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| Question | Answer |
| What does ACID stand for? | Atomicity - All or nothing of transaction is completed. Consistency - DB transforms from one consistent state to another Isolation - Incomplete transactions not visible to other transactions Durability - Effects of committed Transactions are permanent |
| What are the three levels of ANSI-SPARC? | 1) External Level 2) Conceptual Level 3) Internal Level |
| What is the external view of ANSI-SPARC? | It is the users view of the database and it describes the part of the database that is relevant to a particular user. |
| What is the Conceptual level of ANSI-SPARC? | It is the community view of the database. It describes what data is stored in the database and the relationships amongst the data. |
| What is the Internal level of ANSI-SPARC? | The physical representation of the data on the computer. Describes how the data is stored in the database |
| What are the functions of a DBMS? | 1) Data Storage, Retrieval and Update 2) A User-Accessible Catalogue 3) Transaction Support 4) Concurrency Control Services 5) Recovery Services 6) Authorisation Services 7) Support for Data Communication 8) Integrity Services 9) Services to promote Data Independence 10) Utility Services |
| What is a Transaction? | A transaction is an action, or series of actions, carried out by a user or application program, which accesses or changes content to a database. |
| What is Concurrency Control? | Concurrency Control is the process of managing simultaneous operations on the database without having interference between them. |
| What is the purpose of a Concurrency Control Protocol? | The purpose of a Concurrency Control Protocol is to schedule transactions to avoid interference. |
| What is Serialisability? | Non-serial schedules that allow transactions to execute concurrently, without interference, producing the same database state as a serial schedule. |
| Shared Lock | A transaction can read the item but not update it. |
| Exclusive Lock | A transaction can both read and update the item. |
| What is the 2-Phase Locking (2PL) protocol rationale? | 2PL protocol is a concurrency control protocol that guarantees serialisability. The rationale is : 1) All locking operations precede the first unlock operation in a transaction. 2) Growing Phase - All locks acquired, none released. 3) Shrinking Phase - locks released, no new locks acquired. |
| What are the rules of 2PL? | 1) Transaction must acquire lock on an item before operating on it. 2) Once a transaction releases a lock, it can never acquire any new locks. 3) Upgrading of the locks takes place in the growing phase. 4) Downgrading of the locks takes place only during the shrinking phase. |
| What is a Deadlock? | Deadlock is the case when two, or more, transactions are waiting for locks held by each other to be released. |
| What is a Deferred Update? | It is a recovery technique in which updates are not written to the database until after a transaction has reached its commit point. If the transaction fails before the commit, it will not have modified the database and so no undoing of changes is required. However, it may be necessary to redo the updates of committed transactions as their effect may not have reached the database. |
| What is Shadow Paging? | Shadow Paging is a recovery technique in which two page tables are maintained during the lifetime of a transaction, the current page and the shadow page. When the transaction starts, the two pages are the same and during the transaction the current page records all updates to the database while the shadow page stays the same. When the transaction completes, the current page table becomes the shadow page while in the event of failure the shadow page is used to restore the database. |
| What is query decomposition? | Query Decomposition is the process of transforming a high-level query into Relational Algebra to check whether that query is syntactically and semantically correct. |
| What is Query Optimisation? | Query Optimisation is the selection of the order in which operations are to be performed so as to minimise resource usage, which usually is the disk accesses. |
| When does the 4th NF occur? | Occurs when there is a dependency between attributes (for example, A, B, and C) in a table, such that for each value of A there is a set of values for B and a set of values for C. However, set of values for B and C are independent of each other. So, there is multi-valued dependency (MVD). |
| What is the Lossless-Join property? | It is the property to find any instance of the original table from the corresponding instances in the smaller tables. |
| Dependency Preservation | A property of normalisation which enforces a constraint on the original table by enforcing constraints on each of the smaller tables. |
| Six (6) Denormalisation Targets | – combine 1:1 relationships – duplicate non-key attributes in 1:* relationships to reduce joins – duplicate foreign key attributes in 1:* relationships to reduce joins – introduce repeating groups – merge lookup tables with base tables – create extract tables |
| Types of Entity Constraint | 1) Required Data 2) Domain Constraints 3) Entity Integrity 4) Referential Integrity 5) Enterprise Integrity |
| View Resolution | Refers to how a query on a view in handled |
| OLAP | OnLine Analytical Processing |
| OLTP | OnLine Transaction Processing |
| Idea behind Data Warehousing? | Separating OLAP from OLTP because it can lead to delays. |
| Data Warehousing | Data Warehousing can be defined as a collection of methods, technologies and tools to assist the so-called "knowledge worker" to conduct data analysis aimed at implementing decision-making processes. |
| What is a Fact? | It is a point of interest for decision making. |
| What are Measures? | They are continuously valued (typically numerical) attributes which describe a fact from different points of view. |
| What are Dimensions? | They are discrete attributes which determine the minimum granularity adopted to represent facts |
| What are Hierarchies? | They contain dimension attributes (levels, parameters) connected in a tree-like structure by many-to-one relationships (functional dependencies). |
| Roll-Up | The roll-up operator causes an increase in data aggregation and removes a detail level from a hierarchy. |
| Drill-Down | The drill-down operator is the complement to the roll-up operator. |
| Slicing | We define slicing as an operation that reduces the number of cube dimensions after setting one of the dimensions to a specific value. |
| Dicing | Dicing is an operation that reduces the set of data being analyzed by a selection criterion |
| Pivot | The pivot operator implies a change in layouts and it aims at analysing a set of information from a different viewpoint. |
| Drill-Across | The term drill-across stands for the opportunity to create a link between two or more interrelated cubes in order to compare their data. |
| Drill-Through | This operation switches from multidimensional aggregate data in data marts to operational data in sources or in the reconciled layer. |
| Holdout | A method for deriving the accuracy of an classifier where the data is split into two independent sets, the training set (2/3 of data) and the test set (1/3 of data). |
| k-fold Cross Validation | A technique for estimating the accuracy of classifier by partitioning the dataset into k sets (folds). In the ith iteration, the ith set is used as the test set while the rest as the training sets. This way all sets become the training sets k-1 times and the test set 1 time. |
| Cluster | A collection of objects that are similar to each other and dissimilar to objects in other clusters. |
| Hibernate | – an object relational mapping library for Java. – a framework for mapping an object oriented domain model to a traditional relational database. |
| Semi-Structured Data | Data that does not conform to fixed external schema. |
| FLWOR | FLWOR expression (Flower) starts with one or more FOR or LET clauses in any order, followed by optional WHERE clause, optional ORDER BY clause, and required RETURN clause. |
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