With COVID-19 and the current market uncertainty, every business leader is under unprecedented pressure to cut their expenses while still ensuring business continuity – no one, more so than the CIO. Enabling this new reality of virtual collaboration, automation and self-service while supporting the increased focus on data, analytics and AI is forcing IT leaders to reduce complexity and consolidate their offerings. Despite these hurdles, a downturn like we are experiencing today can be an opportunity. Remember that some of the most successful companies like WhatsApp and Uber were born during the global economic crisis of 2008. It is critical that we realize this crisis too shall pass but our actions and decisions today will have far reaching implications.

IBM’s Cloud Pak for Data is purposely built to deliver significant cost savings while laying the foundation for a modern data architecture for successful AI. It can be flexibly deployed on any public or private cloud allowing customers to choose the environment that best suits their needs and also avoiding vendor lock-in. The fact that it embeds and runs on top of Red Hat OpenShift means that it inherits a number of cloud native benefits including auto provisioning and scaling, seamless upgrades, built-in high availability, common logging, metering, monitoring etc. Among all the potential cost savings, there are four that resonate with our customers. They are:

1. Reduce data storage and movement costs through Data Virtualization
2. Consolidate Data and AI capabilities into an integrated platform
3. Minimize infrastructure and maintenance costs with a modern cloud native architecture
4. Streamline governance & security while ensuring compliance

Each of the above cost-savings are significant in their own merit but when combined with the prospect of a modern platform can amplify  benefits multiple fold. Stated otherwise, Cloud Pak for Data enables customers to easy adapt to  changing market conditions while delivering the much needed cost savings at the same time. Let’s look into these four  areas in depth and how one can progressively adopt the platform.

1. Reduce data storage and movement costs

Historically, companies have tried to break down silos by copying data from different operational systems into central data stores, such as data marts, data warehouses and data lakes, for analysis. While this is still very relevant for certain use cases, the time, money and resources required make it prohibitive to scale every time a business user or data scientist needs new data. Extracting, transforming and consolidating data is resource intensive, expensive and time consuming and could be avoided through data virtualization. Tap into data at the source to remove complexity and incremental governance, security and storage requirements of duplicating data.  This also helps simplify application development and utilize hybrid data sources within a single view. ETL (Extract, Transform and Load) on the other hand, is helpful for complex transformational processes and nicely complements data virtualization which allows users to bypass many of the early rounds of data movement and transformation providing an integrated business-friendly view in near real time. Check out the recent Forrester report that found Cloud Pak for Data can reduce ETL requests by 25-65 percent.

Another area where Cloud Pak for Data helps eliminate data redundancy and storage expenses is in application testing. The platform now offers a new service called Virtual Data Pipeline (VPD) which has been shown to deliver up to 95 percent storage capacity savings due to capacity-efficient snapshots instead of full copies for functional Test and Development. By optimizing each copy of the production data through high level compression techniques it is able to dramatically minimize the required storage while still maintaining continuity between the compressed and optimized versions of the source data.

2. Consolidate Data and AI software and reduce tools spend

The adoption of cloud is driving consolidation and consistency across the board and as customers look to modernize their architectures, it’s imperative that they streamline disparate legacy offerings for an integrated future. This not only allows for significant cost savings in the short term but also enables rapid innovation while addressing common skills gap. Cloud Pak for Data provides an integrated Data and AI platform spanning the full analytics life-cycle, delivering all the capabilities an enterprise needs to Collect, Organize, Analyze data and Infuse AI into their business processes. With a vibrant ecosystem of proprietary, open source and 3rd party services, it enables organizations to consolidate and modernize legacy capabilities from disparate vendors while significantly reducing their IT spend on software maintenance as well as administering, upgrading and integrating those point solutions.

Reducing redundancy also helps focus your resources on strategic priorities while allowing manual tasks and integration to be addressed by the platform – A perfect example is Auto AI, a service on Cloud Pak for Data which allows AI models to be built in a matter of minutes without the expertise of a seasoned Data Scientist. This is critical in a world where Data Scientists are a rare commodity. Automating tasks also helps drive agility in the organization and ensures that skilled resources can focus on higher value problems.

3. Reduce infrastructure and maintenance costs with cloud native architecture

Cloud native architecture is a paradigm shift in how we develop and deliver software and is not just reserved for public clouds. Red Hat OpenShift helps realize these benefits anywhere through containerized services, container management and orchestration that can lower IT infrastructure and development costs by up to 38 percent per application. Building upon these benefits, Cloud Pak for Data is further optimized for enterprise deployments and helps reduce administration expenses with simplified provisioning and scaling, consolidated administration, automated IT operations, and seamless upgrades. By reducing infrastructure management efforts 65 – 85 percent the platform helps customers free up infrastructure and administration resources to focus on more complex problems.

The flexibility to deploy Cloud Pak for Data anywhere enables customers to avoid vendor-lock in while tapping into the infrastructure benefits of public clouds (or their own private cloud). Also, the availability of Cloud Pak for Data as a hyper-converged system provides additional benefits to customers looking for faster time to value, optimized local infrastructure and consolidated support across hardware and software. This is especially crucial given the sophistication of private cloud deployments for Do-It-Your-Own on-premise scenarios.

Finally, cloud native architectures ensure High Availability and seamless upgrades, which are significant for enterprises. Today, upgrades to traditional software can take anywhere from a few weeks to a few months, depending on the complexity costing significant resources, time and money – all of this can be avoided and more importantly realize immediate benefits of software updates through Cloud Pak for Data. The cost savings involved here across infrastructure, administration and software upgrades can in itself justify a business case to modernize to Cloud Pak for Data.

4. Automate governance & security while ensuring compliance

Most enterprise customers view governance and security as a cost of doing business: to ensure regulatory compliance and to avoid business and reputation risk from security breaches. However, Governance done well can deliver significant business value in the form of self service analytics. The key to governance and security is  automation which is exactly what we do with Cloud Pak for Data. By automating manual tedious tasks – data discovery, term assignment, identifying compliance risks and policy enforcement on all data assets (structured and unstructured), Cloud Pak for Data significantly reduces the cost of data governance and ensuring compliance. Today enterprises spend millions of dollars on third party consulting firms to handle governance and security but that’s only a temporary fix not a permanent solution. With Cloud Pak for Data, you can reduce these costs significantly while modernizing at the same time.

Another area of focus is privacy and data protection regulations which are growing and evolving around the world. The General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA) and Brazil’s General Data Protection Law (LGPD) are some of the largest privacy regulations to impact global organizations. There are 25+ states in the US with similar mandates requiring various levels of maturity. “InstaScan” is a new unstructured data management and privacy service in Cloud Pak for Data that automates scans across  Box, Google Drive, Microsoft OneDrive and SharePoint. It identifies and prioritizes hot spots & privacy violations for remediation within a matter of hours significantly reducing the manual effort needed for regulatory compliance.

Finally, COVID-19 will bring in big changes in how we live, learn, work and entertain; and in many cases accelerate the trends we’ve seen growing across industries. In particular this also applies to how Data, Analytics & AI workloads will be managed going forward. Enterprises taking the initiative and leveraging this opportunity to streamline, consolidate and transform their architecture will come out ahead both in sustaining the short term impact through immediate cost savings and in modernizing for an evolving and agile future. IBM is willing to co-invest resources to accelerate and help you with this journey. If you are interested and want to explore how Cloud Pak for Data can help you save money, please join us for our upcoming webinar or schedule a consultation with one of our experts.

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