This is what IBM Cloud Pak for Data can do, and companies can reap these benefits and added value quickly, relatively easily, and flexibly.
Data-based business decisions rather than gut feelings: that has been companies’ recipe for success in the last few years. Data-driven companies that rely on business analytics are taking advantage of market opportunities faster, they are more successful on the market, and they are better than their competitors in many ways. This is not just a guess, but a verified, hard fact.
IBM interviewed 13,484 C-Class managers from 20 industries and 98 countries for its Global C-suite Study (20th edition). The result: 69% of companies that rapidly adapt and deploy digital technologies such as business intelligence and business analytics achieved excellent revenue growth, well above that of their competitors. In fact, with the help of data analytics technologies, 71% of these companies’ profitability was significantly higher than average.
IBM’s Cloud Pak for Data addresses these business challenges and needs. IBM Cloud Pak for Data is an integrated, secure, highly scalable platform for implementing an information architecture for data and artificial intelligence in any cloud. The Cloud Pak brings together the technologies and solutions relevant to data analysis that IBM has developed. IBM Cloud Pak for Data runs under a partially automated architecture, including Watson Assistant, Watson Discover, Cognos Analytics, Planning Analytics/TM1, DB2, DWH, and Red Hat OpenShift. It can be used in any operating/procurement model, from on-premise to managed to completely “Software-as-a-Service” from the public cloud.
Behind the scenes
What makes Cloud Pak for Data special: IBM has containerized all software services with the help of the Kubernetes OpenShift orchestration platform, which adds essential business functions to Kubernetes. In addition, there is a virtualization layer that combines all distributed data sources into a unified, consolidated user view. This is a huge advantage, because no time at all is required to copy or process data, as with other common solutions. For example, business users can deploy a single SQL query statement to search Oracle and DB2 databases, Hadoop clusters, SQL servers, NoSQL data stores, and Excel spreadsheets as if they were a single system.
Forrester has taken a closer look at the IBM Cloud Pak for Data. This research firm concluded that the IBM AI analytics platform reduces the ETL queries needed to build an enterprise data warehouse by 25 to 64%. The effort to maintain the entire infrastructure required to run analytics applications is reduced by 65 to 85% with the Cloud Pak for Data.
Forrester estimates the average return on investment, based on a three-year period, to be between 86 and 158%. Forrester used a model organization with annual sales of $2 billion and 8000 employees. (Source: The Total Economic Impact of IBM Cloud Pak for Data).
IBM Cloud Pak for Data comes with many pre-configured services for practical use, including AI, analytics, dashboards, data governance, industry solutions, data sources, and developer tools. For a detailed overview of all services, click here. Here is a selection of proven, particularly exciting application scenarios with high added value.
Use case: Data warehousing & data transformation
A rapidly growing company has acquired several business units and wants to integrate the new partners into a unified IT architecture as quickly and efficiently as possible. With IBM’s data virtualization layer, it is possible to consolidate many local data pots, systems, and reports in different locations in high-performance fashion without having to migrate the data sources.
However, it is also possible to construct a classic enterprise data warehouse without any problems. The IBM Cloud Pak for Data accelerates and reduces the cost of the necessary extract, transform, load (ETL) processes. Data analysis and visualization of the results are then performed by specialist users with IBM Cognos Analytics as an optional component of the Cloud Pak for Data.
Use case: For specialist users – the AI Self Service “AutoAI”
A company wants to use self-learning artificial intelligence to improve its forecasting and make its decisions on a more robust, data-based basis. However, the company has no experts such as data scientists who are familiar with the new technologies.
With AutoAI AI self-service, even specialist users without specific knowledge of AI validate whether and if so, which AI models are useful in their particular application and will lead to success. Specialist users select the relevant datasets, AutoAI independently tests the relevant AI models and provides a strengths-weaknesses analysis at the end of the process. Creation takes only a few minutes. The result can be taken directly into production and integrated into existing or new business processes.
Use case: Moving quickly together from zero to one hundred
A wholesaler wants to unify the work of its data analysts and integrate it into its business processes. With IBM Cloud Pak for Data, different roles such as data scientists, business analysts, data engineers, controllers, business users, and app developers work together transparently on the same platform. The end-to-end integration of processes and roles enables faster and higher penetration of AI across the enterprise.
Use case: Make the most of scarce resources
Scarce resources that need to be optimized for availability, cost, or benefit are available across industries in any company, whether it be personnel, materials, or capital. IBM Cloud Pak for Data optimizes the use of resources, quickly reduces costs, and reduces doubled assignments and penalties.
Would you like to see for yourself?
Click here to go to the free trial account with preconfigured templates and use cases (registration required)
White paper: IBM Cloud Pak for Data
Smarter, better, more successful: Read this white paper to learn about the benefits of IBM’s AI analytics cloud.