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.
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Transform Legacy Data Stores with Microsoft Azure and Precisely
- 1. Transform Legacy Data Stores: Microsoft and Precisely Precisely Connect and Microsoft Azure Partnership Overview Ashwin Ramachandran | Senior Product Manager
- 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. Challenges of legacy data in cloud ecosystems Complexity Governance Bottlenecks Scaling Precisely: Transform Legacy Data Stores: Microsoft and Precisely
- 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. 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. 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. 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. Precisely: Transform Legacy Data Stores: Microsoft and Precisely +
- 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. 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
Notes de l'éditeur
- 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