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Geek Sync | Becoming a Better Data Modeler: Part 1 (Data Modeling Certification)

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You can watch the replay for this Geek Sync webcast, Becoming a Better Data Modeler: Part 1 (Data Modeling Certification)l, in the IDERA Resource Center, http://ow.ly/kNco50A4qO3.

As a data professional, you know that improving your data modeling skills will help you to increase your productivity and efficiency. And demonstrating your knowledge with a certification can enhance your marketability. In this Geek Sync webinar, Steve Hoberman will go through several sample questions to test your data modeling skills and help you prepare for taking the new Data Modeling Certification (DMC) exam. He’ll explain the answers for each question, with the goal of making you a better data modeler by the end of this session!

Speaker: Steve Hoberman has trained more than 10,000 people in data modeling since 1992. Steve is known for his entertaining and interactive teaching style (watch out for flying candy!), and organizations around the globe have brought Steve in to teach his Data Modeling Master Class, which is recognized as the most comprehensive data modeling course in the industry. Steve is the author of nine books on data modeling, including the bestseller Data Modeling Made Simple. One of Steve’s frequent data modeling consulting assignments is to review data models using his Data Model Scorecard® technique. He is the founder of the Design Challenges group, Conference Chair of the Data Modeling Zone conferences, and recipient of the Data Administration Management Association (DAMA) International Professional Achievement Award.

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Geek Sync | Becoming a Better Data Modeler: Part 1 (Data Modeling Certification)

  1. 1. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 1 Topics  Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Becoming a Better Data Modeler Part 1: Data Modeling Certification OCTOBER 10, 2019 Steve Hoberman me@stevehoberman.com www.SteveHoberman.com Why get certified? More skill, more people $$$ Proof Know what you don’t know
  2. 2. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 2 https://DataModelingInstitute.com/ About the DMC exam 90 minute exam 10 categories containing 100 subcategories containing 350 questions 1 question randomly chosen from each category Question sequence and answer choices random Must score at least 90 Internet, browser, web camera (if not at conference)
  3. 3. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 3 Process 1. Complete https://datamodelinginstitute.com/register/ 2. Start with Assessment to gauge skill level ($0) 3. Purchase ($199) 4. Schedule 5. Go (login, live proctor, cam) Or take DMC exam at DMZ (www.DataModelingZone.com) ERStudioIsAwesome gives 20% off registration! Passing and not passing • If you pass – Onsite certificate received immediately – Within 24 hours • Badge • DMC Wall of Fame • Registered in DB for verifications – Will receive certificate in mail within 3 weeks • If you do not pass – Second chance free – If do not pass second time, need to register and pay again
  4. 4. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 4 DMC exam taster Syntax Components (entities, relationships, attributes, keys, domains, subtypes) Process and approach Conceptual, logical, and physical Relational and dimensional Notations Abstraction Naming standards Definitions Best practices and pitfalls Syntax What is another name for a dependent entity? A. Weak. B. Outrigger. C. Junk. D. Meager. E. Supertype. F. Hub.
  5. 5. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 5 Syntax What is another name for a dependent entity? A. Weak. B. Outrigger. C. Junk. D. Meager. E. Supertype. F. Hub. Class Class Code Class Short Name (AK1:1) Class Long Name Class Full Description Text Student Grade Student ID (FK) Class Code (FK) Semester Code (FK) Final Grade Semester Semester Code Semester Short Name (AK1:1) Semester Long Name Student Student ID Student Last Name (AK1:1) Student First Name (AK1:2) Student Birth Date (AK1:3) Student Number (AK2:1) Student Shoe Size Student Favorite Ice Cream Flavor Name Candidate and foreign keys Student ID Class Code Semester Code Final Grade 44 M123 Fall14 C 44 M45 Sum14 B 32 B123 Spr13 B 44 C123 Win13 A
  6. 6. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 6 Syntax What acronym denotes a non-unique index? A. AK. B. PK. C. IE. D. UF. E. NU. F. FK. Syntax What acronym denotes a non-unique index? A. AK. B. PK. C. IE. D. UF. E. NU. F. FK.
  7. 7. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 7 CALENDAR PRODUCT GEOGRAPHY Month Month Sequence Number Year Code (FK) (AK1:2) Month Code (AK1:1) Month Name Sales Product Number (FK) Region Code (FK) Month Sequence Number (FK) Gross Sales Amount Region Region Code Country Code (FK) Region Name (AK1:1) Product Category Product Category Code Product Category Description Text (AK1:1) Product Line Product Line Code Product Category Code (FK) Product Line Name (AK1:1) Product Product Number Product Line Code (FK) Product Name (AK1:1) Product Frozen Indicator (AK1:2) (IE1:1) Product UPC Code (AK2:1) Product EAN Number (AK3:1) Country Country Code Country Name (AK1:1) Country ISO Code (AK2:1) Year Year Code Year Name Year Sequence Number (AK1:1) IndexingWhat was our Gross Sales Amount for all Frozen products from the NE in January 2019? Components How many candidate keys are on the following entity? A. Three. B. One. C. Two. D. Zero. E. Four. F. Five. Employee Employee ID Employee First Name (AK1:1) Employee Last Name (AK1:2) Employee Birth Date (AK1:3) Employee Number (AK2:1) Employee Start Date
  8. 8. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 8 Components How many candidate keys are on the following entity? A. Three. B. One. C. Two. D. Zero. E. Four. F. Five. Employee Employee ID Employee First Name (AK1:1) Employee Last Name (AK1:2) Employee Birth Date (AK1:3) Employee Number (AK2:1) Employee Start Date Components A Calendar dimension has been designed to be used by multiple applications. Calendar is what type of dimension? A. Degenerate. B. Junk. C. Mini. D. Conformed. E. Behavioral. F. Synched.
  9. 9. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 9 Components A Calendar dimension has been designed to be used by multiple applications. Calendar is what type of dimension? A. Degenerate. B. Junk. C. Mini. D. Conformed. E. Behavioral. F. Synched. Process and approach Which of the following statements does this model support? A. Account 123 is not owned by a Customer. B. Account 123 is owned by two Customers. C. Account 123 is owned by one Customer. D. Account 123 is identified by a Customer. Customer Account Own
  10. 10. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 10 Process and approach Which of the following statements does this model support? A. Account 123 is not owned by a Customer. B. Account 123 is owned by two Customers. C. Account 123 is owned by one Customer. D. Account 123 is identified by a Customer. Customer Account Own Customer Account Own Each Customer may own one or many Accounts. Each Account must be owned by one Customer. Example 1
  11. 11. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 11 Process and approach Which model supports these statements? Each Office must contain one or many Managers. Each Manager may be assigned to zero or one Office. A. B. C. Contain 0..1 1..*Office Manager Contain 1..* 0..1Office Manager Contain 1..1 1..*Office Manager Process and approach Which model supports these statements? Each Office must contain one or many Managers. Each Manager may be assigned to zero or one Office. A. B. C. Contain 1..* 0..1Office Manager Contain 0..1 1..*Office Manager Contain 1..1 1..*Office Manager
  12. 12. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 12 Conceptual, logical, and physical Which type of model would MOST LIKELY contain a many-to-many relationship? A. CDM. B. PDM. C. LDM. D. UDM. E. EDM. F. ADM. Conceptual, logical, and physical Which type of model would MOST LIKELY contain a many-to-many relationship? A. CDM. B. PDM. C. LDM. D. UDM. E. EDM. F. ADM.
  13. 13. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 13 Conceptual, logical, and physical Which type of model would MOST LIKELY contain a view? A. CDM. B. PDM. C. LDM. D. UDM. E. EDM. F. ADM. Conceptual, logical, and physical Which type of model would MOST LIKELY contain a view? A. CDM. B. PDM. C. LDM. D. UDM. E. EDM. F. ADM.
  14. 14. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 14 Relational and dimensional What is the LOWEST level of normalization violated on this model? A. 4NF. B. 3NF. C. BCNF. D. 2NF. E. 0NF. F. 1NF. Employee Employee ID Employee First Name (AK1:1) Employee Last Name (AK1:2) Employee Birth Date (AK1:3) Employee Number (AK2:1) Employee Phone Number 1 Employee Phone Number 2 Employee Phone Number 3 Employee Start Date Relational and dimensional What is the LOWEST level of normalization violated on this model? A. 4NF. B. 3NF. C. BCNF. D. 2NF. E. 0NF. F. 1NF. Employee Employee ID Employee First Name (AK1:1) Employee Last Name (AK1:2) Employee Birth Date (AK1:3) Employee Number (AK2:1) Employee Phone Number 1 Employee Phone Number 2 Employee Phone Number 3 Employee Start Date
  15. 15. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 15 Relational and dimensional What is the grain of this meter? A. Sales. B. Month Code. C. Product, Month, and Territory. D. Sales Amount. E. Sales Gross Amount and Sales Net Amount. F. Order Line. Sales Product Number Month Code Territory ID Sales Gross Amount Sales Net Amount Relational and dimensional What is the grain of this meter? A. Sales. B. Month Code. C. Product, Month, and Territory. D. Sales Amount. E. Sales Gross Amount and Sales Net Amount. F. Order Line. Sales Product Number Month Code Territory ID Sales Gross Amount Sales Net Amount
  16. 16. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 16 Notations What is a difference between IE and IDEF1X? A. IE cannot show weak entities. B. IDEFIX cannot show weak entities. C. IE cannot show overlapping subtypes. D. IDEF1X cannot show overlapping subtypes. E. IE cannot show associative entities. F. IDEF1X cannot show associative entities. Notations What is a difference between IE and IDEF1X? A. IE cannot show weak entities. B. IDEFIX cannot show weak entities. C. IE cannot show overlapping subtypes. D. IDEF1X cannot show overlapping subtypes. E. IE cannot show associative entities. F. IDEF1X cannot show associative entities.
  17. 17. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 17 Lecture Workshop Course Lecture Workshop Course IDEF1X subtyping Complete Incomplete Notations Which of the following is a fact-based modeling notation? A. FCO-IM. B. DV. C. UML. D. IE. E. IDEF1X. F. Barker.
  18. 18. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 18 Notations Which of the following is a fact-based modeling notation? A. FCO-IM. B. DV. C. UML. D. IE. E. IDEF1X. F. Barker. Abstraction A software vendor is modeling a product inventory application to sell to organizations across many different industries. Which of the following product models would work BEST? Product Raw Material Semi-Finished Good Finished Good Product Raw Material Semi-Finished Good Finished Good Contain Contain Contain Product Contain Product Relate with A B C D
  19. 19. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 19 Abstraction A software vendor is modeling a product inventory application to sell to organizations across many different industries. Which of the following product models would work BEST? Product Raw Material Semi-Finished Good Finished Good Product Raw Material Semi-Finished Good Finished Good Contain Contain Contain Product Contain A B C D Abstraction What is a role that a Party can play? A. Finished Product. B. Employee. C. Purchase Order. D. Arrival Time. E. Policy. F. Service.
  20. 20. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 20 Abstraction What is a role that a Party can play? A. Finished Product. B. Employee. C. Purchase Order. D. Arrival Time. E. Policy. F. Service. Naming standards Which of the following is NOT a valid attribute name? A. Employee Last Name. B. Employee Number. C. Employee ID. D. Employee First Name. E. Employee. F. Employee Middle Name.
  21. 21. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 21 Naming standards Which of the following is NOT a valid attribute name? A. Employee Last Name. B. Employee Number. C. Employee ID. D. Employee First Name. E. Employee. F. Employee Middle Name. Naming standards What is an example of camel case? A. Project_Start_Date. B. Project-Start-Date. C. Project Start Date. D. Project*Start*Date. E. Project,Start,Date. F. ProjectStartDate.
  22. 22. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 22 Naming standards What is an example of camel case? A. Project_Start_Date. B. Project-Start-Date. C. Project Start Date. D. Project*Start*Date. E. Project,Start,Date. F. ProjectStartDate. Definitions Which word makes this definition for Employee imprecise? An Employee is a person who works for our organization and often receives a salary. A. Person. B. Works. C. Often. D. Organization. E. Salary.
  23. 23. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 23 Definitions Which word makes this definition for Employee imprecise? An Employee is a person who works for our organization and often receives a salary. A. Person. B. Works. C. Often. D. Organization. E. Salary. Definitions “The Customer Identifier is the identifier for the customer” is what type of definition? A. Syllogism. B. Disjunctive. C. Validity. D. Pleonasm. E. Tautology. F. Inference.
  24. 24. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 24 Definitions “The Customer Identifier is the identifier for the customer” is what type of definition? A. Syllogism. B. Disjunctive. C. Validity. D. Pleonasm. E. Tautology. F. Inference. Best practices and pitfalls What is wrong with the following model? A. The foreign key is missing in Customer. B. The foreign key should be an inversion entry. C. Account should be a dependent entity. D. The foreign key should be composite. E. Customer should be a dependent entity. F. The foreign key should be required. Customer Customer Number NOT NULL Customer First Name NULL Customer Last Name NULL Account Account Code NOT NULL Customer Number (FK) NULL Account Open Date NULL Own
  25. 25. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 25 Best practices and pitfalls What is wrong with the following model? A. The foreign key is missing in Customer. B. The foreign key should be an inversion entry. C. Account should be a dependent entity. D. The foreign key should be composite. E. Customer should be a dependent entity. F. The foreign key should be required. Customer Customer Number NOT NULL Customer First Name NULL Customer Last Name NULL Account Account Code NOT NULL Customer Number (FK) NULL Account Open Date NULL Own F Driver Drive License Number NOT NULL Driver First Name NULL (AK1:1) Driver Last Name NOT NULL (AK1:2) Driver Birth Date NOT NULL (AK1:3) Vehicle Vehicle Identification Number NOT NULL Drive License Number (FK) NULL Vehicle Model Name NOT NULL Vehicle Series Name NOT NULL Drive Best practices and pitfalls What is wrong with this model? A. Foreign key is null yet relationship is mandatory. B. Foreign key is not null yet relationship is optional. C. You cannot have more than two attributes in an AK. D. One of the attributes in the AK is null. E. The foreign key should be part of the primary key.
  26. 26. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 26 Driver Drive License Number NOT NULL Driver First Name NULL (AK1:1) Driver Last Name NOT NULL (AK1:2) Driver Birth Date NOT NULL (AK1:3) Vehicle Vehicle Identification Number NOT NULL Drive License Number (FK) NULL Vehicle Model Name NOT NULL Vehicle Series Name NOT NULL Drive Best practices and pitfalls What is wrong with this model? A. Foreign key is null yet relationship is mandatory. B. Foreign key is not null yet relationship is optional. C. You cannot have more than two attributes in an AK. D. One of the attributes in the AK is null. E. The foreign key should be part of the primary key. Data Modeling Certification Why About Prepare Maintain Taste
  27. 27. DataModelingInstitute.com 10/10/2019 © Steve Hoberman Page 27 Topics  Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Becoming a Better Data Modeler Part 1: Data Modeling Certification OCTOBER 10, 2019 Steve Hoberman me@stevehoberman.com www.SteveHoberman.com

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