Top 29 Sas Di Interview Questions You Must Prepare 24.May.2024

  • Scheduling and executing the batch jobs.
  • Configuring, starting and stopping the real-time services
  • Adapters configuration and managing them.
  • Repository usage, Job Server configuration.
  • Access Server configuration.
  • Batch job publishing.
  • Real-time services publishing through web services.

SAS management console application provides a single user interface for performing SAS administrative tasks.

Physical Data Integration is all about creating new system that replicates data from the source systems. This process is done to manage the data independent of the original system. Data Warehouse is the example of Physical Data Integration. The benefits of PDI include data version management, combination of data from various sources, like mainframes, flat files, databases.

  • Alternate key is term also known as unique key.
  • Business key is one or more columns in a dimension table that comprise the primary key in a source table in an operational system.
  • Foreign key is one or more columns that are associated with a primary key or unique key in another table. A table can have one or more foreign keys. A foreign key is dependent upon its associated primary or unique key. In other words, a foreign key cannot exist without that primary or unique key.
  • Generated keys is used to implement surrogate keys and retained keys, one or more columns that are used to uniquely identify a row in a table. A table can have only one primary key. One or more columns in a primary key cannot contain null values. Retained key is a numeric column in a dimension table that is the primary key of that table.
  • Surrogate key is a column which contains unique integer values that are generated sequentially when rows are added and updated. In the associated fact table, the surrogate key is included as a foreign key in order to connect to specific dimensions.

Staging area of the data warehouse is both the storage area and set of process commonly referred as extract transformation load. The data staging area is everything between the operational source systems and the data presentation area.

NO_CACHE – It is used for not caching values.

PRE_LOAD_CACHE – Result column preloads and compares the column into the memory, prior to executing the lookup.

PRE_LOAD_CACHE is used when the table can exactly fit in the memory space.

DEMAND_LOAD_CACHE – Result column loads and compares the column into the memory when a function performs the execution.

DEMAND_LOAD_CACHE is suitable while looking up the highly repetitive values with small subset of data.

Change analysis is the process of comparing one set of metadata to another set of metadata and identifying the differences between the two sets of metadata.

  • No, Data Integration and ETL programming are different.
  • Passing of data to different systems from other systems is known as data integration.
  • It may integrate data within the same application.
  • ETL, on the other hand, is to extract the data from different sources.
  • The primary ETL tool job is to transform the data and loads into other objects or tables.

Browser-based analysis and reporting capabilities are provided by Metadata reports.

The DI Metadata Reports are generated on metadata that associates with Data Integration jobs.

Other BO applications those are associated with Data Integration.

Three modules are provided by Metadata Reports. They are:

  • Operational Dashboards.
  • Auto Documentation.
  • Impact and Lineage analysis.

  • The process of combining data from different resources.
  • The combined data is provided to the users with unified view.
  • Information from different enterprise domains are integrated – known as Enterprise Information Integration.
  • Useful for merging information from different technologies among enterprises.

Table that describes the relationships between two or more tables. For example, an intersection table could describe the many-to-many relationships between a table of users and a table of groups.

SAS application server provides SAS services to a client. On the other hand database server provides relational database service to a client. Oracle, DB2, and Teradata are examples of relational databases.  SAS OLAP server provides access to multidimensional data. SAS metadata server provides metadata management services to one or more client application.

It is the access by selected business users to raw (untransformed) data loads.

Companies are realizing that in order to succeed they need an integrated view of their data and SAS Data Integration Studio is the single tool that provides the flexibility, reliability and agility needed to respond to new data integration challenges. Regardless of the project, SAS Data Integration Studio users can respond with speed and efficiency, reducing the overall cost of data integration.

Star schema is defined as database in which single fact table is connected to multiple dimension tables. This is represented in a star schema.

Following are the benefits of data integration:

  • Makes reporting, monitoring, placing customer information across the enterprise flexible and convenient.
  • Data usage is efficient.
  • Cost Effective.
  • Risk adjusted profitability management as it allows accurate data extraction.
  • Allows timely and reliable reporting, as data quality is the prime technology for business challenges.

It is the robust, reliable, repeatable and controlled process both at point of input and through subsequent downstream control checks. This process exists to manage updates of business rules to maintain a level of consistency.

Operational data is used as source data for a data warehouse. While operational system is one or more programs that provide source data for a data warehouse.

SAS Data Integration Studio empowers data integration managers and designers to work more efficiently, manage change effectively and deliver high-quality results faster.

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  • Construction of parent/child relationships hierarchy is known as Hierarchy Flattening.
  • A description of hierarchy in the vertical or horizontal format is produced.
  • The hierarchy pattern includes Parent column, Child Column, Parent Attributes and Child Attributes.
  • Hierarchy Flattening allows to understand the basic hierarchy of BI in a lucid manner.
  • As the flattening is done in horizontal or vertical format, the sub elements are easily identified.

It is a metadata object which determines how to extract data, transform data and load data into data stores.

It is a set of attributes that describe a table, a server, a user and another resource on a network.

This is the technique for tracking changes to dimensional table values in order to analyze trends. For example, a dimension table named customers might have columns for customer id, home address and income. Each time the address or income changes for a customer, a new row could be created for that customer in the dimensional table and old row could be retained.

The scheduler used for scheduling job is control m while CONTROL-m also user to view process flow and dependencies so that they can optimize business processes easily and efficiently, even in a data center that includes multiple platform types (for example, Unix, Microsoft Windows, and MVS)

Snowflake schema is defined in which a single fact table is connected to multiple dimension tables. The dimension are structured to minimize update anomalies and to address single themes.

Types of the data transformation are append, apply lookup standardization, create match code transformation, data transfer, data validation, extract, fact table lookup, key effective data transformation, lookup, SAS rank, SAS sort, SAS splitter, SCD type 2 loader, SQL join, standardize transformation, Surrogate key generator , Transpose transformation, User written code transformation.

Following are the ways to perform this:

  • Using array fetch size.
  • Ordering the joins.
  • Extracted data minimizing.
  • Locale conversion minimization.
  • Setting target-based options to optimize the performance.
  • Improving throughput.
  • Data type conversion minimization.

Unique key is one or more columns that can be used to uniquely identify a row in a table. A table can have one or more unique keys. Unique keys can contain null values. While on the other hand table can have only one primary key. One or more columns in a primary key cannot contain null values.

Change analysis is the process of comparing one set of metadata to another set of metadata and identifying the differences between the two sets of metadata.