Automated Workload Transformation from SAS to PySpark

SAS migration to modern data platforms like PySpark enables businesses to unlock their true potential.

Enterprises are modernizing their data platforms to minimize costs, achieve faster real-time insights, and ensure greater scalability. SAS migration to modern data platforms like PySpark enables businesses to unlock their true potential. However, the path to modernization can be challenging and time-consuming.

LeapLogic can change that!

With LeapLogic’s scalability, flexibility, and unmatched performance, you can automate SAS to PySpark migration with up to 95% and minimize costs, effort, and risk.

Check out how LeapLogic automates the end-to-end SAS migration process with its proven 4-step approach:

Assessment

LeapLogic’s first step in the SAS to PySpark migration journey is to assess the level of script complexity and segregate analytical scripts into three workload types:

  • Procedural
  • Statistical
  • Advanced algorithmic workloads

Furthermore, LeapLogic provides in-depth insights, such as data steps, procedural constructs, and more.

In addition, LeapLogic provides detailed reports that you can use offline to analyze the assessment results and make informed business decisions.


Transformation

LeapLogic performs end-to-end transformation of SAS workloads to PySpark by implementing three stages:

Migration

Converts the schema to PySpark-equivalent and migrates all the available data into PySpark data warehouse tables

Data validation

Authenticates and certifies all the migrated data

Transformation

Modifies the SAS code and business logic to PySpark-equivalent code

With the unmatched power of LeapLogic’s intelligent transformation engine, enterprises can save significant manual effort in mapping and converting all functions, keywords, and constructs during SAS migration to PySpark.


Validation

Once LeapLogic transforms all the legacy code, it auto-generates reconciliation PySpark scripts and offers unit and integration testing to further optimize the data on the target environment.

LeapLogic also offers cell-to-cell validation reports, file-to-file validation, data type, and entity-level matching.


Operationalization

When we say end-to-end, we mean it!

Using target executable packaging, LeapLogic integrates legacy tools and existing processes to PySpark-native orchestrators. When migrating workloads from SAS to PySpark, LeapLogic also ensures operationalization of the migrated workloads on PySpark.

LeapLogic assists with capacity planning, ensuring performance of the workloads in your new PySpark-native stack.


What value do you get out of these?

Automated, secure, risk-free, and affordable modernization and migration of your workloads without any business disruption.

Choose LeapLogic today to accelerate and automate your SAS migration journey to PySpark. It’s more than the next step – it’s a leap into the future of your business.