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No, FILE FORMAT is not a DATASTORE TYPE.

No, File format is not a datastore type.

1. SCD Type 1 No HISTORY preservation
2. Natural consequence of normalization
3. SCD Type 2 Preserving all history and new rows
4. There are new rows generated for significant changes
5. You NEED to use of a unique KEY
6. There are new fields are generated to store history data
7. You need to MANAGE an Effective_Date field.
8. SCD Type 3 Limited history preservation
9. In this only two states of data are preserved - current and old

SCDS are DIMENSIONS that have DATA that CHANGES over TIME.

SCDs are dimensions that have data that changes over time.

If you update version of SAP Data Services, there is a need to update version of Repository.

Below points should be considered when migrating a central repository to upgrade version:

Point 1

Take the backup of central repository all tables and objects.

Point 2

To maintain version of objects in data services, maintain a central repository for each version. Create a new central history with new version of Data Services SOFTWARE and copy all objects to this repository.

Point 3

It is always recommended if you install new version of Data Services, you should upgrade your central repository to new version of objects.

Point 4

Also upgrade your local repository to same version as different version of central and local repository may not work at the same time.

Point 5

Before migrating the central repository, check in all the objects. As you don’t upgrade central and local repository SIMULTANEOUSLY, so there is a need to check in all the objects. As once you have your central repository upgraded to new version, you will not be able to check in objects from local repository which is having older version of Data Services.

If you update version of SAP Data Services, there is a need to update version of Repository.

Below points should be considered when migrating a central repository to upgrade version:

Point 1

Take the backup of central repository all tables and objects.

Point 2

To maintain version of objects in data services, maintain a central repository for each version. Create a new central history with new version of Data Services software and copy all objects to this repository.

Point 3

It is always recommended if you install new version of Data Services, you should upgrade your central repository to new version of objects.

Point 4

Also upgrade your local repository to same version as different version of central and local repository may not work at the same time.

Point 5

Before migrating the central repository, check in all the objects. As you don’t upgrade central and local repository simultaneously, so there is a need to check in all the objects. As once you have your central repository upgraded to new version, you will not be able to check in objects from local repository which is having older version of Data Services.

One Input: EMBEDDED data flow is ADDED at the end of dataflow.

One Output: Embedded data flow is added at the BEGINNING of a data flow.

No input or output: REPLICATE an existing data flow.

One Input: Embedded data flow is added at the end of dataflow.

One Output: Embedded data flow is added at the beginning of a data flow.

No input or output: Replicate an existing data flow.

Embedded DATA FLOW is known as data flows which are called from another data flow in the design. The embedded data flow can contain MULTIPLE number of source and TARGETS but only one input or output pass data to MAIN data flow.

Embedded data flow is known as data flows which are called from another data flow in the design. The embedded data flow can contain multiple number of source and targets but only one input or output pass data to main data flow.

This is most common TRANSFORMATION used in Data Services and you can perform below functions:

1. Data filtering from sources
2. Joining data from multiple sources
3. Perform functions and transformations on data
4. Column mapping from input to OUTPUT schemas
5. Assigning PRIMARY KEYS
6. Add new columns, schemas and functions resulted to output schemas
7. As Query transformation is most commonly used transformation, so a SHORTCUT is provided for this query in tool palette.

This is most common transformation used in Data Services and you can perform below functions:

• Data INTEGRATION
• Data Quality
• Platform
• MERGE
• QUERY
• Text data processing

TRANSFORMS are used to manipulate data sets as inputs and CREATING one or multiple outputs. There are VARIOUS transforms that can be used in Data SERVICES.

Transforms are used to manipulate data sets as inputs and creating one or multiple outputs. There are various transforms that can be used in Data Services.

You can also ADD Conditionals to workflow. This ALLOWS you to implement If/Else/Then logic on the WORKFLOWS.

You can also add Conditionals to workflow. This allows you to implement If/Else/Then logic on the workflows.

There is a fact table that you want to update and you have created a data flow with the transformation. Now If you want to move the data from source system, you have to check last MODIFICATION for fact table so that you EXTRACT only rows that has been added after last update.

In order to achieve this, you have to create one script which determines last update DATE and then PASS this as input parameter to data flow.

You also have to check if data connection to a PARTICULAR fact table is active or not. If it is not active, you need to setup a catch block which automatically sends an email to administrator to notify about this problem.

There is a fact table that you want to update and you have created a data flow with the transformation. Now If you want to move the data from source system, you have to check last modification for fact table so that you extract only rows that has been added after last update.

In order to achieve this, you have to create one script which determines last update date and then pass this as input parameter to data flow.

You also have to check if data connection to a particular fact table is active or not. If it is not active, you need to setup a catch block which automatically sends an email to administrator to notify about this problem.

Yes

Yes

Data flow is used to extract, transform and load data from SOURCE to target system. All the transformations, loading and formatting occurs in DATAFLOW.

Data flow is used to extract, transform and load data from source to target system. All the transformations, loading and formatting occurs in dataflow.

You can use Microsoft Excel workbook as data SOURCE using file formats in Data Services. Excel WORK book should be available on WINDOWS file SYSTEM or Unix File system.

You can use Microsoft Excel workbook as data source using file formats in Data Services. Excel work book should be available on Windows file system or Unix File system.

1. DELIMITED
2. SAP Transport
3. Unstructured TEXT
4. Unstructured BINARY
5. Fixed WIDTH

Adapter Datastore allows you to import APPLICATION metadata into repository. You can also access application metadata and you can also move batch and real TIME data between DIFFERENT applications and SOFTWARE.

Adapter Datastore allows you to import application metadata into repository. You can also access application metadata and you can also move batch and real time data between different applications and software.

There are various database vendors which only provides one way communication path from one database to another database. These paths are known as database links. In SQL Server, Linked server allows one way communication path from one database to other.

Example:

Consider a LOCAL database Server name “Product” stores database link to access information on remote database server called Customer. Now users that are connected to remote database server Customer can’t use the same link to access data in database server Product. USER that are connected to “Customer” should have a separate link in data dictionary of the server to access the data in Product database server.

This communication path between two databases are called database link and Datastores which are created between these linked database relationships is known as linked Datastores.

There is a POSSIBILITY to connect DATASTORE to another Datastore and importing an external database link as option of Datastore.

There are various database vendors which only provides one way communication path from one database to another database. These paths are known as database links. In SQL Server, Linked server allows one way communication path from one database to other.

Example:

Consider a local database Server name “Product” stores database link to access information on remote database server called Customer. Now users that are connected to remote database server Customer can’t use the same link to access data in database server Product. User that are connected to “Customer” should have a separate link in data dictionary of the server to access the data in Product database server.

This communication path between two databases are called database link and Datastores which are created between these linked database relationships is known as linked Datastores.

There is a possibility to connect Datastore to another Datastore and importing an external database link as option of Datastore.

You can create Datastore using memory as DATABASE type. Memory Datastore are used to improve the performance of data flows in real time jobs as it STORES the data in memory to facilitate quick access and doesn’t require to go to ORIGINAL data source.

A memory Datastore is used to store memory table schemas in the repository. These memory tables get data from tables in Relational database or using hierarchical data files like XML MESSAGE and IDocs.

The memory tables remain alive till job executes and data in memory tables can’t be shared between DIFFERENT real time jobs.

You can create Datastore using memory as database type. Memory Datastore are used to improve the performance of data flows in real time jobs as it stores the data in memory to facilitate quick access and doesn’t require to go to original data source.

A memory Datastore is used to store memory table schemas in the repository. These memory tables get data from tables in Relational database or using hierarchical data files like XML message and IDocs.

The memory tables remain alive till job executes and data in memory tables can’t be shared between different real time jobs.

In OBJECT LIBRARY in DS DESIGNER.

In Object library in DS Designer.

It is a developer TOOL which is used to create objects consist of data MAPPING, transformation, and logic. It is GUI BASED and work as designer for Data Services.

You can create various objects using Data Services Designer like PROJECT, Jobs, Work Flow, Data Flow, mapping, transformations, etc.

It is a developer tool which is used to create objects consist of data mapping, transformation, and logic. It is GUI based and work as designer for Data Services.

You can create various objects using Data Services Designer like Project, Jobs, Work Flow, Data Flow, mapping, transformations, etc.

DS Management CONSOLE → JOB EXECUTION HISTORY

DS Management Console → Job Execution History

In DATA Services, you can create a TEMPLATE table to move to TARGET system that has same STRUCTURE and data type as SOURCE table.

In Data Services, you can create a template table to move to target system that has same structure and data type as source table.

DATA SERVICES MANAGEMENT CONSOLE

Data Services Management Console

CENTRAL repository is used to control the version management of the objects and is used for multiuse development. Central Repository STORES all the VERSIONS of an application OBJECT so it allows you to move to previous versions.

Central repository is used to control the version management of the objects and is used for multiuse development. Central Repository stores all the versions of an application object so it allows you to move to previous versions.

To CREATE BODS Repository you need a database installed. You can use SQL Server, ORACLE database, My SQL, SAP HANA, Sybase, etc. You have to create below users in database while installing BODS and to create Repositories. These users are REQUIRED to login to different servers CMS Server, AUDIT Server. To create a new repository, you have to login to Repository manager.

To create BODS Repository you need a database installed. You can use SQL Server, Oracle database, My SQL, SAP HANA, Sybase, etc. You have to create below users in database while installing BODS and to create Repositories. These users are required to login to different servers CMS Server, Audit Server. To create a new repository, you have to login to Repository manager.

Reusable Objects:

Most of the objects that are stored in REPOSITORY can be reused. When a reusable objects is defined and save in the local repository, you can reuse the object by creating calls to the definition. Each reusable object has only one definition and all the calls to that object refer to that definition. Now if definition of an object is changed at one place you are CHANGING object definition at all the PLACES where that object appears.

An object library is used to contain object definition and when an object is drag and drop from library, it means a new reference to an existing object is created.

SINGLE USE Objects:

All the objects that are defined specifically to a job or data flow, they are called single use objects. Example-specific transformation used in any data load.

Reusable Objects:

Most of the objects that are stored in repository can be reused. When a reusable objects is defined and save in the local repository, you can reuse the object by creating calls to the definition. Each reusable object has only one definition and all the calls to that object refer to that definition. Now if definition of an object is changed at one place you are changing object definition at all the places where that object appears.

An object library is used to contain object definition and when an object is drag and drop from library, it means a new reference to an existing object is created.

Single Use Objects:

All the objects that are defined specifically to a job or data flow, they are called single use objects. Example-specific transformation used in any data load.

Repository is used to store meta-data of objects used in BO Data Services. Each Repository should be registered in Central Management Console CMC and is linked with SINGLE or many job servers which is responsible to execute jobs that are created by you.

There are three types of Repositories:

Local Repository:

It is used to store the METADATA of all objects created in Data Services Designer LIKE project, jobs, data flow, work flow, etc.

Central Repository:

It is used to control the version management of the objects and is used for multiuse development. Central Repository stores all the versions of an APPLICATION object so it allows you to move to previous versions.

Profiler Repository:

This is used to manage all the metadata related to profiler tasks performed in SAP BODS designer. CMS Repository stores metadata of all the tasks performed in CMC on BI platform. Information Steward Repository stores all the metadata of profiling tasks and objects created in information steward.

Repository is used to store meta-data of objects used in BO Data Services. Each Repository should be registered in Central Management Console CMC and is linked with single or many job servers which is responsible to execute jobs that are created by you.

There are three types of Repositories:

Local Repository:

It is used to store the metadata of all objects created in Data Services Designer like project, jobs, data flow, work flow, etc.

Central Repository:

It is used to control the version management of the objects and is used for multiuse development. Central Repository stores all the versions of an application object so it allows you to move to previous versions.

Profiler Repository:

This is used to manage all the metadata related to profiler tasks performed in SAP BODS designer. CMS Repository stores metadata of all the tasks performed in CMC on BI platform. Information Steward Repository stores all the metadata of profiling tasks and objects created in information steward.

SAP BO DATA SERVICES is an ETL tool used for Data integration, data quality, data profiling and data PROCESSING and ALLOWS you to integrate, transform trusted data to data warehouse system for analytical reporting.

BO Data Services consists of a UI development interface, metadata repository, data connectivity to SOURCE and target system and management console for scheduling of jobs.

SAP BO Data Services is an ETL tool used for Data integration, data quality, data profiling and data processing and allows you to integrate, transform trusted data to data warehouse system for analytical reporting.

BO Data Services consists of a UI development interface, metadata repository, data connectivity to source and target system and management console for scheduling of jobs.

There is a staging area that is required during ETL load.

There are VARIOUS reasons why a staging area is required:

As source systems are only available for specific period of time to extract data and this time is less than TOTAL data load time so Staging area allows you to extract the data from source system and keep it in staging area before time slot is ended.

Staging area is required when you want to get data from multiple data sources together. If you want to JOIN two or more systems together. Example- You will not be able to perform a SQL query joining two tables from two physically different databases.

Data EXTRACTIONS time slot for different systems vary as per the time zone and operational hours.

Data extracted from source systems can be used in multiple data warehouse system, Operation Data stores, etc.

During ETL you can perform complex transformations that allows you to perform complex transformations and require extra area to store the data.

There is a staging area that is required during ETL load.

There are various reasons why a staging area is required:

As source systems are only available for specific period of time to extract data and this time is less than total data load time so Staging area allows you to extract the data from source system and keep it in staging area before time slot is ended.

Staging area is required when you want to get data from multiple data sources together. If you want to join two or more systems together. Example- You will not be able to perform a SQL query joining two tables from two physically different databases.

Data extractions time slot for different systems vary as per the time zone and operational hours.

Data extracted from source systems can be used in multiple data warehouse system, Operation Data stores, etc.

During ETL you can perform complex transformations that allows you to perform complex transformations and require extra area to store the data.

Indexes: OLTP system has only few indexes while in an OLAP system there are many indexes for performance optimization.

Joins: In an OLTP system, LARGE NUMBER of joins and data is normalized however in an OLAP system there are less joins and de-normalized.

AGGREGATION: In an OLTP system data is not AGGREGATED while in an OLAP database more aggregations are used.

Indexes: OLTP system has only few indexes while in an OLAP system there are many indexes for performance optimization.

Joins: In an OLTP system, large number of joins and data is normalized however in an OLAP system there are less joins and de-normalized.

Aggregation: In an OLTP system data is not aggregated while in an OLAP database more aggregations are used.

1. Using the auto-correct load option in the target table.
2. INCLUDING the Table Comparison transform in the data FLOW.
3. Designing the data flow to completely replace the target table during each EXECUTION.
4. Including a preload SQL statement to EXECUTE before the table loads.

The Data CLEANSE transform can generate NAME match standards and greetings. It can also assign gender CODES and prenames such as Mr. and MRS.

The Data Cleanse transform can generate name match standards and greetings. It can also assign gender codes and prenames such as Mr. and Mrs.

Use the USA Regulatory transform if USPS certification and/or additional options such as DPV and Geocode are required. GLOBAL ADDRESS Cleanse should be utilized when processing multi-country data.

Use the USA Regulatory transform if USPS certification and/or additional options such as DPV and Geocode are required. Global Address Cleanse should be utilized when processing multi-country data.

1. Data Cleanse: Parse names into GIVEN and FAMILY.
2. ADDRESS Cleanse: VALIDATE address information.
3. MATCH: Find duplicates.

1. Enhancement Benefit
2. Determine gender DISTRIBUTIONS and target
3. Gender CODES MARKETING campaigns
4. Provide fields for IMPROVING matching
5. Match STANDARDS results

1. Global_Address_Cleanse
2. Data_Cleanse
3. MATCH
4. ASSOCIATE
5. Country_id
6. USA_Regulatory_Address_Cleanse

1. Data_Transfer
2. Date_Generation
3. Effective_Date
4. Hierarchy_Flattening
5. History_Preserving
6. Key_Generation
7. Map_CDC_Operation
8. PIVOT REVERSE Pivot
9. Table_Comparison
10. XML_Pipeline

The MERGE TRANSFORM.

The Merge transform.

DISCRETE, MULTILINE, and HYBRID.

Discrete, multiline, and hybrid.

The DataServices repository is a SET of TABLES that holds user-created and predefined system objects, source and TARGET METADATA, and transformation rules.

There are 3 types of repositories.

1. A local repository
2. A CENTRAL repository
3. A profiler repository

The DataServices repository is a set of tables that holds user-created and predefined system objects, source and target metadata, and transformation rules.

There are 3 types of repositories.

FILE FORMAT

File Format

REMOVE redundant and OBSOLETE OBJECTS from the REPOSITORY tables.

Remove redundant and obsolete objects from the repository tables.

Three.

1. Database Datastores: PROVIDE a simple way to import metadata directly from an RDBMS.
2. APPLICATION Datastores: let USERS EASILY import metadata from most Enterprise Resource Planning (ERP) systems.
3. Adapter Datastores: can provide access to an application’s data and metadata or just metadata.

Three.

PROJECT, JOB, WORKFLOW, DATAFLOW.

Project, Job, Workflow, Dataflow.

1. A job is the smallest unit of WORK that you can SCHEDULE independently for execution.
2. A work flow defines the decision-making process for executing data flows.
3. Data flows extract, transform, and LOAD data. Everything having to do with data, including reading sources, transforming data, and LOADING targets, occurs inside a data flow.

DATA Services INCLUDES the following standard components:

• Designer
• Repository
• Job Server
• Engines
• Access Server
• Adapters
• Real-time Services
• ADDRESS Server
• Cleansing PACKAGES, DICTIONARIES, and Directories
• Management Console

Data Services includes the following standard components:

BusinessObjects Data Services provides a graphical interface that allows you to EASILY create jobs that EXTRACT data from heterogeneous sources, transform that data to meet the BUSINESS requirements of your organization, and load the data into a single LOCATION.

BusinessObjects Data Services provides a graphical interface that allows you to easily create jobs that extract data from heterogeneous sources, transform that data to meet the business requirements of your organization, and load the data into a single location.