Bob Lambert

Jazz on the harmonica

Tag: Application Development

  • Secrets of Successful Projects

    I’ve had the good fortune to have been involved in many successful application development and analytics efforts (here and here), and a few that were less so (here and here). Recently, I’ve thought about the differences between the successful and the unsuccessful. As I see it, there are five general characteristics that the successful endeavors…

    continue reading

  • 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…

    continue reading

  • Guidelines for Successful Tableau Analytics Rollout

    I’ve written previously about development of Tableau analytics capability from single user to multiple teams across an organization. This article is intended for those who may have first installed Tableau Server to enable folks outside their own sphere to interact with their Tableau creations. For the way ahead, it presents a few guidelines for successful…

    continue reading

  • The Myth of Agile Sign-Off

    Although Agile writers and thinkers agree that “there is no sign-off” in Agile methodology, the practice of requiring product owners and business customers to sign off on requirements and delivered work products persists in Agile settings. I’ve seen it most when an agile team faces delivery challenges and leaders perceive the problem is scope creep or…

    continue reading

  • 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…

    continue reading

  • 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…

    continue reading

  • 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…

    continue reading

  • More on “Select Failed. [2646] No more spool space”

    Also see the previous related post Escaping Teradata Purgatory (Select Failed. [2646] No more spool space) Not too long ago I posted on how to avoid the dreaded “No more spool space” error in Teradata SQL. That post recounted approaches to restructuring SQL queries so that they would avoid being cancelled for using inordinate amounts…

    continue reading

  • Toward a Values-Based Approach to Auditing Agile Projects

    By now Agile has taken over waterfall as the dominant app dev project pattern*. In many large organizations, the traditional waterfall PMO also owns Agile projects. One aspect of PMO oversight that can work against Agile culture is the project audit. If the goal of an audit is to ensure the project reflects Agile values,…

    continue reading

  • 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…

    continue reading