Business Objects - 3

Tuesday, July 22, 2008

21. what is the source for metrics?
Measure objects.

22. Why do we need metrics and sets?
Metrics are used for analysis and Sets are used for grouping.

23. Is there any bug in 6.x?
In earlier version of 6.0 they had, but 6.5 is the best version with out any bugs.

24. What are the general issues in migration process?
Alignment, performance.

25. What is the use of BO SDK?
Bo SDK's main use is to suppress “no data to fetch” using Macros.

26. How can we improve performance?
By making use of Aggregate tables.

27. Analysis in BO?
Slice-Dice and Drill analysis.

28. How can you check the integrity?
By making use of Check integrity button.

29. What are Universe parameters?
Name of the universe, description and RDBMS connection, size and rights.

30. Types of Universes?
Simple and Complex.

31. What is the use of BCA?
BCA is used to refresh and schedule and export and save as .html, .rtf, .xls , .pdf.

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Business Objects - 2

11. What do you mean by Object qualification?
Object qualification represents what kind of object is that, usually we have three types of object qualifiers they are measure, dimension, detailed.

12. What is the size of data base?
In general it will be anything between 4-8 Terabytes.

13. What is a loop? How can we overcome?
Loop is nothing but a closed circular flow; it can be overcome by making use of Alias and Context.

14. What is a join? Explain different types of joins?
Join is used to link to tables depending upon the data requested by the user, Usually we have Inner Join, Outer Join, Left Join, Right Join, Full Outer join.

15. What are Linked Universes?
If the data provided is from two different data providers then we can link those two universes, such type of universe is called Linked Universe.

16. What are Alerter, Filters, Breaks and Conditions?
Alters are nothing but they are used to draw attention to a block of data by highlighting.
Breaks are nothing but grouping the data without any change in the format.
Condition is used to retrieve data which meets certain criteria.
Filters are used to get necessary data.

17. What is the difference between master-detail and Breaks?
In break common fields are deleted (here in this case the table format is not changed) whereas in master-detail , we declare certain entity as a master to get the detailed information or report in this case the table format is changed.

18. What is metrics?
Metrics are a system of parameters or ways of quantitative and periodic assessment of a process that is to be measured; these are used to track trends, productivity.

19. What is a Set?
Its nothing but grouping of users.

20. What is the use of AFD? Where it can be stored?
AFD is used to create dashboards. It can be stored in repository, corporate or personal.

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Business Objects - 1

1. Explain detail objects?
Detail objects are attached to dimensions, one cannot drill on details nor link on details when linking multiple data providers. While Customer ID would be a dimension, customer name, address, phone and so on should be details.

2. What is BOMain.Key?
BoMain.Key file contains the information about the repository site i.e it contains the address of the repository security domain.

3. What is Business objects Repository?
It is nothing but metadata.

4. What is domain? How many are there in a basic setup? What are they?
Domain is nothing but logical grouping of system tables. There are three domains usually in a basic setup. They are Secure, Universe, Document. Business objects are sometimes called domain objects (where the word domain means the business), and a domain model represents the set of domain objects and the relationships between them.

5. When is the Repository created?
In 5i/6i versions after installing the software, whereas in Xi version a repository is created at the time of installation.

6. Can we have multiple domains?
Yes. (Security domain can not be multiple).

7. How do you restrict access to rows of a database?
In XI version it can be done by using row-level security in designer module whereas in 5i/6i it is done by supervisor.

8. What is a category?
It is nothing but grouping of certain entities.

9. What is a Universe?
It is a semantic layer between Database and the designer used to create objects and classes. (It maps to data in Database).

10. What is an Object?
It is an instance of class, its nothing but an entity.

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DataWare Housing Glossary of Terms - 'T'

Sunday, July 20, 2008

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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Chitika

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