Just another data platform or Breakthrough? IBM Cloud Pak For Data

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What Questions You Should Ask as a Digital Ready Enterprise

  1. Have we defined the Enterprise Innovation Goals?
  2. Do we need collaboration among departments and teams?
  3. Does it also require working on multiple applications at the same time?
  4. Do we need to manage teams with different roles and security parameters?
  5. Does it require open source software and libraries?
  6. Does it need to scale to intelligent and automation use cases?
  7. How would multiple solutions talk to each other within same policies and governance rules?
  8. How the platforms and applications manage the data security while accessing at different locations?

IBM Cloud Pak for Data

The highly innovative platform introduced by IBM that is built on Red Hat® OpenShift® Container Platform. Cloud Pak for Data is a great platform for organizations starting their secured journey for Data, Apps & customer centric digital products.

It also comes with Industry accelerators; in case you are at an early stage for your innovation and AI projects.

You may deploy CP4D on any cloud such as IBM, Private, Google or Microsoft. This speed up the implementation of your ongoing projects and innovate with at scale by using market leading Watson AI capabilities.

There are various services included from IBM and third-party vendors. The catalog services include: AI, Analytics, Dashboards, Data governance, Data sources, Developer tools, Industry solutions and storage.

Source: www.ibm.com/cloud-pak/data

The Industry Accelerators

IBM provides set of artifacts to help you started with common business challenges in the form of Industry accelerators.

The accelerator includes a structured set of business terms. The glossaries provide the information architecture that you need to effectively analyze your data. Some accelerators include sample projects with necessary data services running for you to start your analysis and gather results.

The accelerators also include sample data science assets that you can use to accelerate your analysis. The assets include:

  • Sample data sets and schemas
  • Jupyter notebooks that you can use to cleanse and prepare the data, run machine learning algorithms, and score the resulting models
  • Sample dashboards to display the results interactively
  • API endpoints that you can call from other applications

Some Accelerators are discussed below:

1- Contact Centre Optimization

This accelerator includes more than 95 business terms and enables you to effectively analyze the productivity of your contact centre. The data scientists can use the data associated with this glossary to discover patterns related to:

Agent productivity and Contact centre usage

2- Credit Card Fraud

The accelerator includes more than 135 banking business terms and enables any suspicious activities.

3- Customer 360 Degree View

This accelerator includes more than 70 business terms and enables you to gain insight into facets such as:

Customer Segmentation, Credit risk, Loyalty programs, Social media sentiment

4- Customer Life Event Prediction

Plan with your clients for their financial programs by using more than 100 business terms to start with and with streaming data, know when to target your end user with new offerings.

5- Streaming Analytics for Customer Life Event Prediction

Extend the Customer Life Event Prediction accelerator with streaming data.

Learn More or Register for free trial:


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