Foreign keys of dimension tables are primary keys of entity tables. Foreign keys of facts tables are primary keys of Dimension tables.
Fact tables
A fact table is a table in a star or snowflake schema that stores facts that measure the business, such as sales, cost of goods, or profit. Fact tables also contain foreign keys to the dimension tables. These foreign keys relate each row of data in the fact table to its corresponding dimensions and levels.
Dimension Tables
A dimension table is a table in a star or snowflake schema that stores attributes that describe aspects of a dimension. For example, a time table stores the various aspects of time such as year, quarter, month, and day. A foreign key of a fact table references the primary key in a dimension table in a many-to-one relationship.

Data Mining is the process of analyzing data from different perspectives and summarizing it into useful information.
Data Mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.

A view takes the output of a query and makes it appear like a virtual table and it can be used in place of tables. A materialized view provides indirect access to table data by storing the results of a query in a separate schema object.

Entity Relationship Diagrams are a major data modelling tool and will help organize the data in your project into entities and define the relationships between the entities. This process has proved to enable the analyst to produce a good database structure so that the data can be stored and retrieved in a most efficient manner. An entity-relationship (ER) diagram is a specialized graphic that illustrates the interrelationships between entities in a database. A type of diagram used in data modeling for relational data bases. These diagrams show the structure of each table and the links between tables.

ODS is abbreviation of Operational Data Store. A database structure that is a repository for near real-time operational data rather than long term trend data. The ODS may further become the enterprise shared operational database, allowing operational systems that are being reengineered to use the ODS as there operation databases.

ETL is abbreviation of extract, transform, and load. ETL is software that enables businesses to consolidate their disparate data while moving it from place to place, and it doesn't really matter that that data is in different forms or formats. The data can come from any source.ETL is powerful enough to handle such data disparities. First, the extract function reads data from a specified source database and extracts a desired subset of data. Next, the transform function works with the acquired data - using rules orlookup tables, or creating combinations with other data - to convert it to the desired state. Finally, the load function is used to write the resulting data to a target database.

VLDB is abbreviation of Very Large DataBase. A one terabyte database would normally be considered to be a VLDB. Typically, these are decision support systems or transaction processing applications serving large numbers of users.

No. OLTP database tables are normalized and it will add additional time to queries to return results. Additionally OLTP database is smaller and it does not contain longer period (many years) data, which needs to be analyzed. A OLTP system is basically ER model and not Dimensional Model. If a complex query is executed on a OLTP system, it may cause a heavy overhead on the OLTP server that will affect the normal business processes.

Foreign keys of facts tables are primary keys of Dimension tables. It is clear that fact table contains columns which are primary key to other table that itself make normal form table.

A lookup table is the table placed on the target table based upon the primary key of the target, it just updates the table by allowing only modified (new or updated) records based on thelookup condition.

Aggregate table contains the summary of existing warehouse data which is grouped to certain levels of dimensions. It is always easy to retrieve data from aggregated tables than visiting original table which has million records. Aggregate tables reduces the load in the database server and increases the performance of the query and can retrieve the result quickly

Data warehousing captures business activity data. Real-time data warehousing captures business activity data as it occurs. As soon as the business activity is complete and there is data about it, the completed activity data flows into the data warehouse and becomes available instantly.

Conformed dimensions mean the exact same thing with every possible fact table to which they are joined. They are common to the cubes.

Conformed dimensions are the dimensions which can be used across multiple Data Marts in combination with multiple facts tables accordingly.

Time dimensions are usually loaded by a program that loops through all possible dates that may appear in the data. 100 years may be represented in a time dimension, with one row per day.

Level of granularity means level of detail that you put into the fact table in a data warehouse. Level of granularity would mean what detail are you willing to put for each transactional fact.

Non-additive facts are facts that cannot be summed up for any of the dimensions present in the fact table. However they are not considered as useless. If there is changes in dimensions the same facts can be useful.