If you're looking for SAS DI Interview Questions for Experienced or Freshers, you are in the right place. There are a lot of opportunities from many reputed companies in the world. According to research, SAS DI has a market share of about 2.9%... So, You still have the opportunity to move ahead in your career as a SAS Data Integration Developer.
Mindmajix offers Advanced SAS Data Integration Interview Questions 2021 that help you in cracking your interview & acquire a dream career as SAS Data Integration Programmer.
Data Dimension in the SAS DI is defined as the data in between the customers, products, and organization that can be accessed with the governance of data. Generally, we need to acquire the best support of all the business data views with great self-service reporting.
With the help of this data dimension, you can completely view the strength and capability of the clients, products as well as organization.
The Data Access in SAS Data Integration is defined as approval that was selected by the particular business users for the sake of large data loads.
Data Governance in the Data Integration is a repeatable, affordable, and robust process, which downstream all the down checks. This process will able to manage all the updates that can maintain all the consistency of the data.
The exception reporting in the DI is mainly used to report the data which includes more data issues.
The multidimensional reporting in the DI will allow the users to make the aggregate analysis for the business metrics across a wide range of business dimensions.
The dimension table in SAS Data Integration is defined as the integral component for the fact table, as it contains more textual explanations regarding the business. These dimension tables in the DI is a well-designed model that may contain more attributes and columns, as they will describe the dimension of the row table and serves as the main source of reporting labels.
The staging area in the DI is defined as the data warehouse which can store the data and process it normally in order to extract more transformation. This data staging will always happen in between the data presentation area as well as the operational source systems.
The star schema in the DI is described as the set of the database where the single fact table is subjected to the multiple dimension tables, whereas the snowflake schema is stated as the single fact table is interlinked to the multiple sets of dimension tables in order to reduce all the themes.
A unique key in the DI is nothing but a key that contains one, two, or more columns, which can be usually used to identify the particular row in a table. The value of the unique key is always equal to null, whereas the primary key has one value that doesn't have a null value.
The SAS metadata server in the data integration will be able to provide all the metadata management services according to the request that will be raised on the client application. While the SAS application will directly provide their immense services to the customers without any hassle.
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The operating system in the data integration of SAS will have a set of multiple programs that can provide the major source for the particular data warehouse, whereas the operational data can provide the single source for an entire data warehouse.
The SAS Management Console in the Data Integration is mainly used to provide a great user interface in order to perform all the tasks that are done by the SAS administration.
Metadata Object is the transformation, which is used in the SAS DI in order to evaluate the process of extracting data into respective data stores.
The following are some of the listed data transformations which are mainly used in the SAS DI:
A metadata object is nothing but a group of attributes that describes a server, a user, a table, and other resources on a network.
In SAS Data Integration, change analysis is used to identify the differences between two sets of metadata and also compare 1 set to another set of metadata.
In SAS Data Integration, the interaction table tells the relationship between 2 or more tables.
Ex: consider the intersection table which describes the many-to-many relationships between the table of groups and table of users.
CONTROL-m is the scheduler for scheduling the job and also process flow, view, and dependencies for the user. So, they can optimize business processes efficiently, easily and data in a center that includes different platforms like Microsoft, Windows, VMS, and Unix.
By enabling the rapid generation of data warehouses, data streams, and data marts reduce the development time of SAS data integration. The SAS DI sometimes can have performance issues and generate very complex code that is very hard to decode.
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