MC	Which statement is NOT CORRECT?	At the tactical level, decisions are made by middle management with a medium-term (e.g. a month, a quarter, a year) focus.	incorrect	At the strategic level, decisions are made by senior management with long term implications (e.g., 1, 2, 5 years or more)	incorrect	At the operational level, day to day business decisions are made, typically in real-time or with a short time frame.	incorrect	A data warehouse provides a centralized, consolidated data platform by integrating data from different sources and in different formats.  As such, it provides a separate and dedicated environment for operational decision making.	correct	
MC	Which statement is NOT CORRECT?	A fact constellation schema has more than one fact table.	incorrect	Relational OLAP (ROLAP) stores the data in a relational data warehouse, which can be implemented using a star, snowflake or fact constellation schema.	incorrect	At the operational level, day to day business decisions are made, typically in real-time or with a short time frame.	incorrect	In terms of data manipulation, a data warehouse focusses on Select/Update statements.	correct	
MC	In terms of data manipulation, a data warehouse focusses on...	Select/Update statements	incorrect	Insert/Update/Delete/Select statements	incorrect	Insert/Select statements	correct	Delete statements	incorrect	
MC	Which statement is NOT CORRECT?	Hybrid OLAP (HOLAP) tries to combine the best of both MOLAP and ROLAP.  An RDBMS can then be used to store the detailed data in a relational data warehouse whereas the pre-computed aggregated data can be kept as a multidimensional array managed by a MDBMS.	incorrect	Multidimensional OLAP (MOLAP) stores the multidimensional data using a Multidimensional DBMS (MDBMS) whereby the data is stored in a multi-dimensional array-based data structure optimized for efficient storage and quick access.	incorrect	MOLAP scales better to more dimensions than ROLAP.  The query performance may however be inferior to ROLAP unless some of the queries are materialized or high-performance indexes are defined.	correct	Relational OLAP (ROLAP) stores the data in a relational data warehouse, which can be implemented using a star, snowflake or fact constellation schema.	incorrect	
MC	Which statement is CORRECT?	In a fact constellation schema, more than one fact table is used.	correct	In a data warehouse context, an outrigger table can be defined to store a set of attribute types of a dimension table which are not correlated, high in cardinality and updated sequentially.	incorrect	Contrary to the RANK() OLAP function, the DENSE_RANK() OLAP function leaves gaps between the ranks.  	incorrect	A data lake assumes that data schema definitions are determined when the data are loaded (schema-on-write).	incorrect	
MC	Which statement is CORRECT?	In case of a data warehouse, the data schema definitions are only determined when the data is read (schema-on-read) whereas for data lakes it is fixed when the data is loaded (schema-on-write).	incorrect	A data lake is targeted towards decision makers at middle and top management level, whereas a data warehouse requires a data scientist, which is a more specialized profile in terms of data handling and analysis.	incorrect	A key distinguishing property of a data lake is that it stores raw data in its native format which could be structured, unstructured or semi-structured.	correct	A data lake is less agile compared to a data warehouse which has no structure.	incorrect	
MC	Which statement is NOT CORRECT?	Multidimensional OLAP (MOLAP) stores the multidimensional data using a Multidimensional DBMS (MDBMS) whereby the data is stored in a multi-dimensional array-based data structure optimized for efficient storage and quick access.	incorrect	Relational OLAP (ROLAP) stores the data in a relational data warehouse, which can be implemented using a star, snowflake or fact constellation schema.	incorrect	MOLAP scales better to more dimensions than ROLAP.  The query performance may however be inferior to ROLAP unless some of the queries are materialized or high-performance indexes are defined.	correct	Hybrid OLAP (HOLAP) tries to combine the best of both MOLAP and ROLAP.  An RDBMS can then be used to store the detailed data in a relational data warehouse whereas the pre-computed aggregated data can be kept as a multidimensional array managed by a MDBMS.	incorrect	
MC	Which statement is CORRECT?	During the ETL process, a staging area can be used to decrease the burden on the operational systems and the data warehouse.  This area can then be used to execute (complex) queries.	incorrect	An outrigger table can be defined to store a set of attribute types of a dimension table which are uncorrelated, high in cardinality and updated simultaneously.	incorrect	The ETL process is only executed right before the data warehouse is made operational.	incorrect	Some estimates state that the ETL step can consume up to 80% of all efforts needed to set up a data warehouse.	correct	
MC	Which statement is NOT CORRECT?	One way to deal with rapidly changing dimensions is by splitting the information into stable and rapidly changing information.  The latter can then be put into a separate mini-dimension table with a new surrogate key.  The connection can then be made by using the fact table or by introducing a new table connecting both.	incorrect	For slowly changing dimensions, surrogate keys can be handy to store the historical information by duplicating a record and adding, e.g., Start_Date, End_Date and Current_Flag attribute types.	incorrect	Junk dimensions can be defined to efficiently accommodate low cardinality attribute types such as flags or indicators.	incorrect	An outrigger table can be defined to store a set of attribute types of a dimension table which are uncorrelated, high in cardinality and updated simultaneously.	correct	
MC	Which statement is NOT CORRECT?	An outrigger table can be defined to store a set of attribute types of a dimension table which are uncorrelated, high in cardinality and updated simultaneously.	correct	Junk dimensions can be defined to efficiently accommodate low cardinality attribute types such as flags or indicators.	incorrect	One way to deal with rapidly changing dimensions is by splitting the information into stable and rapidly changing information.  The latter can then be put into a separate mini-dimension table with a new surrogate key.  The connection can then be made by using the fact table or by introducing a new table connecting both.	incorrect	For slowly changing dimensions, surrogate keys can be handy to store the historical information by duplicating a record and adding, e.g., Start_Date, End_Date and Current_Flag attribute types.	incorrect