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Artificial intelligence (AI) is no longer the next big thing. It’s a present reality of IT, and it’s only becoming more important.
In a recent study by MIT Sloan Management Review, 91 percent of business leaders said they expected AI to deliver new business growth by 2023. The study also showed that firms that had invested in AI were already pulling ahead.
Despite the clear opportunity that AI presents, many organizations are struggling to wrangle the data required for AI applications.
To help enterprises gain more of a self-service option for AI, IBM built IBM Cloud Private Experiences, a guided, no-download-needed journey through collecting, organizing and analyzing data with IBM Cloud Private and IBM Cloud Private for Data. Users can build cloud-native, AI-powered apps over the course of seven days of access to a hosted environment.
To help explain the power of this tool, we’ll walk through each of the experience’s paths using an industry example of machine learning applications for banking.
Easily collect data sources
Users can connect to existing databases for quick and easy access to data no matter where it lives. For example, in the banking industry, enterprises can use the integrated connectors to connect to the bank’s database, then discover and select the data needed to build a mortgage prediction model.
IBM Cloud Private Experiences can help turn data into trusted data. Automated discovery can help users import, analyze and classify data. They can define business terms so that data is consistent, as well as apply rules and policies to make data compliant with regulations. They can transform the data to make it useful, and, most importantly, make the data easy for users to find by publishing it to the enterprise data catalog.
Analyze and build
Quickly analyze relevant data and build cloud-native apps. For example, again within the banking industry, users can build, deploy, and publish a machine learning model to predict whether clients will repay their mortgage or default on it. The model can be further trained with different classification techniques and insights can be easily seen through visual dashboards.
Enterprises can start from any of these points to easily build custom AI-powered applications.
Choose your path
Test the tool by visiting the IBM Cloud Private Experiences website and learn more from the introductory video.
Dive deeper by reading the next IBM Cloud Private Experiences blog post. Learn how to build a Helm chart, manage the deployment and deploy your cloud-native app. Plus, see how companies can automate a mortgage application process by building a machine learning model that can accurately predict the likelihood of any given client defaulting on their mortgage.