BMC AMI Cloud Analytics transfers mainframe data to object storage in the cloud and then transforms it into open formats for use in cloud applications. It is the only solution that eliminates proprietary data silos without consuming mainframe CPU or requiring changes to your mainframe applications.

Integrate your Data with Cloud-Native AI/ML and Analytics Applications

BMC AMI Cloud Analytics can quickly transfer, transform, and integrate your mainframe data so you can add it to your data lake and use it in cloud-based artificial intelligence and machine learning (AI/ML) and analytics applications. Eliminate performance bottlenecks and put your data to work at the rhythm of your business, instead of the other way around.

• Monetize unlocked mainframe data
• Accelerate and scale mainframe data transformation projects
• Reduce mainframe MIPS charges with modern extract, load, transform (ELT) methods
• Improve on change data capture (CDC) tools

Mainframe to Cloud: A fast and efficient mainframe-to-cloud file transfer solution

With BMC AMI Cloud Analytics, clients can move petabytes of data between the mainframe and on-premises object storage or cloud object storage such as Amazon Simple Storage Service (Amazon S3) or Azure Blob Storage. The use cases are limitless, ranging from simply moving a file to an object storage platform inside the walls of your data center to moving large files for integration into a cloud application running on a public cloud.

Process Data: Use ELT to process data faster, at scale

Traditional ETL-dependent processes required picking data sets one at a time. BMC AMI Cloud Analytics uses zIIP to queue data for transfer over TCP/IP into the cloud. This speeds data extraction and transformation, making the processes highly scalable.

Transform Data: Transformation is done in the cloud, without consuming mainframe MIPS

BMC AMI Cloud Analytics uses an ELT architecture to deliver mainframe-formatted data to object storage in the cloud, and then transform it via the target platform. In contrast, the antiquated extract, transform, load (ETL) approach uses mainframe CPU processing to transform data into open formats first, and then move it into the cloud.

Change Data Capture: Get huge performance gains over CDC tools

CDC tools focus on replicating updates primarily in databases. BMC AMI Cloud Analytics does not impact online or batch windows, and directly delivers and transforms both live data from disk and historical data on tape to the cloud. Mainframe data sources include:

• IBM® Db2® image copy
• Virtual storage access methods (VSAM) data sets
• Sequential data sets
• Partitioned data sets
• Extended format data sets
• Db2 archive logs
• COBOL copybooks Target cloud formats and services include:
• JSON
• CSV
• XML file formats
• Amazon Athena
• Aurora
• QuickSight and Redshift
• Microsoft Azure HDInsight and SQL Data Warehouse
• Google BigQuery and BigTable
• Snowflake
• Apache Spark
• Hadoop
• Splunk