Setup SQL Server

2024-07-16

In this section we will guide you through the setup and configuration of the SQL Server objects required for the i-refactory metadata repository. You will also find the prerequisites for the other logical data domains as well. The Solution Overview briefly introduces the role of SQL Server and the logical data domains.

Before you begin

Before you continue installing the SQL Server objects required for the i-refactory, please make sure:

  1. You have a SQL Server instance up and running.
  2. You have SQL Server Management Studio installed.
  3. You have access to the SQL Server instance with a DBA account.

Supported SQL Server Versions

The i-refactory server runs on SQL Server 2016, 2017, 2019 and 2022.

What is the i-refactory metadata repository?

In the i-refactory metadata repository we store the following information:

  1. Data Definition Metadata: Facts regarding data models such as entities, attributes, relationships, constraints, ...
  2. Data Delivery Metadata: Facts regarding the creation of deliveries, the state of a delivery, the detailed specifications of a delivery, occurred constraint violations, ...
  3. Data Logistics Metadata: Facts regarding the execution of tasks to process a delivery.

On top of the fact store we've created access views with which you can easily retrieve the metadata information without having to know how the physical data is stored.

The i-refactory metadata repository is implemented as an immutable fact store which means we never update or remove metadata. The metadata is completely versioned. This allows for time travelling and auditability regarding the creation and changes of metadata data.

Storage requirements

The size of the i-refactory metadata repository in terms of disk storage depends on the number of daily executed deliveries and the number of data models created. Due to the nature of the immutability of the fact store the total disk size in time will grow.

Typically, the total storage in time requires several Gibabytes. As a rule of thumb, executing 1.000 tasks requires approximately 1 Megabyte of storage.

Step 1 - Unpack SQL Server folder

From the provided installation zip file unpack the folder i-refactory-sqlsever to a location where you are able to access the contents of this folder. We will refer to this install folder in the next sections as I-REFACTORY-SQLSERVER-PATH.

Step 2 - Connect to your SQL Server instance

We recommend connecting to your SQL Server Instance with SQL Server Management Studio. Connect to your SQL Server instance with a DBA account. If you don't have SQL Server Management Studio you at least should have a tool with which you can connect to your SQL Server instance and are allowed to execute SQLCMD script.

Step 3 - Create a database

Create a database in your SQL Server instance for the i-refactory metadata repository. We recommend naming the database IREFACTORY.

{info} Use your company standard settings for creating a SQL Server database. Make sure your SQL Server collation is set to Latin1_General_CS_AS. If not, specify this collation when creating the database.

CREATE DATABASE [<Your Database Name>]
<Your Default Settings>

Change the following settings:

ALTER DATABASE [<Your Database Name>] SET TRUSTWORTHY ON
GO

ALTER DATABASE [<Your Database Name>] SET ALLOW_SNAPSHOT_ISOLATION ON
GO

ALTER DATABASE [<Your Database Name>] SET READ_COMMITTED_SNAPSHOT ON
GO

ALTER DATABASE [<Your Database Name>] SET QUOTED_IDENTIFIER ON
GO

{warning} The i-refactory metadata repository database should be configured for READ_COMMITTED_SNAPSHOT. Not doing so will block both readers and writers and most likely will result in deadlock errors more often. To learn more check the Microsoft docs regarding Transaction Locking and Row Versioning Guide.

It is highly recommended to enable automatic statistics gathering.

ALTER DATABASE [<Your Database Name>] SET AUTO_UPDATE_STATISTICS ON

Step 4 - Execute the install script

The i-refactory metadata repository SQLServer objects will be created with an install script which can be found in I-REFACTORY-SQLSERVER-PATH.

The script doesn't drop or alter anything. It will create new objects. It is assumed that you are installing in a clean and empty database.

The script runs within a transaction. If a failure occurs during the install, the complete install is reversed with a rollback. Your session will be disconnected upon failure. You need to close the session and create a new one.

To run the installation execute the following steps.

  1. Open install script:

    In SQL Server Management Studio open the file Install.sql from I-REFACTORY-SQLSERVER-PATH.

  2. Change query parameters:

    Menu > Query > Specify Values for Query Parameters

    Set the value of the following parameters:

    1. Install directory: set the value to I-REFACTORY-SQLSERVER-PATH.
    2. i-refactory database name: set the value to the name of the database you created or accept the default value.
    3. Value for high end dt: keep the default value.
  3. Change query to SQLCMD modus:

    Menu > Query > SQLCMD mode

  4. Execute the script:

    Execute

The install script typically will finish within 60 seconds.

The messages tabpage logs the result of the installation:

Messages
Messages

Step 5 - Create additional databases

Besides the storage of metadata we need to have storage locations for the data from external and internal data

We recommend to create at least 4 additional databases.

  1. A technical staging database

    In this database the tables are created for storing the raw data provided by the external data suppliers. The tables typically do not implement any constraints although optionally you can create indexes. The tables only contain data for a single data delivery. For each new delivery for a given data supplier the relevant tables should be truncated.

    Instead of a single technical staging database you could create a technical staging database for each raw data supplier.

    If you opt for a single technical staging database you should avoid naming conflicts between tables of different data suppliers by applying a unique schema (we call it a namespace) convention for each data supplier.

  2. A logical validation database

    In the logical validation database the raw data is transformed and stored in a logical format. In this database we also store intermediate results regarding the execution and validation of constraints. The tables stored in the logical validation database are buffered, a snapshot time is added to the primary key. Buffering allows for parallel execution of deliveries.

    The same approach as for a technical database can be chosen for a logical validation database. You can opt to create only one database or a database for each external data supplier.

  3. A facts database

    As a rule of thumb, you only create a single fact database. In this database typically the facts are stored for each and every delivery and for each and every data supplier. The fact database is integrated over data sources.

    {editorial} [EJ] Create reference to explanation of the fact store.

    However, if data from external sources doesn't need to be integrated you could opt here as well to create a seperate database for each specific data source.

  4. A data access database

    In the data access database no physical data is stored, nor are any physical tables created. The database simply creates interfaces on the facts stored in the fact database. These interfaces are implemented as views, stored procedures and table valued functions.

    The same approach as for a technical and logical validation can be chosen. You could create only a single data access database or several ones. Again care should be taken regarding possible naming conflicts on object types.

{info} Depending on the data volumes, number of concurrent users, ... the required SQL Server resources should be carefully sized regarding CPU, memory, data storage, temp storage. It is assumed that sufficient DBA experience is available to manage and configure a SQL Server instance and databases.

  1. Step 1 - For each database you want to create.

    CREATE DATABASE [<Your Database Name>]
    <Your Default Settings>
  2. Step 2 - Change the following settings:

    ALTER DATABASE [<Your Database Name>] SET TRUSTWORTHY ON
    GO
    
    ALTER DATABASE [<Your Database Name>] SET ALLOW_SNAPSHOT_ISOLATION ON
    GO
    
    ALTER DATABASE [<Your Database Name>] SET READ_COMMITTED_SNAPSHOT ON
    GO
    
    ALTER DATABASE [<Your Database Name>] SET QUOTED_IDENTIFIER ON
    GO

{warning} The databases should be configured for READ_COMMITTED_SNAPSHOT. Not doing so will block both readers and writers accessing the same data and will most likely result in deadlock errors more often. To learn more check the Microsoft docs regarding Transaction Locking and Row Versioning Guide.

Step 6 - Grant access to the metadata database

The i-refactory server needs to be able to connect to the SQL Server instance with a SQL Server login. To access to the i-refactory metadata repository, a user should be created for this login. This user should be granted specific access rights.

To create the login and a user with proper access rights on the i-refactory metadata repository, execute the following steps:

  1. Connect to SQL Server Management studio.

  2. Copy / paste the script in a new query window.

    :setvar APPLICATION_USER "<Application user name, string, i-refactory>"
    :setvar APPLICATION_USER_PASSWORD "<Application user password, string,>"
    
    :setvar IREFACTORY_DB "<i-refactory repository database name, string, IREFACTORY>"
    
    USE [master]
    IF NOT EXISTS(SELECT * FROM sys.server_principals WHERE name = '$(APPLICATION_USER)')
    BEGIN
        CREATE LOGIN [$(APPLICATION_USER)] WITH PASSWORD=N'$(APPLICATION_USER_PASSWORD)', DEFAULT_DATABASE=[$(IREFACTORY_DB)], CHECK_EXPIRATION=OFF, CHECK_POLICY=OFF
        GRANT VIEW SERVER STATE TO [$(APPLICATION_USER)];
    END
    
    IF CAST(SERVERPROPERTY('productmajorversion') AS INTEGER) > 14 
    BEGIN
    -- SQLServer 2019 and higher support for loading CSV files with BULK INSERT requires additional GRANT. 
    -- Note: this is not supported on SQLServer on Linux.
        GRANT ADMINISTER BULK OPERATIONS TO [$(APPLICATION_USER)];
    END
    IF CAST(SERVERPROPERTY('productmajorversion') AS INTEGER) > 15 
    -- SQLServer 2022 and higher include additional security controls and therefore require additional GRANT.
        GRANT VIEW DATABASE PERFORMANCE STATE TO [$(APPLICATION_USER)];
    END
    
    USE [$(IREFACTORY_DB)]
    IF NOT EXISTS(SELECT * FROM sys.database_principals WHERE name = '$(APPLICATION_USER)')
    BEGIN
        CREATE USER [$(APPLICATION_USER)] FOR LOGIN [$(APPLICATION_USER)]
        ALTER ROLE [db_datareader] ADD MEMBER [$(APPLICATION_USER)]
        ALTER ROLE [db_datawriter] ADD MEMBER [$(APPLICATION_USER)]
        ALTER ROLE [db_ddladmin] ADD MEMBER [$(APPLICATION_USER)]
        GRANT EXECUTE TO [$(APPLICATION_USER)];
    END
  3. Change query parameters.

    Menu > Query > Specify Values for Query Parameters

    Set the value of the following parameters:

    1. Application username: change the value or accept the default.
    2. Application user password: enter a password.
    3. i-refactory repository database name: change the value or accept the default.
  4. Change query to SQLCMD modus.

    Menu > Query > SQLCMD mode

  5. Execute the script.

    Execute

Step 7 - Grant access to the other databases

For each database you've created in Step 5: Create additonal databases, the i-refactory server needs to have proper access. We need to create a SQL Server user for each of these database with the proper access rights. We will use the login account created in Step 6 to create a user in each of the databases.

  1. Connect to SQL Server Management studio.

  2. Copy / paste the script in a new query window.

    :setvar APPLICATION_USER "<Application user name, string, i-refactory>"
    :setvar DB "<Database name, string,>"
    
    USE [$(DB)]
    IF NOT EXISTS(SELECT * FROM sys.database_principals WHERE name = '$(APPLICATION_USER)')
    BEGIN
        CREATE USER [$(APPLICATION_USER)] FOR LOGIN [$(APPLICATION_USER)]
        ALTER ROLE [db_datareader] ADD MEMBER [$(APPLICATION_USER)]
        ALTER ROLE [db_datawriter] ADD MEMBER [$(APPLICATION_USER)]
        ALTER ROLE [db_ddladmin] ADD MEMBER [$(APPLICATION_USER)]
    END
  3. Change query parameters.

    Menu > Query > Specify Values for Query Parameters

    Set the value of the following parameters:

    1. Application username: change the value or accept the default.
    2. Database name: set the name of the database.
  4. Change query to SQLCMD modus.

    Menu > Query > SQLCMD mode

  5. Execute the script.

    Execute

Step 8 - Allow connecting to the SQL Server instance

  1. The SQL Server Instance should be configured to allow access with SQL Server and Windows Authentication model.
  2. Connecting to the SQL Server Instance over TCP/IP should be enabled. Check with your company regarding firewall settings or other blocking settings preventing you from connecting over TCP/IP.

{info} The i-refactory server should be able to connect to the SQL Server instance with a low latency network connection.

What's next

Start the installation of i-refactory server.

{info} If you are not directly involved in the installation of the other server components you should inform your peers regarding the SQL Server setup.


At least provide the following information:

  • Host and port of the SQL Server instance.
  • The login and password of the application user created in Step 6
  • The name of the database — created in Step 3 — in which you have installed the i-refactory metadata repository.

Constraint violation actions are applicable to certain constraint categories. Not all combinations of constraint categories and violation actions are allowed.

An attribute must have a value, whatever that value may be. It must not be NULL.

A data type of an attribute defines what value an attribute can hold. The data type specifies what type of mathematical, relational, or logical operations can be applied to it without causing an error.

An attribute datatype constraint is the most basic constraint type. It checks for the datatypes we support and have implemented.

For example, we check for string, length of string, integer, date, etc. In the following figure you can see the supported data types by PowerDesigner.

Image is omitted: Supported data types

Constraints can be violated and there are some actions that can be performed when a violation occurs. The possible actions are: EMPTY COLUMN, NO ACTION and SKIP ROW.

An attribute value constraint is an expression that is evaluated. The person who writes the expression is responsible for the correctness of it. The expression should be formulated in a positive way and lead to a Boolean answer. If the expression validates to True, than the value is correct.

Examples

  • The values in attribute X has to be bigger than 10: X > 10
  • The email address has to be in a certain pattern: email address LIKE '%_@_%.__%'

A Concept Integration Model is also a central facts model on which you place integration patterns. It is not required to create a concept integration model, but it can be very useful.

Every constraint is assigned to a constraint classification.

The main purposes of the Generic Data Access Layer (GDAL) are to provide logical perspectives for data consumption and to manage CRUD actions.

A generic data access model is a virtual data model that acts as an interface bridge between consumer applications and the central fact storage.

Every attribute is assigned to an attribute classification.

An entity record constraint checks whether an attribute meets the requirements set by another attribute belonging to the same entity.

The main purpose of the Logical Validation Layer (LVL) is to transform the data received from external data sources to fit into the logical data model structure. It is also responsible for validating deliveries. The Logical Validation Layer is also known as the Historical Staging In (HSTGIN) Layer.

The logical validation model is the representation of a single external data source in a logical format. It represent how data delivered by a specific tenant should be transformed, temporalized and validated in the {popup}logical validation layer. The logical validation model is also known as Historical Staging model (HSTGIN).

Multi-active attributes are attributes that contain a business key to provide multiple context records at the same time. For example: a customer has multiple types of phone numbers. “Home”, “Work” and “Mobile”. In that case we add a dependent entity on customer with key “Phone Nbr Type”. This is to prepare for the CFPL multi-active key on customer.

The main purpose of the Technical Staging Layer (TSL) is to create a common starting point for further data processing. It receives data delivered from external data sources and temporally stores them in a database. The input data should be in a tabular format (rows and columns).

Bi-temporal attribute is an attribute that changes over time: they follow a valid timeline. For example, a Part may have a price valid for December and a price valid for January.

Every entity is assigned to an entity classification and to a parent entity classification. The possible values for entity classification are: ALTERNATE KEY CONTEXT, ATTRIBUTE CONTEXT, GENERALIZATION,HELPER, REFERENCE CONTEXT, STABLE, STABLE DEPENDENT and STABLE INDEPENDENT

Entity Set Constraint An entity set constraint can be used to perform a check concerning values of two or more attributes that belong to different entities or to perform a check concerning the value of an attribute with respect to a set of values.

A Set Constraint Helper is a helper in the logical validation model. It is the implementation of a set constraint. The helper returns the records of an entity for a given set constraint, where the instances of this entity do not meet the definition of this set constraint.

The business requirements describe how data should be delivered for the data consumers (end users or applications) in terms of concepts, relationships between concepts and constraints to validate the data. These requirements can be described in a logical data model, for example.

A Business Rule Helper is a helper in the central facts model. It is a set-based calculation of derived facts. You need to use a Business Rule Helper if you want to make a calculation and want to keep a transaction history of the results of this calculation. You use the existing entities from the central facts model as input. The results of the helper must be materialized in 'regular' fact entities, such as Anchors and Contexts, to make them accessible in the Generic Data Access Layer.

Closed Open means that the timeline is valid from (vanaf in Dutch) the supplied valid start date until - but not including - (tot in Dutch) the supplied valid end date. In practice, this means that the start date of a valid time record is equal to the end date of the previous valid time record.

You need to create context-based entities when a set of data may be delivered within the boundaries of a parent context. A context-based entity applies when:

  • At least 2 entities are delivered.
  • A context relationship exists between these 2 entities. One entity is the parent context of the other entity.
  • The parent context entity is delivered as a delta and the child entity is delivered as a full set.

You need to create context-based entities when a set of data may be delivered within the boundaries of a parent context. A context-based entity applies when:

  • At least 2 entities are delivered.
  • A context relationship exists between these 2 entities. One entity is the parent context of the other entity.
  • The parent context entity is delivered as a delta and the child entity is delivered as a full set.

The Management Model contains the PowerDesigner objects for the Unified Anchor Modelling (UAM). When a UAM object is created, a so-called PowerDesigner replica of the corresponding Management Model object is created. This means that certain properties such as metadata columns and column stereotypes are configured in the Management Model and cannot be changed. The replication settings specify which elements of an object can be changed after creating a replica from the template object. It is possible to override the replication settings of an UAM object and change a specific property.

The temporal atomic type describes the datatype of the temporal attributes|

The main purposes of the Central Facts Layer (CFL) is to store data historically. It can also integrate data from different sources. The Central Facts Layer is also known as Central Facts Persistency Layer (CFPL)

The central facts persistence implementation model is the representation of facts in an anchorized data model with the ability to integrate multiple logical models.

In the context of i-refactory, data transformation refers to operations involved in turning raw data readily useful and closer to the business requirements.

Integration patterns are used to integrate entities from different data models. If two or more entities from different data models share the same business key, you can use the Integration Pattern named Key Root. It is a good practice to capture integration patterns in a separate model, named Concept Integration Model.

An attribute is mandatory when its value can not be empty (NULL).

A Physical Data Model (PDM) represents how data will be implemented in a specific database.

{note} The i-refactory uses four PDMs: technical staging model, logical validation model, central facts model and generic access model. Each one of these models is implemented as an additional database, which is used to store data from external and internal data sources.

Reverse engineering is the process of reconstructing a physical and/or Entity Relationship (ER) model from an existing data source. The purpose of reverse engineering is to avoid manual work as much as possible.

Architecture layer

The core of the i-refactory architecture has four layers: TSTGIN, LVL, CFL and GDAL. There are also two auxiliary layers: UCLVL and EXT.

If an entity has one or more attributes that changes over time and you want to keep track of when a attribute is valid at a certain transaction time, then you have a special case of a regular dependent entity, called bi-temporal entity. The bi-temporal entity stores historical data with two timelines. The primary key of the bi-temporal entity is composed by the primary key of the parent entity and the valid start date attribute. The attribute that changes over the valid time is called a bi-temporal attribute.

If an entity has one or more attributes that changes over time and you want to keep track of when a attribute is valid at a certain transaction time, then you have a special case of a regular dependent entity, called bi-temporal entity. The bi-temporal entity stores historical data with two timelines. The primary key of the bi-temporal entity is composed by the primary key of the parent entity and the valid start date attribute. The attribute that changes over the valid time is called a bi-temporal attribute.

A delivery agreement is a contract between a Tenant and a Logical Implementation Model or Generic Data Access model. An agreement has a duration. The delivery agreement set the architecture layer (interface) where the data should be ingested as well as the default settings to be applied to the deliveries.

A dependency mapping is a mapping between a helper (or BR helper) and a source entity used in the query of the helper. The helper and the source entity must belong to the same model.

  • Default dependency is set on entity level (source entity to helper entity)
  • To allow lineage on attribute level, via the Mapping editor, you could manually add the dependency on attribute level.

An Independent Entity is an entity that implements an Anchor for a Business Key that ‘stands alone’ e.g. that does not contain a reference to another Entity.

An Independent Entity is an entity that implements an Anchor for a Business Key that ‘stands alone’ e.g. that does not contain a reference to another Entity.

A Logical Data Model (LDM) matches the language, structure and quality of the business, regardless of the physical data implementation. The Logical Data Model reflects the business requirements.

A delivery may be considered as "untrusted" if deletes of data in the Logical Validation Layer have taken place and the processing of new deliveries cannot 100% rely (trust) on having enough statistics and data available to detect logical deletes, to determine the exact delta and to execute set based validations.

A delivery may be considered as "untrusted" if deletes of data in the Logical Validation Layer have taken place and the processing of new deliveries cannot 100% rely (trust) on having enough statistics and data available to detect logical deletes, to determine the exact delta and to execute set based validations.

A Dependent Entity is an entity that implements an Anchor for a Business Key that ‘depends’ in its existence on another Entity. A Dependent Entity contains Business Key fields of which at least one is a foreign key (FK).

A Dependent Entity is an entity that implements an Anchor for a Business Key that ‘depends’ in its existence on another Entity. A Dependent Entity contains Business Key fields of which at least one is a foreign key (FK).

The transaction time in i-refactory is different from what is commonly understood by transaction time. Transaction time is usually seen as the moment when a fact was stored in the database. In the i-refactory, the transaction time is the time, as dictated by the source system, not by the i-refactory database.

The Attribute type links the attribute to one of the existing interfaces.

Computed columns are columns whose content is computed from values in other columns in the table.

Functional date A functional date or time is a point in time and is defined by a user. An example is an order date or date of birth.

The technical model (also known as Technical Staging In model: TSTGIN) is a representation of how exactly one delivery from a specific data source will be processed in the technical staging layer.

Generalization is the process of extracting shared characteristics from two or more classes (hyponyms), and combining them into a generalized superclass (hypernym). For example: an 'employee' and a 'customer' are both 'persons'.

The Mapping Editor provides a graphical interface for creating and viewing mappings between models. It provides a global view of all the mappings related to the entities of a given model, allowing you to quickly identify those which are mapped and not mapped.

When a certain fact can change over time and you need to capture when that fact is valid in the real world, you can add a valid start date and a valid end date to the entity.

A valid time tells us in which period a record is valid. While a functional date represents just one point in time, the valid time has a begin and an end date, for example:

  • For Order item 123, a Retail price of 10.00 was valid from 2019-01-01 to 2019-06-01.
  • For Order item 123, a Retail price of 12.00 was valid from 2019-06-01 to 2020-01-01.

Alternate key is an attribute or a group of attributes whose values uniquely identify every record in an entity, but which is not the primary key

Candidate key

A candidate key consists of one or more attributes and meets the following requirements:

  • Unique: The value of the key defines uniquely one instance of a concepts. There are no double values.
  • Non-volatile: (Almost) doesn't change.
  • Minimal: Contains only the elements needed.

There are two kinds of candidate keys:

  • primary key
  • alternative key

Normalization is the process of decomposing tables in a database in order to reduce data redundancy and improve data integrity.

A strongly typed model is a model in which each all attributes have a predefined data type, for example: integers, doubles, date.

Surrogate Key A surrogate key is a system generated unique identifier that does not have any contextual or business meaning.

Business Key

A business key is an unique identifier that has business meaning and exists in the real world outside of the database. It consists of a column or a set of columns that already exists in a table. A business key is also known as a natural key

A Key Root Hub is an integration concept that must be used when the exact same business concept or independent business key occurs in different models. The Hubs for this independent business key in the different UAM models are all subtypes of the Keyroot Hub.

A relationship shows how two entities are related to one another. For example, a customer can place an order, and a order can have a customer.

Every Attribute has an atomic type (data type) which is linked to the attribute type of that attribute.

The cardinality shows how many instances of an entity can take place in a relationship.

The cardinality shows how many instances of an entity can take place in a relationship.

An enumeration consists of the list of values that a given attribute should adhere to.

{example} An order can have different statuses, such as shipped,packing,created anddone. Other statuses are not allowed.

Foreign Key

A foreign key is an attribute or a set of attributes that refers to the primary key of another entity. The original entity containing the primary key is called the 'parent' entity and the entity containing the foreign key is called the 'child' entity.

A natural key is an unique identifier that has business meaning and exists in the real world outside of the database. It consists of an column or a set of columns that already exists in a table. A natural key is also known as a business key

The primary key is an assigned key that consists of a minimal set of attributes to uniquely specify an instance of a record. The attribute or a combination of attributes should meet the following characteristics:

  • Unique: The attribute values of the key uniquely identify one instance of a concept. There are no duplicate instances.
  • Non-volatile: The key does not change.
  • Mandatory: All values are filled; there are no NULL values.

It is good practice to choose a primary key that also meet the following characteristic:

  • Safe: Doesn't contain private or sensitive information, such as a social security number.

Constraints are related to the other elements depending of the type of the constraint. Certain constraints are associated to attributes, entities, helper entities, unique keys or relationships between entities.

An attribute may be assigned to one or more entities (ex: acm_exists_ind) and an entity may have several attributes

Each layer may have one or more interfaces. The amount of interfaces depend on how many tenants and delivery agreements have been configured.

Namespace is what in the terminology of SQL Server is called database schema.|

A Delivery is a container that holds the specification of what is actually pushed to the i-refactory platform. This specification consists of a list of entities.

A Delivery is a container that holds the specification of what is actually pushed to the i-refactory platform. This specification consists of a list of entities.

Key Root A Key Root is a central repository for Business Keys. A Key Root ensures that similar records out of different data sources are identified by both the same Business Key as the Surrogated Key.

Context

A Context is a temporal table with a transaction start and end date. The Context tracks all changes of the context attributes related to a business key in the transaction time. This means that every change of an attribute value in a source system leads to a new record in the Context. The old record is end dated with the load date and the new record is start dated with the load date.

Hyponym is a term that denotes a subcategory of a more general class. For example: 'cat' and 'dog' are a hyponyms of 'animal'.

A mapping establishes relationships between concepts of separate data models. It creates a link between entities and attributes from a source model to related entities and attributes in the target model. A source model should precede the target model in the i-refactory architecture.

oasi_bk is an abbreviation for One Attribute Set Interface (OASI) with business keys. A normal view in the generic data access layer (GDAL) consists of the surrogate key, foreign key and attributes. The oasi_bk-view in the GDAL is a view where the business key(s) are also shown.

A subtype is a subgroup of an entity. You can create a subtype if a group of instances share some attributes and relationships that only exist for that group. For example, entity Customer can have a subtype Company and a subtype Person. They share the common attribute customer number, and can have some attributes of their own. Such as birth date for a Person. The entity Customer is called a supertype.

A subtype:

  • inherits all attributes of the supertype
  • inherits all relationships of the supertype
  • usually has one or more own attributes
  • can have subtypes of its own

Anchor: Independent Entity

An Independent Entity is an entity that implements an Anchor for a Business Key that ‘stands alone’ e.g. that does not contain a reference to another Entity.

Anchor: Dependent Entity

A Dependent Entity is an entity that implements an Anchor for a Business Key that ‘depends’ in its existence on another Entity.

A domain will help you to identify the types of information in your model. It defines the set of values for which a column is valid. A domain can specify a data type, length, precision, mandatoriness, check parameters, and business rules. It can be applied to multiple columns, which makes it easier to standardize data characteristics for columns in different tables.

Each interface may have one or more entities and one entity belongs to only one interface. An entity belongs to an i-refactory data model.

Each interface may have one or more entities and one entity belongs to only one interface. An entity belongs to an i-refactory data model.

A helper entity creates a derived entity and can be used when you need to transform, filter, or calculate data. The purpose of a helper differs per model:

  • Technical model: a helper is used to transform data.
  • Logical validation model: a helper is an implementation of a set constraint (Set Constraint Helper).
  • Central facts model: a helper is used for a set-based calculation of derived facts (Business Rule Helper).

HSTGIN is the abbreviation of Historical STaging IN. It is an older term to indicate the Logical Validation Model or Logical Validation Layer.

A schema is a set of database objects, such as tables, views, triggers, stored procedures, etc. In some databases a schema is called a namespace. A schema always belongs to one database. However, a database may have one or multiple schema's. A database administrator (DBA) can set different user permissions for each schema.

Each database represents tables internally as <schema_name>.<table_name>, for example tpc_h.customer. A schema helps to distinguish between tables belonging to different data sources. For example, two tables in two schema's can share the same name: tpc_h.customer and complaints.customer.

A Tenant is a delivering party for a dataset or datarecord as agreed in the Delivery Agreement.

TSTGIN is the abbreviation of Technical STaging IN. It is an older term to indicate the Technical Model or Technical Staging Layer.

An index organizes data in a way that improves the speed of data retrieval from a database. To maintain the index data structure, there is a cost of additional writes and storage space.

An index organizes data in a way that improves the speed of data retrieval from a database. To maintain the index data structure, there is a cost of additional writes and storage space.

The acronym CRUD stands for create, read, update, and delete. These are the four basic functions of persistent storage.

OLAP is a acronym for Online Analytical Processing. OLAP is category of software tools which provide analysis of data for business decisions. It uses complex queries to analyze aggregated historical data from OLTP systems.The primary objective is data analysis and not data processing.

OLTP is a acronym for Online transaction processing. OLTP captures, stores, and processes data from transactions in real time. Its primary objective is data processing and not data analysis.

A hub or independent entity is an entity that implements an Anchor for a business key that ‘stands alone’ e.g. that does not contain a reference to another entity. An independent entity contains business key fields, that show up as alternate key (AK), and the primary key (PK) is its surrogate key (ID).

A key is a combination of one or more attributes of an entity that uniquely defines one instance of that entity.