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TDWI Best Practices Reports


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.


Self-Service Business Intelligence

Self-Service Business Intelligence: Empowering Users to Generate Insights

July 1, 2011

In today's economic environment, organizations must use business intelligence (BI) to make smarter, faster decisions. Yet, in too many organizations, decisions are still not based on business intelligence because of the inability to keep up with demand for information and analytics. To satisfy this demand, one approach involves setting up a self-service BI (SS BI) environment.


Next Generation Data Integration

Next Generation Data Integration

April 1, 2011

Data integration (DI) has undergone an impressive evolution in recent years. Today, DI is a rich set of powerful techniques, including ETL (extract, transform, and load), data federation, replication, synchronization, changed data capture, data quality, master data management, natural language processing, business-to-business data exchange, and more. This report brings readers up to date on all that's happening in this exciting arena of data management.


Visual Reporting and Analysis

Visual Reporting and Analysis: Seeing Is Knowing

January 3, 2011

Data visualization is increasingly an essential element of business intelligence (BI). No longer restricted to specialized applications, data visualization in the form of charts, maps, and other graphical representations is enabling business users to better understand data and use it to achieve tactical and strategic objectives.


Operational Data Warehousing

Operational Data Warehousing: The Integration of Operational Applications and Data Warehouses

October 1, 2010

This report gives readers a jump-start on their journey toward operational data warehousing by describing its enabling technologies and real-world business use cases, providing useful planning information for both business and technical managers.


BI on a Limited Budget: Strategies for Doing More with Less

July 1, 2010

The current economic downturn has accentuated the need among business intelligence (BI) teams to do “more with less.” With budgets cut or flat, most BI teams have been forced to innovate and find new ways to deliver projects more efficiently.


Unified Data Management: A Collaboration of Data Disciplines and Business Strategies

April 1, 2010

In most organizations today, data and other information are managed in isolated silos by independent teams using various data management tools for data quality, data integration, data governance and stewardship, metadata and master data management, B2B data exchange, content management, database administration and architecture, information lifecycle management, and so on. In response to this situation, some organizations are adopting what TDWI calls unified data management (UDM), a practice that holistically coordinates teams and integrates tools. Other common names for this practice include enterprise data management and enterprise information management. Regardless of what you call it, the “big picture” that results from bringing diverse data disciplines together yields several benefits, such as cross-system data standards, cross-tool architectures, cross-team design and development synergies, leveraging data as an organizational asset, and assuring data’s integrity and lineage as it travels across multiple organizations and technology platforms.


Transforming Finance: How CFOs Use Business Intelligence to Turn Finance from Record Keepers to Strategic Advisors

January 1, 2010

The finance department sits at the information nexus of the organization. It regularly collects financial and non-financial data from every business unit and consolidates that information into summary and detailed management reports. Finance can therefore be a powerful agent of organizational change. It can leverage the information that it collects to assist executives and line of business managers to optimize processes, achieve goals, avert problems, and make decisions.


Next Generation Data Warehouse Platforms

October 1, 2009

If you’re a data warehouse professional—or you work closely with one—you’ve probably noticed the many new options for data warehouse platforms that have appeared this decade. We’ve seen the emergence of new categories of data warehouse (DW) platforms, such as data warehouse appliances and software appliances. A new interest in columnar databases has led to several new vendor products and renewed interest in older ones. Open source Linux is now common in data warehousing, and open source databases, data integration tools, and reporting platforms have come out of nowhere to establish a firm foothold. In the hardware realm, 64-bit computinghas enabled larger in-memory data caches, and more vendors now offer MPP architectures. Leading database vendors have added more features and products conducive to data warehousing.


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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
  • 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 senior manager of TDWI Research. He is a well-known figure in business intelligence, having worked as an industry analyst covering BI and related issues for Forrester Research, Giga Information Group, Hurwitz Group, and his own private BI practice. At TDWI, he specializes in data warehousing and data integration issues. He is the author of many in-depth reports and is a frequent speaker at TDWI conferences and Webinars; he is also chair of TDWI’s Solution Summit on Master Data Management. He can be reached at prussom@tdwi.org

    View a selection of Philip's contributions

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