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Making Mainframe Data Available on Snowflake

I don’t like to admit how long it took me to embrace the cloud. I would not say I was an early adopter. I understood the compute power available in the cloud, but I saw it as an environment for “new” data, not the place where you put your most valuable enterprise data. That type of data, the critical enterprise data, was on premises, often residing in the Mainframe. That is not going to change. Mainframes are going to remain at the center of many critical IT operations for the foreseeable future. They just work too well to be replaced right now. However, this does not mean that data on the Mainframe can’t be brought to the cloud for analytics. The cloud is going to be the focal point of new IT initiatives and the mainframe data is going to be part of those initiatives.

Fortunately for me I was already a cloud believer by the time I saw Snowflake, so I was ready to appreciate what a game changer it was. It was a data warehouse that could make full use of the advantages of the cloud without compromise because it had no debt to an on premise architecture. Storage and compute were decoupled and each individually scalable without any prior planning. At the same time, you could access all of this with SQL, which meant you could start without learning significant new skills and any existing work you had done elsewhere was readily ported over. It can be as good or better than any highly curated on premises solution while at the same time being cost effective and have zero administration overhead.

As capable as Snowflake is, like many modern platforms it still can’t make use of raw mainframe data. The data needs to be transformed before it can be consumed. Making mainframe data accessible outside the mainframe is something Syncsort has been doing for decades now. We started with doing mainframe style sorting on UNIX, but overtime extended our capabilities to include delivering ready to use data to Splunk and Hadoop. We are becoming the “go to” solution for getting your mainframe data into modern analytical solutions.

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Syncsort recently announced support for Snowflake, so we can deliver transformed mainframe data directly to their platform. Snowflake isn’t tied to a particular cloud vendor and neither is our solution. Using Connect ETL (formerly DMX) developers are going to be able to source, transform and load Mainframe data to Snowflake within a single flow. Once the data lands in Snowflake it will be entirely indistinguishable from other data source and immediately ready to be using in existing or new processes. I am really looking forward in bringing the capability to our existing customers and also finding new customer looking to bring their valuable Mainframe data to the cloud.

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