DataWare Housing Glossary of Terms - 'T'

Table	a relation that consists of a set of columns with a heading and a set of rows.
Time Variant Data	data whose accuracy is relevant to some one moment in time.
Top down methodology	Involves in building a datawarehouse first and then building datamarts..
Transaction Processing	the activity of executing many short, fast running programs, providing the end user with consistent two or three second response time.
Transition Data	data possessing both primitive and derived characteristics; usually very sensitive to the running of the business.

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DataWare Housing Glossary of Terms - 'S'

Schema	The logical organization of data in a database.
Scope of Integration	the formal definition of the boundaries of the system being modelled.
Sequential File	a file in which records are ordered according to the values of one or more key fields.
Serial File	a sequential file in which records are physically adjacent, in sequential order.
Slowly Changing Dimensions	The approaches involving maintaining a list or history by adding related rows or new columns, or simply ignoring the problem by retaining the only the current data.Type I, Type II, Type III
Snowflake Schema	A snowflake schema is a set of tables comprised of a single, central fact table surrounded by normalized dimension hierarchies. Each dimension level is represented in a table. Snowflake schema implement dimensional data structures with fully normalized dimensions. Star schema are an alternative to snowflake schema.
Star Schema	A star schema is a set of tables comprised of a single, central fact table surrounded by de-normalized dimensions. Each dimension is represented in a single table. Star schema implement dimensional data structures with de-normalized dimensions. Snowflake schema are an alternative to star schema.
Surrogate Key	It has system-generated artificial primary key values, which allows to maintain historical records in the Data Warehouse more effectively.

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DataWare Housing Glossary of Terms - 'Q' & 'R'

Query Language

a language that enables an end user to interact directly with a DBMS to retrieve and possibly modify data managed under the DBMS.

Record	an aggregation of values of data organized by their relation to a common key.
Recovery	the restoration of the database to an original position or condition, often after major damage to the physical medium.
Redundancy	the practice of storing more than one occurrence of data.
Referential Integrity	the facility of a DBMS to ensure the validity of a predefined relationship.
Refresh	Refreshing a warehouse consists in propagating updates on source data to correspondingly update the base data and derived data stored in the warehouse. Two sets of issues to consider; when to refresh and how to refresh. Refresh policy is set by warehouse administrator, depends on user needs and traffic and may be different for different sources.
Replication	The physical copying of data from one database to another.
Reporting	The process of translating data to presentation formats via a pre-defined or ad-hoc queries.
ROLAP	Relational OLAP. Data warehouses that are implemented on standard or extended relational DBMSs,called Relational OLAP(ROLAP)servers.These servers assume that data is stored in relational databases.
Roll up	to increase or acquire by successive accumulations
Rolling Summary	a form of storing archival data where the most recent data has the lowest level of details stored ande the older datra has higher levels of details stored.

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DataWare Housing Glossary of Terms - 'P'

Parallel Data Orgnization	an arrangement of data in which the data is spread over independent storage devices and is managed independently.
Parallel Search Storage	a storage device in which one or more parts of all storage locations are queried simultaneously for a certain condition or under certain parameters.
Parsing	the algorithm that translates syntax into meaningful machine instructions. Parsing determines the meaning of statements issued in the data manipulation language.
Partition	a segmentation technique in which data is divided into physically different units. Partioning can be done at the application or the system level.
Performance	the length of time from the moment a request is issued until the first of the results of the request are received.
Periodic Discrete Data	a measurement or description of data taken at a regular time interval.
Prefix Data	data in a segment or a record used exclusively for system control, usually unavailable to the user.
Primitive Data	data whose existence depends on only a single occurance of a major subject area of the enterprise.
Privilege Descriptor	a persistent object used by a DBMS to enformce constraints on operations.
Projection	an operation that takes one relation as an operand and returns a second relation that consists of only the selected attributes or columns, with duplicate rows eliminated.
Proposition	a statement about entities that asserts or denies that some condition holds for those entities.

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DataWare Housing Glossary of Terms - 'O'

OLAP (On-Line Analytical Processing)	Describes the systems used not for application delivery, but for analyzing the business, e.g., sales forecasting, market trends analysis, etc. These systems are also more conducive to heuristic reporting and often involves multidimensional data analysis capabilities.
OLTP (OnLine Transaction Processing)	Describes the activities and systems associated with a company's day-to-day operational processing and data (order entry, invoicing, general ledger, etc.).
Operational Data Store (ODS)	the form that data warehouse takes in the operational environment. Operational data stores can be updated, do provide rapid and consistent time, and contain only a limited amount of historical data.
Overflow	the condition in which a record or a segment cannot be stored in its home because the address is already occupied.

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DataWare Housing Glossary of Terms - 'N'

Natural Join	a join in which the redundant logic components generated by the join are removed.
Network Model	a data model that provides data relationships on the basis of records or groups of records (ie. sets) in which one record is designated as the set owner, and a single member record can belong to one or more sets.
Nonprocedural Language	syntax that directs the computer as to what to do, not how to do it. Typical nonprocedural languages include RAMIS,FOCUS, NOMAD, and SQL.
Normalization	Normalization is a step-by-step process of removing redundancies and dependencies of attributes in a data structure. The condition of the data at completion of each step is described as a "normal form." Thus, when normalizing we talk about data as being in the first normal form, the second normal form, etc. Normalization theory identifies normal forms up to at least the fifth normal form, plus an adjunct form known as Boyce-Codd Normal Form (BCNF). The first three forms are sufficient to meet the needs of warehousing data models.

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DataWare Housing Glossary of Terms - 'M'

Main Storage Data Base (msdb)	a data base that resides entirely in main storage. Such data bases are very fast to access, but require special handling at the time of update. MSDB's can only manage a small amounts of data.
Maximum Transaction Arrival Rate (MTAR)	the rate of arrival of transactions at the moment of peak period processing.
MDDB	Multi Dimensional DataBase
Metadata or Meta Data	Metadata is data about data. Examples of metadata include data element descriptions, data type descriptions, attribute/property descriptions, range/domain descriptions, and process/method descriptions. The repository environment encompasses all corporate metadata resources: database catalogs, data dictionaries, and navigation services. Metadata includes things like the name, length, valid values, and description of a data element. Metadata is stored in a data dictionary and repository. It insulates the data warehouse from changes in the schema of operational systems.
Metadata Synchronization	The process of consolidating, relating and synchronizing data elements with the same or similar meaning from different systems. Metadata synchronization joins these differing elements together in the data warehouse to allow for easier access.
Metalanguage	a language used to specify other languages.
Methodology	A system of principles, practices, and procedures applied to a specific branch of knowledge.
Mid-Tier Data Warehouses	To be scalable, any particular implementation of the data access environment may incorporate several intermediate distribution tiers in the data warehouse network. These intermediate tiers act as source data warehouses for geographically isolated sharable data that is needed across several business functions.
Middleware	A communications layer that allows applications to interact across hardware and network environments.
Migration	the process by which frequently used items of data are moved to more readily accessible areas of storage and infrequently used items of data are moved to less readily accessible areas of storage.
MOLAP	OLAP on Multidimensional models. In MOLAP servers, Data warehouses directly store multidimensional data in special data structures(eg.,arrays) and implement the OLAP operations over these special data structures.
Multilist Organization	a chained file organization in which the chains are divided into fragments and each fragment is indexed. This organization of data permits faster access to the data.

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DataWare Housing Glossary of Terms - 'K' & 'L'

Key Compression A technique for reducing the number of bits in keys; used in making
indexes occupy less space.

Latency	is often used to mean any delay or waiting that increases real or perceived response time beyond the response time desired.
Load	After extracting, cleaning and transforming, data must be loaded into the warehouse. Additional preprocessing may still be required: checking integrity constraints; sorting; summarization, aggregation and other computation to build the derived tables stored in the warehouse; building indices and other access paths; and partitionaing to multiple target storage areas. Load utilities can be used for these operations.
Lockup	the event that occurs when update is done against a data base record and the transaction has not yet reached a commit point.
Logging	the automatic recording of data with regard to the access of the data, the updates to the data, etc.
Logical Representation	a data view or description that does not depend on a physical storage device or a computer program.

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DataWare Housing Glossary of Terms - 'I' & 'J'

Indexing	fastest searching records
Information	Data that has been processed in such a way that it can increase the knowledge of the person who receives it.
Information Systems Architecture	The authoritative definition of the business rules, systems structure, technical framework, and product backbone for business information systems.
Instance	a set of values representing a specific entity belonging to a particular entity type.
Integrity	a set of values representing a specific property of a data base that ensures that the data contained in the data base in accurate and consistent as possible.
Intelligent Data Base	a data base that contains shared logic as well as shared data and automatically invokes that logic when the data base is accessed. Logic, constraints, and controls relating to the use of data are represented in an intelligent data model.
Interleaved Data	data from different tables mixed into a simple table space where is commonality of physical colocation based on a common key value.
Iterative Analysis	the mode of processing in which the next step of processing depends on the results obtained by the existing step in execution.

Join	an operation that takes two relations as operands and produces a new relation by concatenating the tuples and matching the corresponding columns when a stated condition holds between the two.

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DataWare Housing Glossary of Terms - 'G' & 'H'

Global Business Models	Provides access to information scattered throughout an enterprise under the control of different divisions or departments with different databases and data models. This type of data warehouse is difficult to build because it requires users from different divisions to come together to define a common data model for the warehouse.
Granularity	The level of detail of the data stored in a data warehouse.

Hetergeneous Environment	Within an enterprise, a network of different types of servers and databases.
Heuristic	the mode of analysis in which the next step is determined by the results of the current step of analysis.
Hierarchy	The organization of data into a logical tree structure.
Homogeneous Environment	Within an enterprise, a network consisting of the same type of servers and databases.
Horizontal Distribution	the splitting of a table across different sites by rows. With horizontal distribution rows of a single table residing at different sites in a distributed data base network.
Hub and Spoke Configuration	A configuration of interconnected systems where a single system (the hub) acts as the central point for exchanging data with and between the other systems (spokes).
Huffman Code	a code for data compaction in which frequently used characters are encoded with fewer bits than infrequently used characters.
HyperCube	See CUBE.

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DataWare Housing Glossary of Terms - 'F'

Fact Table	The tables which are extracted from heterogeneous sources and used in the Data Wareahouse
Factless Fact	A fact table without any metrics in it
Flat File	a collection of records containing no data aggregates, nested repeated data items, or groups of data items.
Functional Decomposition	the division of operations into hierarchical functions that form the basis for procedures.

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DataWare Housing Glossary of Terms - 'E'

EDI (Electronic Data Interchange)	is a standard format for exchanging business data.
Encryption	the transformation of data from a recognizable format to a form unrecognizable without the algorithm used for the transformation.
ETL (Extract, Transform and Load)	ETL refers to the process of getting data out of one data store (extract), modifying it (transfer), and inserting it into a different data store (load).
ETT	ETL is sometimes referred as ETT- Extraction, Transformation and Transportation. It is a series of batch interface between the systems.
Executive/Enterprise Information Systems (EIS)	Tools programmed to provide canned reports or briefing books to top-level executives. They offer strong reporting and drill-down capabilities. Today these tools allow ad-hoc querying against a multi-dimensional database, and most offer analytical applications along functional lines such as sales or financial analysis. (Also known as Decision Support System.)
Extendibility	The ability to easily add new functionality to existing services without major software rewrites or without redefining the basic architecture.
External Schema	a logical description of a user's method of organizing and structuring data.

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DataWare Housing Glossary of Terms - 'D'

Data	Facts, concepts, or instructions that a computer records, stores and processes. Used in conjunction with INFORMATION SYSTEMS, “raw data” is organized in such a way that people can understand the results.
Data Cleansing	Removing errors and inconsistencies from data being inported to a data warehouse.
Data Dictionary	a software tool for recording the definition of data, the relationship of one category of data to another, the attributes and keys of groups of data, and so forth.
Data Driven Development	the approach to development that centers around identifying the commonality of data through a data model and building programs that have a broader scope thn the immediate application.
Data Driven Process	a process whose resource consumption depends on the data on which it operates.
Data Mart	A department-specific data warehouse. A) Independent – fed from legacy systems within the department B) Dependent – fed from the enterprise data warehouse (preferred)
Data Mining	The process of finding hidden patterns and relationships in data. For instance, a consumer goods company may track 200 variables about each consumer. There are scores of possible relationships among the 200 variables. Data mining tools will identify the significant relationships.
Data Scrubbing	Removing errors and inconsistencies from data being imported into a data warehouse.
Data Transformation	The modification or alteration of data as it is being moved into the data warehouse.
Data Type	A data type defines the type of data stored in a specific database column, such as date, numeric or character data. Significant differences in data types exist between different platforms’ databases.
Data Warehouse	A data warehouse is a subject oriented, integrated, non volatile, time variant collection of data. The data warehouse contains atomic level data and summarized data specifically structured for querying and reporting.
Data Warehousing	An enterprise-wide implementation that replicates data from the same publication table on different servers/platforms to a single subscription table. This implementation effectively consolidates data from multiple sources.
Database Schema	The logical and physical definition of a database structure.
Date/Time Stamp	A stamp added by an application that identifies a task or activity by the date and time it was initiated and/or completed. This can appear as part of a transaction log, message queue content in job logs.
Decentralized Database	A centralized database that has been partitioned according to a business or end-user defined subject area. Typically ownership is also moved to the owners of the subject area.
Decentralized Warehouse	A remote data source what users can query/ access via a central gateway that provides a logical view of corporate data in terms that users can understand. The gateway parses and distributes queries in real time to remote data sources and returns result sets back to users.
Decision Support Systems (DSS)	Software that supports exception reporting, stop light reporting, standard repository, data analysis and rule-based analysis. A database created for end-user ad-hoc query processing.
Denormalization	the technique of placing normalized data in a physical location that optimizes the performance of the system.
Derived Data	Data whose values are determined by equations or algorithms.
Dimension	A Dimension is typically a qualifiable and text value, such as a region, product line, and includes date values. It defines the secondary headings or labels that make up the body of the report. Each of the dimensions is repeated within each group. Usually, you use items containing text values (for example, Year or item type) for table dimensions. For example, if you select Item Type to be your table dimension, Item Type is a dimension within each group header. Under the dimension "Item Type," appears the name of each kind of item (for example, CD ROM, or HARD Drive). and corresponds to the . A fact is an quantifiable value, such amount of sales, budget or revenue.
Drill Down/Up	The ability to move between levels of the hierarchy when viewing data with multiple levels. A) Drill down – changing a view to a greateer level of detail B) Drill up – changing a view to a greater level of aggregation.

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DataWare Housing Glossary of Terms - 'C'

Canonical model	A data model that represents the inherent structure of data without regard to either individual use or hardware or software implementation.
Cardinality	no of unique rows divided by total no of columns
Cell	A single point in a CUBE.
Conceptual Schema	A consistent collection of data structures expressing the data needs of the organization. This schema is a comprehensive, base level, and logical description of the environment in which an organization exists, free of physical structure and application system considerations.
Condensation	The process of reducing the volume of data managed without reducing the logical consistency of the data.
Connector	A symbol used to indicate that one occurrence of data has a relationship with another occurrence of data. Connectors are used in conceptual data base design and can be implemented hierarchically, relationally, in an inverted fashion, or by a network.
Contention	Tthe condition that occurs when two or more programs try to access the same data at the same time.
Cooperative Processing	Tthe ability to distribute resources (programs, files and data bases) across the network.
Corporate Data	All the databases of the company.This includes legacy systems,old and new transaction systems,general business systems,client/server databases,data warehouses and data marts.
Corporate Information Warehouse (CIF)	The architectural framework that houses the ODS, data warehouse, data marts, i/t interface, and the operational environment. The cif is held together logically by metadata and physically by a network such as the Internet.
Cube – (also Hypercube, Multi-dimensional Cube)	The fundamental structure for information in an OLAP system. A structure that stores multi-dimensional information, having one CELL for each possible combination of dimensions.

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DataWare Housing Glossary of Terms - 'B'

Binary Search	A dichotomizing search with steps in which the sets of remaining items are partioned into two equal parts.
Bit Map	A specialized form of an index indicating the existence or non-existence of a condition for a group of blocks or records.
Bus	The hardware connection that allows data to flow from one component to another.
Business Intelligence Tools	Software that allows business users to see and use large amounts of complex data.

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DataWare Housing Glossary of Terms - 'A'

Agent	An application that searches data and sends an alert when a certain situation occurs. (See ALERT)
Aggregate data	Individual data items, data groups, arrays, tables etc. that can be assembled to form a whole.
Alerts and Alarms	Messages sent automatically by a computer system when an AGENT identifies a certain situation. For example, if stock of an item in a warehouse drops to a certain level, key personnel can be immediately informed.
Algorithm	A set of statements organized to solve a problem in a finite number of steps
Analytical Processing	The usage of the computer to produce an analysis for management decision, usually involving trend analysis, drill down analysis, demographic analysis, profiling, etc.
Architecture Phase	The establishment of the framework, scope and standards and procedures for a data warehouse at the enterprise level.
Atomic level data	Data with the lowest level of granularity. Atomic level data sits in a data warehouse and is time variant (i.e., accurate as of some moment in time now passed).
Attribute	A property or characteristic of an application entity. For example, the attributes of an EMPLOYEE entity in a business application may be: IDFirstname Lastname Job_Title Email_ID An attribute usually represents a column in a table in a relational database, or a field in a file.
Audit Trail	Recording of any changes made to specific data. Details can include date and time of change, how the change was detected, reason for the change and before-and-after data values.

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Data Warehousing Interview Questions - III

38) What is a universe?
39) Analysis in business objects?
40) Who launches the supervisor product in BO for first time?
41) How can you check the universe?
42) What are universe parameters?
43) Types of universes in business objects?
44) What is security domain in BO?
45) Where will you find the address of repository in BO?
46) What is broad cast agent?
47) In BO 4.1 version what is the alternative name for broadcast agent?
48) What services the broadcast agent offers on the server side?
49) How can you access your repository with different user profiles?
50) How many built-in objects are created in BO repository?
51) What are alertors in BO?
52) What are different types of saving options in web intelligence?
53) What is batch processing in BO?
54) How can you first report in BO by using broadcast agent?
55) Can we take report on Excel in BO?

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Data Warehousing Interview Questions - II

21) What is Cognos script editor?
22) What is difference macros and prompts?
23) What is power play plug in?
24) Which kind of index is preferred in DWH?
25) What is hash partition?
26) What is DTM session?
27) How can you define a transformation? What are different types of transformations in Informatica?
28) What is mapplet?
29) What is query panel?
30) What is a look up function? What is default transformation for the look up function?
31) What is difference between a connected look up and unconnected look up?
32) What is staging area?
33) What is data merging, data cleansing and sampling?
34) What is up date strategy and what are th options for update strategy?
35) OLAP architecture?
36) What is subject area?
37) Why do we use DSS database for OLAP tools?

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Data Warehousing Interview Questions - I

1) What is source qualifier?
2) Difference between DSS & OLTP?
3) Explain grouped cross tab?
4) Hierarchy of DWH?
5) How many repositories can we create in Informatica?
6) What is surrogate key?
7) What is difference between Mapplet and reusable transformation?
8) What is aggregate awareness?
9) Explain reference cursor?
10) What are parallel querys and query hints?
11) DWH architecture?
12) What are cursors?
13) Advantages of de normalized data?
14) What is operational data source (ODS)?
15) What is meta data and system catalog?
16) What is factless fact schema?
17) What is confirmed dimension?
18) What is the capacity of power cube?
19) Difference between PowerPlay transformer and power play reports?
20) What is IQD file?

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