IBM Advances IBM Cloud Private for Data Further with Modularity, Premium Add-Ons, and More

Dinesh Nirmal
IBM Data Science in Practice
4 min readNov 27, 2018

Data is the new natural resource — abundant, often untamed, and fueling Artificial Intelligence (AI). It has the potential not only to transform business, but to enable the creation of new business models.

But where and how are you expected to begin your data journey? These are two of the most common questions we get asked. For us, it has everything to do with making things like data science and machine learning capabilities, accessible and easy to use across platforms — providing solutions that handle the analytics where the data resides, rather than bringing the data to the analytics.

By taking this approach, IBM has been a leader in helping clients around the globe more easily collect, organize, and analyze their growing data volumes, all with the end goal of ascending the AI Ladder. To be clear, that’s not as easy as it sounds. For example, according to a report from MIT Sloan, Reshaping Business with Artificial Intelligence, an estimated 85% of 3,000 business leaders surveyed believed artificial intelligence (AI) would enable competitive advantage, however, only about 20% have done anything about it. For many organizations, the task of understanding, organizing, and managing their data at the enterprise level was too complex.

So earlier this year we set out to change all that and make it easier for enterprises to gain control of their data, to make their data simple, and then to put that data to work to unearth insights into their organizations. We launched IBM Cloud Private for Data, the first true data platform of its kind that integrates data science, data engineering, and app building under one containerized roof that can be run on premises or across clouds.

We’ve been busy adding to the platform ever since. Since launch we’ve added support for MongoDB Enterprise and EDB Postgres; we’ve integrated IBM Data Risk Manager; and we’ve announced support for Red Hat Openshift, to name a few. This week we’re keeping the momentum going, announcing a variety of new updates, from premium add-on services and modular install options, to the availability of the first-of-a-kind Data Virtualization technology.

With these updates, the design criterion was to help organizations modernize their environments even further to take advantage of cloud benefits — flexibility, agility, scalability, cost-efficiency — while keeping their data where it is. Leveraging multi-cloud elasticity and the portability of a microservices-based containerized architecture lets enterprises place their data and process where it most benefits the business.

Here’s how the new capabilities line up:

Premium Add-On Services

We continue to enrich IBM Cloud Private for Data’s service catalog with premium add-on services:

  • An advanced data science add-on featuring IBM SPSS Modeler, IBM Watson Explorer, and IBM Decision Optimization to help organizations turn data into game-changing insights and actions with powerful ML and data science technologies
  • Key databases— Mongo DB and Db2 on Cloud
  • IBM AI OpenScale will soon be available as a single convenient package with IBM Cloud Private for Data, helping businesses operate and automate AI at scale, with trust and transparency capabilities to eliminate bias and explain outcomes

Data Virtualization

IBM Cloud Private for Data’s data virtualization (announced in September) can help organizations leverage distributed data at the source, eliminating the need to move or centralize their data. Some of the key highlights are:

  • Query anything, anywhere — across data silos (heterogeneous data assets)
  • Help reduce operational costs with distributed parallel processing (vs centralized processing) — free of data movement, ETL, duplication, etc.
  • Auto-discovery of source and metadata, for ease of viewing information across your organization
  • Self-discovering, self-organizing cluster
  • Unify disparate data assets with simple automation, providing seamless access to data as one virtualized source
  • Governance, security, and scalability built in

In essence the service appears as a single Db2 database to all applications.

IBM Cloud Private for Data update

Other Capabilities in this Release

  • FISMA Compliance — FIPS Level 1
  • Modular Installation — Reduced footprint for base installer by almost 50%. Customers can deploy add-ons as optional features.
  • Support for Microsoft Azure by end of year — Adding to existing IBM Cloud Private, Red Hat OpenShift, and OpenStack and Amazon Web Services support

Next steps

As organizations take this journey with us, these new capabilities of IBM Cloud Private for Data can help further modernize and simplify their data estates for multicloud, leverage the best of the open source ecosystem, and infuse their applications and business processes with data science and AI capabilities. We remain committed to helping our clients unlock the value of their data in innovative smarter ways for better, more timely business outcomes. IBM Cloud Private for Data can be that place to start.

For more information on the latest updates for IBM Cloud Private for Data click here.

Experience the power of IBM Cloud Private for Data today.

Dinesh Nirmal,
VP, IBM Analytics Development

Follow me on twitter @DineshKNirmal

  1. “Twenty percent of the world’s data is searchable. Anybody can get to that 20,” Rometty told “Mad Money” host Jim Cramer on Tuesday. “But 80 percent of the world’s data, which is where I think the real gold is, whether it’s decades of underwriting, pricing, customer experience, risk in loans — that is all with our clients. You don’t want to share it. That is gold.” https://www.cnbc.com/2017/06/20/ibm-ceo-says-80-percent-of-the-worlds-data-is-where-the-real-gold-is.html

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Dinesh Nirmal
IBM Data Science in Practice

Vice President — Analytics Development, Site Executive IBM Silicon Valley Lab. The opinions expressed are my own and don’t necessarily represent those of IBM.