What I did last week at Data Modeling Zone

I wondered why my teachers were so fascinated with what I did during the summer. I suspected that the essay about my summer escapades was a no-brainer for the teacher having summer vacation withdrawal. As I look back, I see that it was a way of getting to know me and getting some insight into my abilities and creativity.

This week I returned to my normal work routine after attending the Data Modeling Zone conference in Portland, Oregon. Those grade school assignments egged me on to share what I learned last week. I was able to boil down three hectic, fact filled days into the following six themes.

  1. Data is a long-term program and not a short-term project.
    Data architects and DBAs have been at odds for years with developers on the importance of data design. Projects are traditionally developer focused and driven. With the advent of business intelligence, master data management and big data, this trend is shifting focus and control to the data people.Data is now more than ever seen more as an enterprise asset. Data breaches and misuse of data has exposed the importance of viewing data from a view greater than at the project. Data architects can lead the way in championing and actively participating in data quality, data governance, and data management at a program (enterprise) level. I witnessed numerous references during the week on the importance of data architects making this change and taking a more active role.
  2. Big data is big, really big, and getting bigger.
    The statement “EBay generates 150 TB of data per day.” was shared by a presenter. I tried to verify it but could not find the exact number quoted, I did uncover amazing facts about the volume of data managed by this web site. For most data architects, EBay’s big data world has yet to impact their role.I attended sessions on big data, Hadoop and NoSQL. There is no denying it is making inroads past these mega websites. Larger companies are toying with big data but still trying to figure it out. Data architects must stay current with these new data technologies and make their voice known in evaluations and discussions at their employer.
  3. Data architects are embracing soft skills.
    Followers of this blog know that I emphasize the importance of effectively using soft skills. I attended a half-day session on negotiation and conflict management that was standing room only. Session attendees were actively engaged in the class exercises and had good dialogue with the instructor.I witnessed numerous speakers emphasizing the importance of stepping beyond the technical data modeling skills into roles that involved marketing, negotiation and effective communication. I led a session that was very well attended on understanding relationships and adapting behavior based on the person’s social style.
  4. Data modeling has a place in the big data world.
    Make no mistake the big data world is confusing not to just data folk but to most IT folk. The technologies are new and evolving. There is no single standard or vendor who outshines the others. Big data software vendors have not focused on data design. Traditional data modeling tool vendors have not ventured far into delivered big data data modeling solutions.Sound data management has paid great dividends over the years. It is only reasonable to think as the volume of data exponentially grows that the value of data management will grow. The data architect will most likely need to evolve their processes. The traditional logical to physical design method does not fit well in this new world. Big data solutions are driven by the needs of the application. It is in that physical side of the data house where data design will begin.
  5. Agile has become the reality and the expected.
    For many years, the data architect world rallied against the agile development folks. Accuracy and thoroughness is a theme that echoes through data architect’s work ethic and methods. The agile world threatened that ethic with talk of shorter development cycles and the perceived shift from design and documentation to prototyping and rapid development.As agile become more mainstream, so did the understanding of the methodology. Data architects have a place at the table. As with all agile team members, we need to demonstrate the value of what we deliver and how we offer that value. Becoming engaged in agile development and establishing a pattern of success softens that adversarial view of the development world.
  6. Data architects do not embrace social networking.
    I was one of the few tweeters during the week at the conference. The conference was social media enabled via a smart phone app, hash tags and speaker LinkedIn and Twitter profiles. In spite of this effort, there was a definite silence during the week.I made my pitch for Twitter and LinkedIn during my sessions. The value of social networking is hard to demonstrate when the social network is small and immature. The data architect network is in its infancy and in a catch-22 situation. There is not a critical mass of social network enabled data architects to demonstrate the network’s value, and the value of the network can only be demonstrated by the size and activity within the network.

Tom Bilcze

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