
- Build A Model That Holds Up Outside Your Sample →Cited source
- Get The Data Trustworthy First →Cited source
Co-cited books
- Data Warehouse and Data Mining · Jugnesh Kumar
- Data Science from Scratch: First Principles with Python
- An Introduction to Statistical Learning: with Applications in R
- Machine Learning and Data Science
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
- Business Intelligence Guidebook: From Data Integration to Analytics · Rick Sherman
- Big Data: A Revolution That Will Transform How We Live, Work, and Think · Viktor Mayer-Schönberger, Kenneth Cukier
- Practical Statistics for Data Scientists