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NEW QUESTION: 1
SCENARIO
Please use the following to answer the next question:
Anna and Frank both work at Ontario University. Anna is a lawyer responsible for data protection, while Frank is a lecturer in the engineering department. The University maintains a number of types of records:
* Student records, including names, student numbers, home addresses, pre-university information, university attendance and performance records, details of special educational needs and financial information.
* Staff records, including autobiographical materials (such as curricula, professional contact files, student evaluations and other relevant teaching files).
* Alumni records, including birthplaces, years of birth, dates of matriculation and conferrals of degrees.
These records are available to former students after registering through Ontario's Alumni portal.
Department for Education records, showing how certain demographic groups (such as first-generation students) could be expected, on average, to progress. These records do not contain names or identification numbers.
* Under their security policy, the University encrypts all of its personal data records in transit and at rest.
In order to improve his teaching, Frank wants to investigate how his engineering students perform in relational to Department for Education expectations. He has attended one of Anna's data protection training courses and knows that he should use no more personal data than necessary to accomplish his goal. He creates a program that will only export some student data: previous schools attended, grades originally obtained, grades currently obtained and first time university attended. He wants to keep the records at the individual student level. Mindful of Anna's training, Frank runs the student numbers through an algorithm to transform them into different reference numbers. He uses the same algorithm on each occasion so that he can update each record over time.
One of Anna's tasks is to complete the record of processing activities, as required by the GDPR. After receiving her email reminder, as required by the GDPR. After receiving her email reminder, Frank informs Anna about his performance database.
Ann explains to Frank that, as well as minimizing personal data, the University has to check that this new use of existing data is permissible. She also suspects that, under the GDPR, a risk analysis may have to be carried out before the data processing can take place. Anna arranges to discuss this further with Frank after she has done some additional research.
Frank wants to be able to work on his analysis in his spare time, so he transfers it to his home laptop (which is not encrypted). Unfortunately, when Frank takes the laptop into the University he loses it on the train. Frank has to see Anna that day to discuss compatible processing. He knows that he needs to report security incidents, so he decides to tell Anna about his lost laptop at the same time.
Anna will find that a risk analysis is NOT necessary in this situation as long as?
A. The data subjects are no longer current students of Frank's
B. The algorithms that Frank uses for the processing are technologically sound
C. The data subjects gave their unambiguous consent for the original processing
D. The processing will not negatively affect the rights of the data subjects
Answer: C

NEW QUESTION: 2
Examine this PeopleCode snippet:
&SQL = CreateSQL("Select %EffDtCheck(EFFDT) from %Table(PSU_INSTR_TBL)");
Select the correct option.
A. The statement is not valid. The correct syntax is:
&SQL = CreateSQL("Select %CurrDate(EFFDT) from %Table(PSU_INSTR_TBL)");
B. The statement is not valid. The correct syntax is:
&SQL = CreateSQL("Select %DateOut(EFFDT) from %Table(PSU_INSTR_TBL)");
C. The statement is valid.
D. The statement is not valid. The correct syntax is:
&SQL = CreateSQL("Select %Current(EFFDT) from %Table(PSU_INSTR_TBL)");
E. The statement is not valid. The correct syntax is:
&SQL = CreateSQL("Select %DateIn(EFFDT) from %Table(PSU_INSTR_TBL)");
F. The statement is not valid. The correct syntax is:
&SQL = CreateSQL("Select %Date(EFFDT) from %Table(PSU_INSTR_TBL)");
Answer: B

NEW QUESTION: 3
You are designing a data warehouse for a fresh food distribution business that stores sales by individual product. It stores sales targets by product category. Products are classified into subcategories and categories.
Each product is included in only a single product subcategory, and each subcategory is included in only a single category.
The data warehouse will be a data source for an Analysis Services cube.
The data warehouse contains two fact tables:
* factSales, used to record daily sales by product
* factProductTarget, used to record the monthly sales targets by product category Reports must be developed against the warehouse that reports product sales by product, category and subcategory, and product sales targets.
You need to design the product dimension. The solution should use as few tables as possible while supporting all the requirements.
What should you do?
A. Create three product tables, dimProduct, dimProductCategory, and dimProductSubcategory, and a fourth bridge table that joins products to their appropriate category and subcategory table records with foreign key constraints. Direct the cube developer to use key granularity attributes.
B. Create two product tables, dimProduct and dimProductCategory. Connect factSales to dimProduct and factProductTarget to dimProductCategory with foreign key constraints.
Direct the cube developer to use key granularity attributes.
C. Create one product table, dimProduct, which contains product detail, category, and subcategory columns. Connect factSales to dimProduct with a foreign key constraint. Direct the cube developer to use a non-key granularity attribute for factProductTarget.
D. Create three product tables, dimProduct, dimProductCategory, and dimProductSubcategory. Connect factSales to all three product tables and connect factProductTarget to dimProductCategory with foreign key constraints. Direct the cube developer to use key granularity attributes.
Answer: C