Offload Mainframe Processing to Hadoop Using Diyotta

Rapidly increase Hadoop ROI by offloading legacy batch processes with Diyotta’s mainframe capabilities.

Offloading Mainframe Data to Hadoop

Diyotta addresses the challenges below and provides an easy, drag & drop interface to quickly and efficiently build the data pipelines without any technical knowledge on SnowSQL. Additionally, you can convert the existing stored procs or scripts into metadata driven processes that can run in a set-based manner on Snowflake using Diyotta.
Seamlessly supports complex structures like OCCURS, REDEFINES and multiple code pages along with Packed Decimal formats
Generates any target definition on Hive, BigSQL or platforms based on COBOL copybook definitions
Leverages distributed computing power of Hadoop to parse massive volumes of EBCDIC data
Ingests EBCDIC files from native or remote locations and convert to ASCII with inbuilt ASCII conversion process
Enrich data with heterogeneous transformations before loading to final target structures
Historical data migration from On-Premise systems
Source data from SaaS applications
Perform transformations using Snowflake’s processing power (ELT on Snowflake)
Provision data from Snowflake for analytics or downstream applications
Orchestrate data movement and transformations across data flows

Eliminate Legacy Platform Limitations

Organizations that have mainframe systems typically have large data volumes and processes buried within legacy applications. Often this data is difficult to access for analytics. Diyotta uses business logic to parse and load EBCDIC data into Hadoop to exploit its distributed processing capabilities. Once deployed, mainframe data can be used to address data mining and analytics needs quickly and efficiently.

Ingest EBCDIC files by importing COBOL copybooks

Seamlessly supports complex structures like OCCURS, REDEFINES and multiple code pages

Leverages distributed computing power of Hadoop to parse massive volumes of EBCDIC data

Accelerate data availability by ingesting, transforming and provisioning mainframe data into Hadoop

Enrich data by performing transformations before loading to final target structures

Enhance data analytics by combining mainframe data with new data sets

Diyotta leverages Hadoop and makes it easier for organizations to offload mainframe batch processes without requiring extensive technical skills. Unleash mainframe data for comprehensive analytics and actionable intelligence.

Reduce Complexity

No coding or special skills
required on Hive, MapReduce, etc.

Fast Setup

Significantly reduce development time
using MDI Suite vs custom scripts

Mainframe Offloading

Build a sustainable solution that is
easier to maintain than other approaches