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All Data Management Publications & Research


Best of Business Intelligence Volume 9

TDWI's Best of Business Intelligence Volume 9

February 1, 2012

In this issue of the Best of Business Intelligence, Stephen Swoyer calls 2011 “the year in which social media emerged as one of several forces … that will fundamentally transform BI as we know it.” Plus, TDWI Research analysts Philip Russom and David Stodder share predictions for 2012.


TDWI Best Practices Report: Mobile Business Intelligence and Analytics

Mobile Business Intelligence and Analytics: Extending Insight to a Mobile Workforce

December 28, 2011

Excitement is growing among business users about how they could use mobile devices to transform the role of information in customer interactions, performance management, planning and forecasting, and their daily operational decisions while on the go. This report examines the impact of mobile computing on the development, management, and implementation of applications and services for business intelligence and analytics.


Business Intelligence Journal | Vol. 16, No. 4

December 5, 2011

 Exploring the power of master data management with social media data; moving to real-time BI; pervasive BI; agile project management; and more.


TDWI Checklist Report: Real-Time Data Quality

TDWI Checklist Report: Real-Time Data Quality

November 7, 2011

This TDWI Checklist Report drills into the details and desirable use cases for real-time data quality (RT DQ) to help user organizations understand what’s available and when to use it.


TDWI Checklist Report Preparing Your Organization for Master Data Management

TDWI Checklist Report: Preparing Your Organization for Master Data Management

October 18, 2011

This TDWI Checklist Report reviews opportunities where anticipating potential roadblocks can help improve planning, identify issues early in the program, and generally eliminate barriers to master data management (MDM) success.


Checklist Report Seven Steps to Implementing Data Discovery

TDWI Checklist Report: Seven Steps to Implementing Data Discovery

September 19, 2011

This report examines the role of data discovery in meeting critical information management objectives for understanding data quality and enabling master data management (MDM), data consolidation, and sensitive data protection.


Big Data Analytics

Big Data Analytics

September 14, 2011

Big data analytics is the intersection of two technical entities that have come together. First, there’s big data for massive amounts of detailed information. Second, there’s advanced analytics, which can include predictive analytics, data mining, statistics, artificial intelligence, natural language processing, and so on. Put them together and you get big data analytics, the hottest new practice in BI.


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Channels by Topic

  • Agile BI »
    Includes:
    • Agile
    • Scoping
    • Principles
    • Iterations
    • Scrum
    • Testing
  • Big Data Analytics »
    Includes:
    • Advanced Analytics
    • Diverse Data Types
    • Massive Volumes
    • Real-time/Streaming
    • Hadoop
    • MapReduce
  • Business Analytics »
    Includes:
    • Advanced Analytics
    • Predictive
    • Customer
    • Spatial
    • Text Mining
    • Big Data
  • Business Intelligence »
    Includes:
    • Agile
    • In-memory
    • Search
    • Real-time
    • SaaS
    • Open source
  • BI Leadership »
    Includes:
    • Latest Trends
    • Technologies
    • Thought Leadership
  • Data Analysis and Design »
    Includes:
    • Business Requirements
    • Metrics
    • KPIs
    • Rules
    • Models
    • Dimensions
    • Testing
  • Data Management »
    Includes:
    • Data Quality
    • Integration
    • Governance
    • Profiling
    • Monitoring
    • ETL
    • CDI
    • Master Data Management
    • Analytic/Operational
  • Data Warehousing »
    Includes:
    • Platforms
    • Architectures
    • Appliances
    • Spreadmarts
    • Databases
    • Services
  • Performance Management »
    Includes:
    • Dashboards, Scorecards
    • Measures
    • Objectives
    • Compliance
    • Profitability
    • Cost Management
  • Program Management »
    Includes:
    • Leadership
    • Planning
    • Team-Building
    • Staffing
    • Scoping
    • Road Maps
    • BPM, CRM, SCM
  • Master Data Management »
    Includes:
    • Business Definitions
    • Sharing
    • Integration
    • ETL, EAI, EII
    • Replication
    • Data Governance

Meet the Analysts

  • Philip Russom

    Philip Russom

    is director of TDWI Research for data management and oversees many of TDWI’s research-oriented publications, services, and events. Before joining TDWI in 2005, Russom was an industry analyst covering BI at Forrester Research, Giga Information Group, and Hurwitz Group. He also ran his own business as an independent industry analyst and BI consultant and was a contributing editor with leading IT magazines. Before that, Russom worked in technical and marketing positions for various database vendors. He can be reached at prussom@tdwi.org. 

    View a selection of Philip's contributions
  • David Stodder

    David Stodder

    is director of TDWI Research for business intelligence. He focuses on providing research-based insight and best practices for organizations implementing BI, analytics, performance management, data discovery, data visualization, and related technologies and methods. He is the author of recent TDWI Checklist Reports on data discovery and information management, and an upcoming Best Practices report on mobile BI and analytics. Stodder has provided thought leadership on BI, information management, and IT management for over two decades. Previously, he headed up his own independent firm and served as vice president and research director with Ventana Research. He was the founding chief editor of Intelligent Enterprise and served as editorial director for nine years. He was also one of the founders of Database Programming & Design magazine and directed the Database Summit Series conferences. He can be reached at dstodder@tdwi.org. 

    View a selection of David's contributions
  • Fern Halper

    Fern Halper

    is director of TDWI Research for advanced analytics, focusing on predictive analytics, social media analysis, text analytics, cloud computing, and other “big data” analytics approaches. She has more than 20 years of experience in data and business analysis, and has published numerous articles on data mining and information technology. Halper is co-author of “Dummies” books on cloud computing, hybrid cloud, service-oriented architecture, and service management, and is currently completing Big Data for Dummies (to be published in April 2013). She has been a partner at industry analyst firm Hurwitz & Associates and a lead analyst for AT&T Bell Labs. Her Ph.D. is from Texas A&M University. You can reach her at fhalper@tdwi.org, or follow her on Twitter: @fhalper. 

    View a selection of Fern's contributions

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