It isn’t going un-noticed why companies like Amazon, Home Depot, Samsung and TD Bank are adopting Apache Spark. Just to name a few. They, like many organizations, are struggling to manage both structured and unstructured data and deliver on objectives around being a data driven organization.
With SPARK, at a minimum, you get 100X improvement of data processing speeds, with the benefits of an open source infrastructure. Couple this with making your data scientists 5X as productive? Adopting SPARK as a future state data science platform is becoming a no-brainer.
However, the big challenge remains migrating from legacy platforms onto SPARK. With most organizations running SAS BI and Analytics tool sets, converting SAS to PySpark can be excruciatingly painful both in time and cost. Many organizations are applying a “brute force” approach to conversion, including offshoring the work which is resulting in cost and timeline overruns. The pain only intensifies as SAS license renewal fees loom with annual increases. Companies need to find ways to justify their move to SPARK with senior leadership through an ROI.
Here are the top 3 reasons why automating SAS to PySpark code migration makes sense for any organization:
#1: SPEED AND SIMPLICITY
A few key things you need to know about SPARK is that you can run programs 100’s of times faster than other legacy data processing systems like SAS, MapReduce, or R, and can scale to any size of data. With SPARK, you can use built-in libraries for data access, streaming, data integration, graph processing and advanced analytics and machine learning – all on one platform. SPARK’s meant to be a processing hub where it can connect many data sources — from relational and SQL databases, data lakes and warehouses and more — computing aggregations, data pre-processing and much more. Speed and simplicity are inherent in this multi purpose platform.
#2: GROWTH FROM AI INNOVATION
What does faster performance mean? It means you can now deliver on your demands around being data driven as an organization – leveraging data processing & analytics, including ML & AI pervasively. This will improve your Enterprise’s ability to grow from innovation. No longer having to depend on time consuming data processing for access to information, you’ll improve your Enterprise’s ability to deliver on growth objectives – all from AI innovation.
#3: ACCOUNTABILITY AND EMPOWERMENT
So now you are a data driven organization…what does this really mean? Netted out, it will allow your organization to enforce accountability at every level of the organization by empowering them with timely and accurate data. Gone will be the days of hiding behind “we don’t have the data to back up this recommendation or strategy”. It will enable you to develop and execute on strategy holistically across your Enterprise, independent of the silos of your organization.
WiseWithData, an expert in SPARK, introduces SPROCKET the world’s first fully automated SAS to SPARK migration product suite. Want to learn more? Contact us @ [email protected]
