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IBM Global Chief Data Office modernizes and gains insights
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For most companies, data is dispersed across departments. As a result, data-driven business insights aren’t widely available. This leads to billions of dollars of inefficiencies, missed growth opportunities and regulatory exposure.

Until several years ago, IBM® faced similar challenges. Without a practical way to discover insights from its data, IBM needed a solution. At the time, there was no commercially available platform to organize disparate data for analysis. So the IBM Global Chief Data Office (GCDO) developed the Cognitive Enterprise Data Platform (CEDP).

The CEDP is a common, unified data platform that is the central source of governed data. The CEDP serves as a data hub. IBM solutions integrate with the CEDP, providing tools and technology for users to load, transform and analyze data.

The platform quickly improved business outcomes for GCDO. In about 18 months, the office generated USD 1.3 billion in business benefits and a 10x ROI from data and AI-based transformation initiatives.

While these results are impressive, GCDO wanted to improve its data intelligence capabilities further.

GCDO had two choices about how to continue modernizing its data. It could spend time, effort and other resources building and updating its platform. Or it could turn to a commercially available platform designed for this purpose.

It chose the latter.

Faster delivery



IBM Cloud Pak® for Data delivers 9000 AI models, twice as fast

Cost savings


Reduced energy reporting software costs by 30% by replacing multiple tools with a single, automated platform

IBM Cloud Pak for Data has advanced CEDP. For example, Watson Studio enables our 600 data scientists and professionals to develop 9,000 AI models at least twice as quickly. We expect similar acceleration and efficiency factors for data ingestion, classification and governance. Inderpal Bhandari Global Chief Data Officer IBM
Flexible data platform modernization

IBM Cloud Pak for Data didn’t exist when GCDO built its CEDP. IBM Data and AI, the business unit that develops IBM Cloud Pak for Data, created it to help companies modernize how they collect, organize and analyze data to infuse AI. IBM Cloud Pak for Data serves as a unified, hybrid-cloud data and AI platform.

The IBM Cloud Pak for Data platform includes a suite of services and various extensions that can be accessed as needed. This makes the platform less expensive for customers, who no longer need numerous, expensive standalone products. It also makes the platform flexible for users: there is no prescriptive model for where to start.

For GCDO, this flexibility to plan and stage its transitions was essential. By running existing systems in parallel with IBM Cloud Pak for Data until they’re ready to switch to the new platform, GCDO can make transitions without disrupting existing processes.

GCDO first started using the AI suite of services within IBM Cloud Pak for Data, including IBM Watson® Studio. IBM Watson Studio runs on premises and in the cloud, analyzing data with the IBM Db2® Big SQL solution.

IBM Watson Studio allows GCDO’s analysts and data scientists to perform analysis without standing up custom environments, which is how they operated in the past. This feature makes IBM Watson Studio one of GCDO’s most used services within IBM Cloud Pak for Data.

Global Leader for Client 360, IBM Global Chief Data Office

As of November 2020, GCDO had 600 registered users accessing IBM Watson Studio. On an average day, the service has up to 300 active runtimes. The GCDO anticipates this user base will increase as word spreads.

“IBM Cloud Pak for Data is instrumental in advancing our CEDP,” says Inderpal Bhandari, Global Chief Data Officer at IBM. “For example, Watson Studio enables our 600 data scientists and professionals to develop 9,000 AI models at least twice as quickly.”

GCDO also uses IBM Watson Studio technology to enable parts of its IBM Recommendation & Insights System (IRIS). This sales analytics platform suggests offerings to propose to specific clients. And it suggests clients to approach with given offerings.GCDO and the IBM Chief Analytics Office (CAO) collaborate closely on this impactful solution.

Recommendations and insights come from machine learning models fed by internal and external data sources. IBM Watson Studio allows data scientists to develop and test new AI models rapidly. With more speed comes more modeling experiments and opportunities to leverage new data sets and combinations of data.

This increased model development velocity leads directly to significantly improved models for production. Since 2017, IRIS has increased the company’s sales pipeline opportunities by over USD 5 billion, all while offering significant efficiencies to sellers.

GCDO uses other IBM Cloud Pak for Data toolsets in its Client360 solution. Client360 unifies internal and external data and performs advanced AI analysis. The analysis gives IBM a holistic view of its clients, which lets sellers identify opportunities and design effective sales strategies.

Client360 uses nearly half of the IBM Cloud Pak for Data platform capabilities. In addition to IBM Watson Studio, Client360 uses the IBM DataStage®IBM Db2 WarehouseIBM watsonx Assistant and IBM Watson Natural Language Understanding solutions. These tools provide a range of ingestion, governance, data science and natural language user interface services.

The solution operates at scale, serving 30,000 users in 2020. It’s fast, too, responding to over 550,000 API calls with sub-second response times.

“Using IBM Cloud Pak for Data, GCDO rapidly migrated data to the public cloud and performed AI analytics,” says Peter Herr, Global Leader for Client 360 at GCDO. “We delivered results in half the time it would’ve taken without the tooling. And we delighted our users all the more quickly.”

Using IBM Cloud Pak for Data, GCDO rapidly migrated data to the public cloud and performed AI analytics. We delivered results in half the time it would’ve taken without the tooling. And we delighted our users all the more quickly. Peter Herr Global Leader for Client 360 IBM Global Chief Data Office
Future data platform modernization

It doesn’t end there.

In its ongoing modernization of its data platform, GCDO will follow a similar process it used with IBM Watson Studio to improve data ingestion and data governance. “We expect similar acceleration and efficiency factors for data ingestion, classification and governance with IBM Cloud Pak for Data,” says Bhandari.

For data ingestion, GCDO will continue transitioning into DataStage. For data governance, it will transition to IBM Watson Knowledge Catalog, another service accessible on the IBM Cloud Pak for Data platform.

GCDO is also looking across the end-to-end processes within its machine learning operations and data operations divisions to modernize them with IBM Cloud Pak for Data services. Many of CEDP’s other processes are also possible candidates for modernization.

And with each new transition GCDO makes, it helps the platform get better for everyone. “In GCDO, we partner with the IBM Cloud Pak for Data team by deploying their solutions on demanding enterprise-scale use cases,” says Caitlin Halferty, GCDO Director of AI Accelerator. “We provide detailed feedback that informs the product roadmap and share insights with our clients to accelerate their own adoption of IBM Cloud Pak for Data.”

GCDO has been digitally transforming its business using its data scientists, AI and machine learning tools to reinvent, innovate, and improve its business intelligence. Now with IBM Cloud Pak for Data, its opportunities for new insights and efficiencies are endless.

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About IBM Global Chief Data Office

The IBM GCDO develops data strategies and platforms that include governance and management systems, deep data and analytics partnerships. The strategy transforms business data into business value. These platforms become the central data source for business analytics across the enterprise and for developing and scaling talent. Together these innovative capabilities use analytic insights to enable growth and productivity.

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