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What happens when it changes?","back":"Every duplicate email copy must be updated.","mcqOptions":[{"text":"Every duplicate email copy must be updated.","correct":true,"explanation":"A flat file has no single linked customer record, so all five copies must be changed. Missing one copy creates inconsistent customer information."},{"text":"Only the most recent email copy must be updated.","correct":false,"explanation":"Changing only the newest record leaves four outdated values. Every duplicate email copy must be updated because each CSV record stores its own independent value."},{"text":"The first email copy automatically updates the others.","correct":false,"explanation":"This assumes the repeated values are linked, but a flat-file CSV provides no automatic relationship between them. Every duplicate email copy must be updated separately."},{"text":"A new email column must be added to each record.","correct":false,"explanation":"Adding another column would increase redundancy rather than correct the existing data. Every duplicate email copy must instead be updated to keep the records consistent."}]},{"id":"aa6607bc-103e-4ada-8cb5-748a9128c582","cardType":"basic","points":2,"front":"How does a relational database reduce duplicated customer details?","back":"Store customer details once in a separate linked table.","mcqOptions":[{"text":"Store customer details once in a separate linked table.","correct":true,"explanation":"A customer table stores one copy of each customer’s details, while orders refer to that record using a key. This reduces redundancy and update anomalies."},{"text":"Store customer details repeatedly in the orders table.","correct":false,"explanation":"Repeating the details in every order preserves the duplication found in a flat file. Customer details should be stored once in a separate linked table."},{"text":"Store customer details once in a single CSV field.","correct":false,"explanation":"Combining details in one field violates atomic data principles and does not create a relational structure. They should be stored once in a separate linked table."},{"text":"Store customer details in a separate unlinked table.","correct":false,"explanation":"An unlinked table would not let orders reliably identify their customers. The customer details must be stored once in a separate linked table."}]},{"id":"98f34e91-734e-42bd-b697-6b9d4b387ef8","cardType":"basic","points":1,"front":"Which key uniquely identifies each record and should not be empty?","back":"Primary key.","mcqOptions":[{"text":"Primary key.","correct":true,"explanation":"A primary key uniquely identifies every record in a table and must contain a value, so duplicate and null primary-key values are not permitted."},{"text":"Foreign key.","correct":false,"explanation":"A foreign key links to a key in another table and may contain repeated values. A primary key uniquely identifies each record and cannot be empty."},{"text":"Secondary key.","correct":false,"explanation":"A secondary key supports searching or sorting but need not uniquely identify records. The non-empty unique identifier for each record is the primary key."},{"text":"Composite key.","correct":false,"explanation":"A composite key is specifically formed from multiple fields, rather than naming the general role described. The key that uniquely identifies each record is the primary key."}]},{"id":"e2b0ddbf-e973-4e9e-9354-218cfdf4cc96","cardType":"basic","points":1,"front":"Which key stores a value matching another table's primary key?","back":"Foreign key.","mcqOptions":[{"text":"Foreign key.","correct":true,"explanation":"A foreign key stores values that refer to a primary key in another table, creating a relationship between records in the two tables."},{"text":"Primary key.","correct":false,"explanation":"A primary key uniquely identifies records within its own table. The field that matches another table’s primary-key values is a foreign key."},{"text":"Secondary key.","correct":false,"explanation":"A secondary key is used mainly for searching or sorting and does not define the link described. A foreign key matches another table’s primary key."},{"text":"Candidate key.","correct":false,"explanation":"A candidate key is any field or field combination capable of uniquely identifying records. A foreign key stores values matching another table’s primary key."}]},{"id":"796c1202-03b6-4a67-8787-d048b449ba71","cardType":"basic","points":1,"front":"A field is used for searching or sorting but is not the primary key. Which key is it?","back":"Secondary key.","mcqOptions":[{"text":"Secondary key.","correct":true,"explanation":"A secondary key is an additional field used to access, search or sort records without serving as the table’s unique primary identifier."},{"text":"Primary key.","correct":false,"explanation":"The question states that the field is not the primary key. A non-primary field used for searching or sorting is a secondary key."},{"text":"Foreign key.","correct":false,"explanation":"A foreign key creates a relationship by matching a key in another table. A field used for searching or sorting is a secondary key."},{"text":"Composite key.","correct":false,"explanation":"A composite key combines two or more fields to identify a record. The field described is instead a secondary key used for searching or sorting."}]},{"id":"6a36a105-e919-400e-b0c2-0c6e192a186b","cardType":"cloze","points":null,"front":"Indexes usually make [ ] faster, but can make [ ] slower.","back":"Indexes usually make reading faster, but can make writing slower.","mcqOptions":[{"text":"Indexes usually make reading faster, but can make writing slower.","correct":true,"explanation":"An index provides a quicker route to matching records during reads, but inserts and updates can be slower because the index must also be maintained."},{"text":"Indexes usually make reading faster, but can make writing faster.","correct":false,"explanation":"The first effect is correct, but writing does not usually become faster because each change may require index updates. Indexes make reading faster but can make writing slower."},{"text":"Indexes usually make reading slower, but can make writing slower.","correct":false,"explanation":"Index maintenance can slow writes, but indexes are created to speed up record retrieval rather than slow it. They usually make reading faster and writing slower."},{"text":"Indexes usually make writing faster, but can make reading slower.","correct":false,"explanation":"This reverses both usual effects. Indexes accelerate reading by avoiding full-table searches, while maintaining those indexes can add overhead and make writing slower."}]},{"id":"617f9aa2-03f2-4745-ad49-205e09378fbe","cardType":"cloze","points":null,"front":"An [ ] is a thing you store data about; an [ ] is a property of it.","back":"An entity is a thing you store data about; an attribute is a property of it.","mcqOptions":[{"text":"An entity is a thing you store data about; an attribute is a property of it.","correct":true,"explanation":"An entity represents something of interest, such as a customer, while attributes describe its properties, such as the customer’s name or email address."},{"text":"An attribute is a thing you store data about; an entity is a property of it.","correct":false,"explanation":"This swaps the two definitions. An entity is the thing represented in the database, while an attribute is a property that describes that entity."},{"text":"An index is a thing you store data about; an attribute is a property of it.","correct":false,"explanation":"An index is a lookup structure used to improve retrieval speed, not the thing being modelled. An entity is the thing, and an attribute is its property."},{"text":"An entity is a thing you store data about; an operation is a property of it.","correct":false,"explanation":"An operation is an action performed on data rather than a stored property. An entity is the thing represented, and an attribute describes one of its properties."}]},{"id":"6c7d6b8a-93ef-4170-8894-401bd54a3ea6","cardType":"basic","points":1,"front":"How is a many-to-many relationship usually resolved in an ER model?","back":"Add a linking table / associative entity.","mcqOptions":[{"text":"Add a linking table / associative entity.","correct":true,"explanation":"A linking table converts the many-to-many relationship into two one-to-many relationships, usually storing foreign keys that refer to both original entities."},{"text":"Add a single foreign key to either entity.","correct":false,"explanation":"One foreign key can represent only one related record per row, so it cannot fully model both sides of a many-to-many relationship. A linking table is required."},{"text":"Add a second primary key to one entity.","correct":false,"explanation":"Adding another primary key does not record all combinations between the entities and may violate key rules. The relationship should be resolved with a linking table."},{"text":"Merge both entities into a single table.","correct":false,"explanation":"Merging distinct entities would duplicate data and mix different record types. A linking table should instead connect the entities through two one-to-many relationships."}]},{"id":"19182dd7-3ba6-4449-a646-50d84bf53b39","cardType":"cloze","points":null,"front":"[ ] uses queries, filters and searches; [ ] transfers data between systems.","back":"Selecting data uses queries, filters and searches; exchanging data transfers data between systems.","mcqOptions":[{"text":"Selecting data uses queries, filters and searches; exchanging data transfers data between systems.","correct":true,"explanation":"Selecting data retrieves particular records or fields through queries, filters and searches, while exchanging data concerns transferring data between different systems."},{"text":"Sorting data uses queries, filters and searches; exchanging data transfers data between systems.","correct":false,"explanation":"Sorting changes the order in which data is presented rather than retrieving data through queries, filters and searches. The correct first term is Selecting data."},{"text":"Selecting data uses queries, filters and searches; validating data transfers data between systems.","correct":false,"explanation":"Validating data checks that input satisfies specified rules; it does not describe transferring data between systems. The correct second term is exchanging data."},{"text":"Backing up data uses queries, filters and searches; encrypting data transfers data between systems.","correct":false,"explanation":"Backing up data creates a recoverable copy, while encrypting data protects confidentiality. Queries, filters and searches select data, and transfers between systems exchange data."}]},{"id":"16f848fc-bb74-4bd6-b2ef-24b436cdb058","cardType":"cloze","points":null,"front":"Normalisation organises data into tables to reduce [ ] and improve [ ].","back":"Normalisation organises data into tables to reduce redundancy and improve data integrity.","mcqOptions":[{"text":"Normalisation organises data into tables to reduce redundancy and improve data integrity.","correct":true,"explanation":"Normalisation separates data into appropriately related tables, reducing repeated data and helping ensure that stored values remain accurate and consistent."},{"text":"Normalisation organises data into tables to reduce relationships and improve data integrity.","correct":false,"explanation":"Normalisation may increase the number of tables rather than reduce their relationships. Its purpose is to reduce redundancy and improve data integrity."},{"text":"Normalisation organises data into tables to reduce redundancy and improve data independence.","correct":false,"explanation":"Data independence is a separate database concept concerning separation between data and programs. Normalisation primarily improves data integrity by reducing redundancy and dependency problems."},{"text":"Normalisation organises data into tables to reduce validation and improve data duplication.","correct":false,"explanation":"Normalisation does not aim to reduce validation or improve duplication. It reduces redundancy, meaning unnecessary repetition, and improves data integrity."}]},{"id":"bc5734da-5b5d-4cf5-8eff-819fe843fd4b","cardType":"basic","points":2,"front":"A field ProductsOrdered contains P01, P02, P07. What 1NF fix is needed?","back":"Use one product per row with atomic fields.","mcqOptions":[{"text":"Use one product per row with atomic fields.","correct":true,"explanation":"First normal form requires every field to contain one atomic value. Storing each ordered product in its own row removes the repeating list from the field."},{"text":"Use one product per column with atomic fields.","correct":false,"explanation":"Using one product per column creates a repeating group and imposes an arbitrary product limit. First normal form requires one product per row with atomic fields."},{"text":"Use one comma-separated list with atomic fields.","correct":false,"explanation":"Changing the separator leaves several product identifiers in one field, so the value remains non-atomic. The 1NF fix is one product per row."},{"text":"Use one calculated product field with atomic fields.","correct":false,"explanation":"A calculated field does not remove the multi-valued product list and therefore does not establish atomicity. Each product must instead occupy a separate row."}]},{"id":"160563b4-a5a6-4263-9592-fdb864e0dc36","cardType":"basic","points":2,"front":"In a composite-key table, an attribute depends only on ProductID. What must happen for 2NF?","back":"Move it to a separate Product table.","mcqOptions":[{"text":"Move it to a separate Product table.","correct":true,"explanation":"Dependence on only part of a composite key is a partial dependency. Moving the attribute to a Product table where ProductID is the key establishes 2NF."},{"text":"Keep it in the existing composite-key table.","correct":false,"explanation":"Leaving the attribute in the composite-key table preserves its partial dependency on ProductID. It must be moved to a separate Product table."},{"text":"Copy it to a second composite-key column.","correct":false,"explanation":"Duplicating the attribute increases redundancy and does not remove its partial dependency. For 2NF, place it once in a separate Product table."},{"text":"Move it to a separate Order table.","correct":false,"explanation":"An Order table is inappropriate because the attribute depends on ProductID, not OrderID. It belongs in a separate Product table."}]},{"id":"7550285c-8b25-49ce-96b9-8eb29b32675d","cardType":"basic","points":2,"front":"If CustomerID determines CustomerName in an order table, what 3NF issue exists?","back":"A transitive dependency: non-key depends on non-key.","mcqOptions":[{"text":"A transitive dependency: non-key depends on non-key.","correct":true,"explanation":"If the order’s key determines CustomerID, which then determines CustomerName, the name depends indirectly on the key through another non-key attribute."},{"text":"A partial dependency: non-key depends on part-key.","correct":false,"explanation":"A partial dependency occurs when an attribute depends on only part of a composite key. Here CustomerName depends on non-key CustomerID, creating a transitive dependency."},{"text":"A functional dependency: non-key depends on primary-key.","correct":false,"explanation":"A functional dependency is a broad relationship and does not identify the specific 3NF violation. A non-key attribute determining another non-key attribute is a transitive dependency."},{"text":"A repeating group: multiple values occupy one field.","correct":false,"explanation":"A repeating group violates 1NF by storing multiple values in a field. This 3NF issue is instead a transitive dependency between non-key attributes."}]},{"id":"5001b0c5-eef2-42d8-8654-02f9d8a1ed0c","cardType":"cloze","points":null,"front":"In 3NF, data should depend on the [ ], the [ ], and nothing but the key.","back":"In 3NF, data should depend on the key, the whole key, and nothing but the key.","mcqOptions":[{"text":"In 3NF, data should depend on the key, the whole key, and nothing but the key.","correct":true,"explanation":"The phrase summarises normalisation: attributes depend on a key for 1NF, the whole composite key for 2NF, and no non-key attribute for 3NF."},{"text":"In 3NF, data should depend on the primary key, the whole key, and nothing but the key.","correct":false,"explanation":"Restricting the statement to the primary key misses that candidate keys can determine attributes. The established summary is the key, the whole key, and nothing but the key."},{"text":"In 3NF, data should depend on the key, the partial key, and nothing but the key.","correct":false,"explanation":"Depending on only part of a composite key is a partial dependency and violates 2NF. Data must depend on the whole key."},{"text":"In 3NF, data should depend on the foreign key, the non-key field, and nothing but the key.","correct":false,"explanation":"Foreign keys represent relationships and non-key fields are attributes, but neither completes the normalisation rule. The required terms are key and whole key."}]},{"id":"933bb8f3-1dda-45cb-b1d6-190a133948ca","cardType":"basic","points":1,"front":"In an OrderLine table with one row per product on an order, what primary key is likely?","back":"Composite key: OrderID + ProductID.","mcqOptions":[{"text":"Composite key: OrderID + ProductID.","correct":true,"explanation":"Neither identifier alone uniquely identifies an order line, but their combination identifies a particular product on a particular order, making a composite primary key appropriate."},{"text":"Primary key: OrderID only.","correct":false,"explanation":"An order can contain several products, so OrderID alone cannot uniquely identify each order-line row. The likely key combines OrderID and ProductID."},{"text":"Primary key: ProductID only.","correct":false,"explanation":"A product can appear on many different orders, so ProductID alone is not unique in the table. The likely composite key also includes OrderID."},{"text":"Composite key: ProductID + Quantity.","correct":false,"explanation":"Adding quantities does not form a stable identifier because quantities can repeat or change. The natural composite key is OrderID combined with ProductID."}]},{"id":"ef0c2be7-81a9-40b1-b567-4115fc357bf1","cardType":"basic","points":1,"front":"What does SELECT * return?","back":"All fields.","mcqOptions":[{"text":"All fields.","correct":true,"explanation":"The asterisk is SQL shorthand for every column in the selected table or joined result. The query still returns only rows permitted by any conditions."},{"text":"All records.","correct":false,"explanation":"The asterisk selects columns, not every database row regardless of conditions. SELECT * means all fields for the rows returned by the query."},{"text":"Primary-key fields.","correct":false,"explanation":"Primary-key fields are not specially selected by the asterisk. It expands to all fields in the table or query result."},{"text":"Non-null fields.","correct":false,"explanation":"SQL does not interpret the asterisk as selecting only populated columns. SELECT * requests all fields, including fields containing NULL."}]},{"id":"b79fae3f-25e8-40bf-9ba9-066ebfdddcb4","cardType":"cloze","points":null,"front":"LIKE 'A%' matches values [ ]; LIKE '%USB%' matches values [ ].","back":"LIKE 'A%' matches values starting with A; LIKE '%USB%' matches values containing USB.","mcqOptions":[{"text":"LIKE 'A%' matches values starting with A; LIKE '%USB%' matches values containing USB.","correct":true,"explanation":"The % wildcard represents any sequence of characters. After A it permits any ending, while surrounding USB with wildcards permits characters before and after USB."},{"text":"LIKE 'A%' matches values ending with A; LIKE '%USB%' matches values starting with USB.","correct":false,"explanation":"This reverses the positions of the wildcards. The first pattern requires A at the start, while the second finds USB anywhere within a value."},{"text":"LIKE 'A%' matches values containing A; LIKE '%USB%' matches values ending with USB.","correct":false,"explanation":"A trailing % allows any characters after A, not before it. Wildcards on both sides of USB mean it may occur anywhere, not only at the end."},{"text":"LIKE 'A%' matches values starting with one A; LIKE '%USB%' matches values equal to USB.","correct":false,"explanation":"The % symbol does not represent exactly one character; that role is normally served by an underscore. These patterns match values starting with A and containing USB, respectively."}]},{"id":"0260fa4b-7cfc-4cf2-89f6-608e0042f152","cardType":"basic","points":1,"front":"What does a nested SELECT use from the inner query?","back":"The inner query result is used by the outer query.","mcqOptions":[{"text":"The inner query result is used by the outer query.","correct":true,"explanation":"A nested SELECT evaluates the inner query first, then supplies its resulting value or set of values for use by the surrounding outer query."},{"text":"The outer query result is used by the inner query.","correct":false,"explanation":"This reverses the direction of evaluation. The inner query runs first, and its result is passed to the outer query to complete the overall statement."},{"text":"The inner query statement is used by the outer query.","correct":false,"explanation":"A nested query does not pass its SQL source text to the outer query. It executes and supplies the resulting value or set of values instead."},{"text":"The inner query field name is used by the outer query.","correct":false,"explanation":"The outer query uses data returned by the inner query, not merely its selected column name. That result may contain one value or a set of values."}]},{"id":"386d9edc-11aa-4e1e-bb6d-9d556df294e5","cardType":"basic","points":1,"front":"In OCR SQL, JOIN acts as an INNER JOIN. What rows are returned?","back":"Only matching rows are returned.","mcqOptions":[{"text":"Only matching rows are returned.","correct":true,"explanation":"An INNER JOIN includes a row only where the join condition finds a corresponding row in both tables, excluding unmatched rows from either table."},{"text":"All rows from both tables are returned.","correct":false,"explanation":"Including every row from both tables describes a FULL OUTER JOIN, not OCR's unqualified JOIN. An INNER JOIN returns only rows satisfying the join condition."},{"text":"All rows from the first table are returned.","correct":false,"explanation":"Preserving unmatched rows from the first table describes a LEFT OUTER JOIN. An INNER JOIN instead returns only rows with matches in both joined tables."},{"text":"Only non-matching rows are returned.","correct":false,"explanation":"Unmatched rows are excluded rather than selected by an INNER JOIN. It returns only rows for which the specified join condition is satisfied."}]},{"id":"238017cc-fd28-4841-8065-b5235f4efb99","cardType":"basic","points":3,"front":"How do DELETE and DROP differ in SQL?","back":"

DELETE removes records from a table.
DROP removes the whole table structure.

","mcqOptions":[{"text":"

DELETE removes records from a table.
DROP removes the whole table structure.

","correct":true,"explanation":"DELETE removes selected or all records while leaving the table available. DROP deletes the table definition itself, including its structure and associated stored data."},{"text":"

DELETE removes the whole table structure.
DROP removes records from a table.

","correct":false,"explanation":"The commands have been reversed. DELETE operates on records while retaining the table structure, whereas DROP removes the table definition and its stored contents."},{"text":"

DELETE removes columns from a table.
DROP removes records but keeps the table.

","correct":false,"explanation":"Removing columns is normally performed with ALTER TABLE, while clearing records does not describe DROP. DELETE removes records; DROP removes the entire table structure."},{"text":"

DELETE changes records in a table.
DROP removes selected table columns.

","correct":false,"explanation":"Changing record values is the purpose of UPDATE, and removing selected columns requires ALTER TABLE. DELETE removes records, whereas DROP removes the whole table structure."}]},{"id":"0ebfd915-2850-471a-8e04-5ef20ad36294","cardType":"basic","points":2,"front":"An order is inserted with CustomerID = 'C020', but no matching customer exists. What should the DBMS do?","back":"Reject it until the matching primary key exists.","mcqOptions":[{"text":"Reject it until the matching primary key exists.","correct":true,"explanation":"The order's foreign key must reference an existing customer primary key. Rejecting the insertion preserves referential integrity until customer C020 has been created."},{"text":"Accept it because the matching primary key is optional.","correct":false,"explanation":"A foreign-key constraint is not optional merely because the referenced record is absent. The DBMS should reject the order until the matching customer primary key exists."},{"text":"Create a customer with the matching primary key automatically.","correct":false,"explanation":"The DBMS must not invent a customer record to satisfy a relationship. It should reject the order until an explicitly inserted customer has the matching primary key."},{"text":"Replace the value with a NULL foreign key automatically.","correct":false,"explanation":"Silently changing C020 to NULL loses the intended relationship and is not how referential integrity is enforced. The insertion should be rejected until the matching primary key exists."}]},{"id":"52fef9bd-8048-4bec-898b-17460ef0b5f1","cardType":"cloze","points":null,"front":"ACID: [ ] means all-or-none; [ ] means valid state to valid state.","back":"ACID: Atomicity means all-or-none; Consistency means valid state to valid state.","mcqOptions":[{"text":"ACID: Atomicity means all-or-none; Consistency means valid state to valid state.","correct":true,"explanation":"Atomicity treats every transaction as an indivisible unit that fully succeeds or is rolled back. Consistency ensures constraints remain satisfied between valid database states."},{"text":"ACID: Consistency means all-or-none; Atomicity means valid state to valid state.","correct":false,"explanation":"The two properties have been swapped. Atomicity provides all-or-none execution, while consistency requires each completed transaction to take the database between valid states."},{"text":"ACID: Durability means all-or-none; Consistency means valid state to valid state.","correct":false,"explanation":"Durability concerns committed changes surviving failures, not all-or-none execution. Atomicity provides all-or-none behaviour, while consistency preserves database rules and valid states."},{"text":"ACID: Atomicity means all-or-none; Isolation means valid state to valid state.","correct":false,"explanation":"Isolation prevents concurrent transactions from interfering, rather than defining valid database states. Atomicity gives all-or-none execution, and consistency maintains validity across transactions."}]},{"id":"62c1bcba-d484-4b8a-b537-88f5f344f2ce","cardType":"cloze","points":null,"front":"ACID: [ ] stops concurrent transactions interfering; [ ] makes committed changes survive crashes.","back":"ACID: Isolation stops concurrent transactions interfering; Durability makes committed changes survive crashes.","mcqOptions":[{"text":"ACID: Isolation stops concurrent transactions interfering; Durability makes committed changes survive crashes.","correct":true,"explanation":"Isolation makes concurrent transactions behave as though executed separately. Durability ensures that once a transaction commits, its changes remain stored even after system failure."},{"text":"ACID: Durability stops concurrent transactions interfering; Isolation makes committed changes survive crashes.","correct":false,"explanation":"The properties have been reversed. Isolation controls interference between concurrent transactions, while durability protects committed changes against crashes and subsequent recovery."},{"text":"ACID: Atomicity stops concurrent transactions interfering; Durability makes committed changes survive crashes.","correct":false,"explanation":"Atomicity ensures that a transaction completes fully or is rolled back; it does not govern concurrent interference. Isolation prevents that interference, while durability preserves committed changes."},{"text":"ACID: Isolation stops concurrent transactions interfering; Consistency makes committed changes survive crashes.","correct":false,"explanation":"Consistency concerns maintaining constraints and valid states, not surviving a system failure. Isolation prevents concurrent interference, and durability ensures committed changes survive crashes."}]},{"id":"5ff3c951-0e1a-46fc-9205-002977b45179","cardType":"basic","points":2,"front":"How does a write lock help prevent a lost update?","back":"Other transactions cannot edit the record until commit or rollback.","mcqOptions":[{"text":"Other transactions cannot edit the record until commit or rollback.","correct":true,"explanation":"A write lock gives the transaction exclusive editing access to the record. Holding it until commit or rollback prevents another transaction overwriting an uncommitted update."},{"text":"Other transactions cannot read the record until commit or rollback.","correct":false,"explanation":"Blocking reads is not the key mechanism for preventing a lost update. The write lock must stop other transactions editing the record until commit or rollback."},{"text":"Other transactions can edit the record before commit or rollback.","correct":false,"explanation":"Allowing edits before the transaction finishes permits one update to overwrite another, causing the lost-update problem. Other transactions must be prevented from editing until commit or rollback."},{"text":"Other transactions cannot edit the record until the write finishes.","correct":false,"explanation":"Releasing the lock immediately after the write can expose an uncommitted change to competing updates. It must remain until the transaction commits or rolls back."}]},{"id":"c0a98b23-6311-498d-9add-a3101b2a210c","cardType":"basic","points":2,"front":"Why can controlled redundancy be useful?","back":"Extra copies improve recovery and availability.","mcqOptions":[{"text":"Extra copies improve recovery and availability.","correct":true,"explanation":"Controlled redundancy keeps selected duplicate data available as a backup. If one copy is lost or inaccessible, another can support recovery and continued service."},{"text":"Duplicate values remove consistency and integrity risks.","correct":false,"explanation":"Duplicating values creates additional consistency risks rather than eliminating them. The benefit of controlled redundancy is that extra copies improve recovery and availability when failures occur."},{"text":"Repeated data reduce storage and processing requirements.","correct":false,"explanation":"Redundant data requires more storage, not less, because the same information is retained in multiple places. Its value lies in improving recovery and availability."},{"text":"Additional records guarantee normalisation and data independence.","correct":false,"explanation":"Normalisation generally removes unnecessary duplication rather than relying on it. Controlled redundancy is useful because extra copies improve recovery and availability, not because they guarantee normalisation."}]}]}],"examCountdown":{"examDate":"2027-06-07","paperLabel":"Paper 1"},"heading":"Databases","title":"Databases Flashcards","topbar":{"backHref":"/a-level/computer-science/ocr/flashcards"},"topicSidebar":"$L38"}]}],"topicId":"d588179c-7b42-5c5a-b087-2ae7ad4b66e3","walled":"$L39"}],"$L3a","$L3b"]