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The Importance of Communication

The Importance of Communication. Effective communication techniques for data management professionals. A presentation by Mike Nicewarner. Важная Информация. Important Information. Effective communication is more than just having good information.

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The Importance of Communication

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  1. The Importance of Communication Effective communication techniques for data management professionals A presentation by Mike Nicewarner

  2. Важная Информация Important Information Effective communication is more than just having good information • Управление данных - важный компонент здоровой организации IT • Администраторы базы данных очень интеллектуальны • Хороший модельер данных может упростить сложные деловые требования • Без хороших данных, будут терпеть неудачу все усилия по IT • Data management is an important component of a healthy IT organization • Database administrators are very intelligent • A good data modeler can simplify complex business requirements • Without good data, all IT efforts will fail It is more than excellent presentation skills It requires understanding, and change, so that the involved parties are impacted So, for today, my goal is to effectively communicate with you

  3. Introduction • Who am I? • Who are you? • Why are we here? • What can we learn today? • Questions are the best wayto start a conversation • “How may I help you?” • But not “Wha’d’ya want??”

  4. Agenda • Data Management • Definitions, discussion • Various Roles and Responsibilities • Bridging the Gap • Discussion of topics, tools and techniques • Conclusion

  5. What is Data Management? • Encompasses data storage, manipulation, migration, security, etc • Data Modeling • Gathering / documenting data requirements • Organizing & structuring data storage • Development project must consider data concerns at an early phase • Data requirements must be captured and communicated during and after the project

  6. What is Data Modeling? Business Requirements Conceptual Data Model Logical Data Model Level of detail Scope of model Physical Data Model Database Implementation Time

  7. What are Data Requirements • Conversational, narrative, business-oriented • Might start as a list of “things” • Describe relationships between things • Capture metadata within context of business process • Ask questions like “What is this?”, “Where does it come from?”, “Who provides this?”

  8. The Conceptual Data Model • History • Peter Chen’s Entity-Relationship Diagram • Typical ERD

  9. The Conceptual Data Model • Can be “read” • Why use just boxes and lines?

  10. The Conceptual Data Model • Value in simplicity • Additional metadata “under the covers” • Can show more or less detail • Audience is Business and Architects

  11. The Conceptual Data Model • ER is most common, but it has failings • Cyclic relationships • Must decide Entity or Attribute too early • Other methods out there • Object Role Modeling • Do not be religious about notations • Use whatever works to communicate • With the Business!

  12. Logical Data Model • Data structure starting to have structure • Additional details • Foreign keys, surrogate keys, indexes, data types • IT standards and conventions • Audience is IT • Architects, Business Analysts , Developers, etc.

  13. Logical Data Model • Consider the other modeling notations • Again, communication is critical • Yes, within IT • Should I force everyone to learn my language? • Can I adapt my presentation to them? • What would make the communication more effective? • Should know their “language”

  14. Physical Data Model • Database-specific details • Very technical • DBA heavily involved • Typical hand-off situation (DA -> DBA) • Naming conventions • Physical options • Audience is DBA and Developer

  15. Physical Data Model • How many of us spend all our time in the physical model? • Is this the right “language” to use for everyone? • How about this one: • Sure, we use data models to initially design the database, but from that point the DBA handles all the maintenance. • YIKES!

  16. Roles and Responsibilities • In IT • Project Manager • Business Analyst • Requirements Analyst • Architect – System, Data, Infrastructure • Developer – Tech lead, Coder • Data Analyst • Database Administrator • What is our collective goal?

  17. Roles and Responsibilities • In Business • Executive • Project Champion • Business Liaison • Subject Matter Expert • Data Steward / Owner • Not a “user” to be found • What “languages” do they “speak”?

  18. Effective Communication • (All that to get to this, it had better be good) • Unfortunately, this is pretty simple stuff,but often overlooked • First, our job in IT is to support the business • If we get caught up in being “gate keepers”, the business will jump the fence • Saying “NO” without something positive causes frustration • Focus on enabling, not on “disabling”

  19. Effective Communication • Second, the business can get along just fine without us • Can you say “outsource”? I knew you could • They had a business process before they came to us • They might be coming to IT because they were told to, not because they wanted to • Be a participant in solving their problems • Add value to their business (easy, huh)

  20. Effective Communication • Finally, educate yourself • Basic communication skills – presenting, organizing, researching, etc • Know the business – not just the IT part;get to know as much as you can (immersion) • Know your job – data management trends, data modeling techniques, corporate decisions, etc

  21. Summary • Data Management • There are a number of styles and notations • Establish corporate standards • Pick appropriate style/form • Need tools that can “tie it all together” • Roles and Responsibilities • Enable, assist, support, add value • Communicate, don’t just talk

  22. Discussion • What do you think?

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