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For decades, mainframe data tasks have regularly included ETL – extract, transform and load – as a key step on the road to insights. Indeed, ETL has been the standard process for copying data from any given source into a destination application or system. ETL got a lot of visibility with the rise in data warehouse operations but was often a bottleneck in those same data warehouse projects.

Today, ETL is still the default choice for data movement, especially in the mainframe. But there is a legitimate alternative – ELT – extract, load, and transform.

As the reshuffling of terms implies, ELT takes a much different approach, first extracting data from wherever it currently resides and then loading it, generally to a target outside of the mainframe. It is there, wherever that “there” is, that the hard work of transform happens, typically as a prelude to the application of analytics.

So, ELT is an acronym, but one that’s pretty revolutionary. 

Why?  By reframing the idea of ETL with the technologies of today, the entire process has the potential to be faster, easier, and less expensive because it can use the most appropriate and cost-effective resources. Not just the mainframe CPU.

ELT tends to require less maintenance than ETL, which typically has many requirements for manual, ad hoc intervention and management. In contrast, ELT is based on automated, cloud-based processing.  Similarly, ELT loads more quickly, since transformation is closely linked to the ultimate cloud-based analysis work. ELT, then, is primarily concerned with getting data from mainframe to the cloud. Finally, of course, it is usually faster overall. And, because it depends primarily on pay-as-you-go cloud resources rather than on the billing structure of the mainframe, it is generally less expensive.

ELT empowers the routine and regular movement of mainframe operational and archived data from expensive and slow tape and VTL to storage environments that are both fast and highly cost-effective, such as AWS S3 Tiered Storage.  ELT can also deliver data directly for transformation to standard formats in the cloud – and then make that data available to data lakes and other modern BI and analytics tools.  Because ELT retains its original format and structure, the options for how the data can be used (transformed) in the cloud are practically unlimited.

The key to ELT on the mainframe is, of course, zIIP engines, the helpful processing capability provided by IBM for handling exactly this kind of `non-critical’ activity. It’s just that no one tried before.

With zIIP help and TCP/IP to assist in movement, buried data sets can be liberated from mainframe data silos and deliver real monetary value. What’s more, companies that have tried ELT have discovered how easy it is to move mainframe data. They can more easily take advantage of cloud storage economics –potentially eliminating bulky and expensive tape and VTL assets.For these many good reasons, ELT is `NJAA,’ not just another acronym – it’s an acronym worth getting to know.

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In addition to being an AWS ISV Partner, Model9 has now expanded the breadth and depth of its solutions in the AWS ecosystem. We are excited to announce that Model9 Cloud Data Manager for Mainframe can now be purchased on the AWS Marketplace.

Model9 has also achieved the AWS Migration Competency and is recognized through the Well-Architected Partner Program, based on the key concepts, design principles, and architectural best practices of the AWS Well-Architected Framework.

Model9 recognizes the C-level concerns with mainframe costs and lack of flexibility with mainframe data. Companies seeking to modernize and move mainframe data to the AWS cloud can start moving data today with Model9 Cloud Data Manager for Mainframe available on AWS Marketplace. Once the data is in Amazon S3, customers can immediately take advantage of other AWS services like Amazon Athena, Amazon Aurora, and Amazon QuickSight. Model9’s patented software solution for mainframe data management in the cloud, helps AWS customers efficiently and securely migrate mainframe data to the cloud where they can then get value from this data by leveraging AWS services, as well as get everything from AWS on one bill.

Model9 allows customers to confidently complete terabyte to petabyte scale mainframe data migrations quickly, providing enhanced time to value by unlocking the mainframe data to AWS analytics services in a matter of months versus multi-year migration projects.

You can get more information on the Model9-AWS partnership here or on the AWS Marketplace.

In the Sept. 2020 publication of IBM IT Economics Consulting & Research, the authors state, “zIIPs can enable clients to rapidly and inexpensively transform, extend and deploy applications into a hybrid cloud environment,” where “new applications can access cloud native services.”

They go on to acknowledge that much critical data – from the systems of record — lives in the mainframe environment but is needed in “systems of engagement” such as a “web enabled customer service application that retrieves customer records from a master DB2 database…”

We totally agree! In fact, leveraging this IBM-approved application of zIIP engines, Model9 long-ago learned to move any mainframe data to or from a cloud – potentially allowing an enterprise to eliminate its tape technology and sharply reduced archive and DR costs, while minimizing MSU consumption.

But, best of all, the freedom provided by Model9 means data access is dramatically improved, enabling an explosion of new analytic possibilities as well as new services and even new businesses.

IBM’s authors write that, “zIIPs can enable clients to rapidly and inexpensively transform, extend and deploy applications into a hybrid cloud environment.” Model9 has been finding ways to unlock and relocate this badly needed data.  Using an extract-load-transform (ELT) process that is much faster and easier than ETL and doesn’t require mainframe CPU cycles. Model9’s patented technology connects the mainframe directly over TCP/IP to cloud storage chosen by the customer. And from there, the analytical choices are numerous.

Best of all, because you can move data back to the mainframe as needed, just as easily, Model9 can even eliminate the need for virtual tape libraries and physical tapes. 

The reward that comes with liberating all that data is a true win-win – especially as companies around the globe struggle to make sense of the rapidly changing business conditions and emerging opportunities of 2020 and beyond.

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Model9 and MinIO are pleased to offer a joint data management solution that leverages powerful,
cloud-based object storage capabilities for the mainframe environment.

Model9 turns MinIO’s high-performance, low-cost object storage into a mainframe-ready, cloud-
based storage solution that helps modernize operations and allows enterprises to eliminate
outdated, costly tape and VTL systems.

The solution enables the migration of mainframe data, such as regulatory data or medical records, to
cost-effective, cloud-based object storage. In addition, it provides quick, universal access to valuable
historical and statistical data – that was previously available solely as “cold” storage, and readable
only by mainframes – for use in analytics, or in profit-oriented business intelligence initiatives.

Model9 and MinIO are affiliate members in Intel Capital’s investment portfolio, and have joined
forces to support the migration of mainframe data to cost-effective object storage on public and
private clouds.

Click here for more information about the Model9 / MinIO solution

Yes, our marketing department is growing, but that wasn’t the only reason for us to rebrand 🙂

Ever since our foundation, we’ve been examining our positioning between the mainframe and cloud ecosystems. At our core we are a group of mainframe experts who understand the challenges and needs that IT professionals are experiencing with these complex environments. With that said, our team expertise also include agile DevOps and Java, and our patented technology can move data anywhere – including public and private cloud – from within the recesses of a monolithic mainframe system.

Listening to our customers and partners, and aligned with the market trends, the answer today is clearer: our core is in the mainframe, but our future is in the cloud. 

Our new brand and product strategy reflects the acknowledgement that mainframe modernization is a journey. We help you take first steps, intermediate steps, and final steps – depending where you are on your journey. We are a software solution and not a service, and that’s unique. Our development efforts are in making it a ready to use software-based solution that can significantly simplify and shorten this journey.

But above all, our mission remains clear: to help companies liberate data and gain FULL access to the data oceans lurking in their mainframe environments, inaccessible to agile, modern, BI and analytics.

Whether you want to modernize, migrate, or just make a better use of your mainframe data, we can help!

We’re proud to be on TheMarker’s selected list of “most promising companies” for 2020!

Model9 is an innovator and disruptor of the mainframe market and a pioneer in cloud data management for mainframe. With a multi-disciplinary team of mainframe and cloud expertise, Model9 is trusted by global leading financial institutions, government agencies, retailers and transportation companies. Backed by Intel Capital and an AWS Advanced Technology Partner – we’re all set for success and the sky’s the limit!

Model9 and Cohesity are pleased to announce the rollout of a joint, unified, cloud data management platform that incorporates mainframe-based data and operations.

The joint Model9/Cohesity solution eliminates the need for legacy mainframe storage systems – such as tapes and VTLs, and provides enterprise users with a unified platform for cloud backup, archive, and DR operations.

The Model9 / Cohesity Environment:

Today, most mainframe data is hosted in proprietary storage silos, making the information difficult to manage and analyze.  The joint Model9/Cohesity solution meets this challenge, unlocking the mainframe data, and presenting enterprises with a unified, organization-wide data management platform – making the data accessible and easily leveraged for use by value-enhancing analytics and BI applications. 

The joint solution was recently deployed at a leading U.S. financial institution that wished to modernize their data center operations – retiring legacy backup and tape management products, reducing reliance on legacy mainframe skills, and adopting the solution’s easy-to-use graphical user interface.

Model9 is now also a part of the Cohesity Marketplace. Using the app, Cohesity customers can transition from an expensive Virtual Tape System to Cohesity DataPlatform, consolidating data silos – to be managed in one place.

Solution Benefits

The Joint Model9-Cohesity solution offers the following benefits:

  • Modernize backup, archive, and DR operations with a flexible software architecture that supports data management, on-premises or in any cloud.
  • No more data silos – manage organizational data operations across locations and technologies from a single, unified software platform.
  • Lower TCO by replacing tape systems, VTLs and tape-management software with affordable cloud data management.
  • Utilize the solution’s phenomenal deduplication capabilities to significantly reduce data footprint – leading to significantly lower costs and reduced risk.
  • Leverage mainframe data for value-added business intelligence initiatives and analytics

Click here for more information about the Model9 / Cohesity solution

Mainframe teams these days are expected to contain backup and archiving costs while ensuring minimum downtime, especially in disaster recovery situations. While full-blown disasters may be rare, costly outages and interruptions are not, and a recent ITIC survey reveals just how expensive they are:

  • 98% of organizations said that one hour of downtime costs over $100,000
  • 86% indicated that an hour of downtime costs their business over $300,000
  • 34% reported that one hour of downtime costs their firms $1–5 million

When designing a data management solution, it is important to explore cost-effective backup options that allow efficient recovery to cope with the enormous amounts of generated data. At the same time, it is also important to look into how to improve recovery efficiency even if it might increase the direct backup costs.

Reducing backup costs

The total cost of ownership (TCO) of mainframe data management consists of several direct and indirect costs. Using the following methods, an organization can reduce backup costs while still meeting demanding recovery requirements:

  • Incremental backup: Instead of backing up all data sets, implement solutions that support incremental backups and only back up data sets that have changed since the previous backup process.
  • Deduplication: A lot of storage space can be saved by eliminating duplicate copies of repeating data. It is therefore recommended to enable deduplication if your target storage system supports it.
  • Compression: Another way to contain data management costs is to ensure that backup data is compressed before it is sent over the network to the storage system.
  • Leveraging commodity storage: Maintaining tape-related hardware and software imposes substantial costs. Instead, a cost-efficient data management solution like Model9’s securely delivers mainframe data to any cloud or on-prem storage system. This makes it possible to benefit from pay-as-you-go cloud storage instead of stocking up on tapes and VTLs.

On top of the above-mentioned practices to reduce the TCO of the data management continuum, one should also factor in the costs of archiving data for longer periods of time to meet regulatory requirements. For example, banks have to keep masses of archived data for many years to comply with regulations, most of which will never be accessed. As explained here, selecting the right kind of storage for this type of data can significantly affect backup costs.

Improving recovery efficiency

A more efficient recovery often requires additional measures in the backup stage, which might actually increase backup costs. However, the staggering costs of unplanned downtime alone can justify the investment, not to mention the heavy non-compliance fees. The following methods can be used for a more efficient recovery:

  • Write Once Read Many (WORM) storage: Keeping backups on WORM storage in the cloud or on-premises prevents accidental or malicious erasure and tampering that will make recovery difficult, more expensive or subject to ransom. In the case of an event, immutable backup data in the cloud is available as soon as the system is up and running without needing to wait for archived data.
  • Multiple snapshots: Taking snapshots, also known as flash copies, of volumes and data sets at regular intervals helps to maintain data set versioning, which is important for automated recovery processes. Snapshots also make it possible to recover a data set in case of logical failure.
  • Stand-alone restore: Stand-alone restore allows bare-metal recovery from tape or cloud in cases of cyberattacks, disasters, and errors. Cloud-based backup platforms like Model9 enable IPL from a cloud server for a quick recovery that significantly reduces unplanned downtime.
  • End-to-end encryption: End-to-end encryption reduces the risk of malicious data corruption that could cause logical failures and other problems making recovery scenarios more complex and more expensive. Encryption is also critical for meeting regulatory requirements regarding data security and privacy.
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In the wake of the coronavirus pandemic, today’s new normal means companies employing remote work for business continuity and the safety and wellbeing of their employees. With a global footprint and employees spanning different continents, Model9 is well prepared to fully serve clients without disruption.  Adhering to federal, state and local guidelines, we are working safely from home leveraging technology to communicate internally as well as with our customers.

Our support team continues to offer the same professional support, utilizing our web-based service portal, video chat, and U.S.-based phone number to remain connected and available. Customers can manage their data with full visibility and control remotely from home while our customer success team spares no resources in helping you reach your goals.

Rest reassured that our team is healthy, committed, and on the job to successfully navigate this challenge together with you.

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