Bob Lambert

Jazz on the harmonica

Category: Data Management

  • One More Species of Overloaded Data

    A while back I wrote the post A Field Guide to Overloaded Data, which publicized the work of Duane Hufford, who examined different types of overloaded data during the 1990s. Over the years his classifications of overloaded data effectively categorized data anomalies I encountered in the wild. That is until recently, when a colleague encountered…

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  • Two key interview questions for SQL developer candidates

    Frequently in my career I’ve selected or helped select ETL and reporting professionals who need SQL skills. For some of those opportunities, placement firms returned resumes with interminable, and nearly identical, lists of technical achievements with excruciating unnecessary detail (paraphrasing: “Wrote SELECT statements using GROUP BY”, “Applied both inner and outer joins”). Before interviewing we…

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  • Reengineered Processes Need Business-Defined Data

    “Business process reengineering is the act of recreating a core business process with the goal of improving product output, quality, or reducing costs.”* Recently I’ve perused articles on business process reengineering and have been surprised to find that they share a lack of emphasis on data definition. By establishing a shared business vocabulary, identifying and…

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  • Data Architecture for Improved Dashboard Performance

    Sometimes success seems like a data analytics team’s worst enemy. A few successful visualizations packaged up into a dashboard by a small skunkworks team can generate interest such that a year later the team has published scores of mission critical dashboards. As their use spreads throughout the organization, and as features expand to meet the…

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  • Two Design Principles for Tableau Data Sources

    It’s not unusual for talented teams of business analysts to find themselves maintaining significant inventories of Tableau dashboards. In addition to sound development practices, following two key principles in data source design help these teams spend less time in maintenance and focus more on building new visualizations: publishing Tableau data sources separately from workbooks and…

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  • Prioritize data initiatives with the new Data Management Maturity Index

    In my experience, data management is both a mission critical and an undervalued capability. Perhaps recent customer data losses and regulatory initiatives like GDPR tend to raise the stock of data maturity efforts, but it remains undervalued. For example, any Fortune 1000 firm building end-to-end processes finds that much of the cost goes to translating…

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  • Data Governance Meets Procurement

    Why pay good money for bad data? Of course no one would do that on purpose, but I as a consultant over many years I’ve often seen it. A vendor fulfills a contract to the letter, which unfortunately allows them to deliver required reports in various, sometimes changing, formats with suspect data quality. The customer…

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  • Leadership Must Prioritize Data Quality

    Data quality improvements follow specific, clear leadership from the top. Project leaders count data quality among project goals when senior management encourages them to do so with unequivocal incentives, a common business vocabulary, shared understanding of data quality principles, and general agreement on the objects of interest to the business and their key characteristics. Poor…

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  • Leader’s Data Manifesto at #EDW19: Building a Foundation for Data Science

    It’s been a truism that data is a resource, but to prove it you just have to follow the money. As the illustration shows, the vast majority of corporate market value draws from intangible assets. Just as money is an abstraction that represents wealth, data is an abstraction that represents these intangible assets. It’s year…

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  • Enterprise Data Prep for Analytics: Two Principles

    Data scientists spend most of their time doing data integration rather than gathering insights. In my interview with data scientist Yan Li, she said that data collection and prep takes at least 70% of her time. Obviously, there’s a lot of integration work to do on data that’s new to analytics efforts, but not every…

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