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Transform Legacy Data Stores with Microsoft Azure and Precisely

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Transform Legacy Data Stores with Microsoft Azure and Precisely

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Cloud ecosystems have the power to transform a business by delivering quick insights at a low cost. But when you must connect legacy systems like mainframe and IBM i to the cloud, your project can become expensive, time-consuming, and reliant on highly specialized skillsets. So much for low cost and efficiency!

During this session gain a deeper understanding of that value that data from mainframe and IBM i systems can bring to the Microsoft Azure ecosystem.

Cloud ecosystems have the power to transform a business by delivering quick insights at a low cost. But when you must connect legacy systems like mainframe and IBM i to the cloud, your project can become expensive, time-consuming, and reliant on highly specialized skillsets. So much for low cost and efficiency!

During this session gain a deeper understanding of that value that data from mainframe and IBM i systems can bring to the Microsoft Azure ecosystem.

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Transform Legacy Data Stores with Microsoft Azure and Precisely

  1. 1. Transform Legacy Data Stores: Microsoft and Precisely Precisely Connect and Microsoft Azure Partnership Overview Ashwin Ramachandran | Senior Product Manager
  2. 2. Housekeeping Webinar Audio • Today’s webcast audio is streamed through your computer speakers • If you need technical assistance with the web interface or audio, please reach out to us using the Q&A box Questions Welcome • Submit your questions at any time during the presentation using the Q&A box Recording and slides • This webinar is being recorded. You will receive an email following the webinar with a link to the recording and slides
  3. 3. Challenges of legacy data in cloud ecosystems Complexity Governance Bottlenecks Scaling Precisely: Transform Legacy Data Stores: Microsoft and Precisely
  4. 4. Data complexity, all your data to the cloud How fast can you unlock legacy data for use in cloud environments? Are the solutions you are using today slowing down or improving processing? Will open source frameworks help address the complexities of legacy data? Do you have legacy data expertise in-house or will you have to seek external resources to access data? Precisely: Transform Legacy Data Stores: Microsoft and Precisely
  5. 5. Lorem ipsum dolor ete sit amet, consectetur Precisely: Transform Legacy Data Stores: Microsoft and Precisely Data governance must cover entire data lifecycle Consider the full data lifecycle Have a metadata strategy in place Clear understanding of data movement Data replication and data lineage are critical foundations
  6. 6. Precisely: Transform Legacy Data Stores: Microsoft and Precisely Data bottlenecks, prevent a single point of failure Native connectivity to target cloud environment Enable a design once, deploy anywhere approach Have no impact on performance Guarantee data delivery ✔ ✔ ✔ ✔ YES NO
  7. 7. Data scaling for real- time business needs • Consider real-time data delivery may break current data pipelines • Select solutions that have reliable transfer of information • Keep in mind streaming platforms such as Kafka on Azure could enable real- time delivery • Assess how your overall cloud strategy supports real-time data delivery Precisely: Transform Legacy Data Stores: Microsoft and Precisely
  8. 8. Precisely: Transform Legacy Data Stores: Microsoft and Precisely +
  9. 9. Connect unlocks data for Microsoft Azure Expertise in legacy data No installation of software on mainframe Use existing metadata Quickly understand and access legacy data Precisely: Transform Legacy Data Stores: Microsoft and Precisely
  10. 10. Precisely: Transform Legacy Data Stores: Microsoft and Precisely Precisely Connect and Microsoft Azure ecosystem Data Lake Analytics Azure Analysis Azure Databricks (Python, Scala, Spark SQL, Sparkfl, Spark MI, SparklyR) Azure Data Lake Storage Azure Synapse Analytics Mainframe Ingest Store Prep and Train PolyBase Model and Serve Business/custom apps(structured) 1 2 4 5 Logs, files, and media (unstructured) 3 SQL

Notas del editor

  • Data complexity: Legacy data is not readily compatible with cloud ecosystems
    Data governance: Copybooks no longer match data, metadata unreadable, record descriptors and data copies lost
    Data bottlenecks: Loading large data sets to the cloud can drag down performance and increase time to insight
    Data scaling: Data is delivered on a delay causing loss in efficiency and inability to deliver at speed of business
  • Legacy data can provide a treasure-trove of information that can transform your business when used within cloud ecosystems
    Consider the speed in which you need you are able to unlock legacy data for use in your cloud environments
    Understand how the solutions you are using today handle variable length records – are they slowing down processing?
    Determine if open-source frameworks will work for your business – mainframe data is not readily compatible with open system data formats in the cloud
    Do you have legacy data expertise in-house or will you have to seek external resources to access data?
  • Moving to the cloud means you must guarantee that high data quality exists throughout the complete lifecycle of the data

    Change data capture and data lineage foundational elements for a data governance strategy for legacy data
    Change Data Capture - what changed the in data
    Data Lineage – where that came from
    Understand how when moving data to the cloud, most tools will unpack, expand, and convert data to readable formats
    Determine how you can use existing metadata including copybooks to meet tightening SLAs
  • A single point of failure and throughput forces performance and reliability of your data that is being connected to the cloud

    Determine if there is native connectivity to the cloud environment you want to move mainframe data to
    Calculate: how much time and effort will it take to load database resources into cloud environments
    How will mainframe data ingestion effect performance overall?
    Consider where your single point of failure exists
  • Tracking and detection of data changes needs to be presented to as close to real-time as possible

    Consider that faster data delivery may break current data pipeline structures
    Look for solutions that insulate your organization against the underlying complexities of your technology stack
    Select solutions that guarantee data delivery and have reliable transfer of information
    Look at how streaming platforms such as Kafka on Azure could be leveraged to feed real-time delivery
    Assess how your overall cloud strategy can support real-time data delivery
  • Precisely Connect offers:
    50 years+ of Mainframe expertise

    No installation of software on the mainframe needed to restructure mainframe and IBM i data into readable formats for use with Azure services
    VSAM connections via: FTP, FTPS, Connect:Direct
    Db2/z connections via: ODBC or JDBC

    Leverage existing metadata including copybooks to meet tightening SLAs
    Convert packed decimal, zoned decimals to readable formats
    On ingestion, handle COBOL high/low values
    Quickly and easily convert EBCDIC to Unicode
    Handle REDEFINEs in COBOL copybooks
    Ingest OCCURS DEPENDING ON variable length arrays

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