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IBM Cloud Pak for Data

Score8.6 out of 10

28 Reviews and Ratings

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What is IBM Cloud Pak for Data?

IBM Cloud Pak for Data (formerly IBM Cloud Private for Data) provides data management, data governance, and automated data discovery and classification.

Categories & Use Cases

Reviews

What users are saying about IBM Cloud Pak for Data.
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Cloud Pak for Data with Netezza

Incentivized
Dana RafieeView profile
Director of Worldwide Strategic Consulting in Professional Services at Destiny Corporation (51-200 employees employees)

Use Cases and Deployment Scope

We advise many of our clients on the best ways to process ETL and Analytics, quickly, and efficiently. CP4D has been around for many years and we have implemented this for many organizations. It solves most bottlenecks clients have for processing in a very cost effective and reliable environment. Clients can also process jobs within seconds where it would previously take days. This offers a platform to organizations allowing them to change their business models. For example, a large financial institution in Canada would normally score their customers in 45 hours. With CP4D with Netezza, the same scoring job completes in 15 seconds. Now customers can be scored daily. This same story can be seen at hundreds of other clients we support. There is nothing else like it on the market at such a competitive price on premise or in the cloud.

Pros

  • the fastest execution of queries
  • business critical support and redundancy in design for almost 100% uptime
  • ties in with many other IBM offerings such as Watson
  • support at IBM is unbeatable with experts available before and after the sale to assist clients

Cons

  • This offering is currently available on prem, in Azure, and soon in AWS. GCP availability will be in the future as there is demand in the marketplace
  • The on premise offering starts with a Base + 0 model, which is a significant appliance. There are no 'mini' offerings as there were in the past.
  • At Destiny, we work closely with IBM to help our clients perform budgetary planning.

Most Important Features

  • Ease of use
  • Fast Analytics
  • Easy to train staff how to use

Return on Investment

  • Incredible ROI for clients
  • Simple for users to understand and use
  • No downtime for analytics processing

Alternatives Considered

VMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ and Tanzu SQL)

Other Software Used

OpenManage Integration for VMware vCenter, JMP Statistical Discovery Software from SAS

You know what you know about "IBM Cloud Pak for Data"

Incentivized
Nitesh SinghView profile
SRE2 in Customer Service at Nutanix (1001-5000 employees employees)

Use Cases and Deployment Scope

We use it to connect it with our product for integration with cloud and it helps to enables all of your data users to collaborate from a single, unified interface that supports many services that are designed to work together. we give the end user recommendation is they want to store the data in cloud.

Pros

  • all-in-one cloud-native Data and AI platform in single platform
  • it enables us to collect, organize and analyze data
  • it provides unprecedented simplicity and agility, within a preconfigured and governed environment.

Cons

  • Cannot save changes to some secrets in the internal vault
  • Sign-in issues on environments where IAM is enabled
  • The Enforce quotas option is disabled

Most Important Features

  • Simplify and automate access to data, across multi-cloud and on-premises data sources, without moving data.
  • Universally safeguard the use of all data, regardless of source.
  • Provide business users with a self-service experience for finding and using data.

Return on Investment

  • can improve readiness for cloud migration, improve licensing flexibility with IBM, and reduce both hardware purchases and infrastructure management efforts.
  • reduces the expenses of internal resources.
  • should improve efficiencies, reduce risks, and increase performance

Alternatives Considered

Nutanix Cloud Clusters (NC2)

Other Software Used

IBM InfoSphere Data Replication, Nutanix Cloud Infrastructure, Amazon S3 (Simple Storage Service)

All-in-one, Real-time Data analytics, phenomenal user experience, Top-notch AI hybrid cloud platform.

Incentivized
Khati DishaView profile
Information Technology Project Manager in Information Technology at Fiserv (10,001+ employees employees)

Use Cases and Deployment Scope

IBM Cloud Pak for Data is a powerful cloud-native AI all-in-one easy to use solution that enables us to put data to work quickly and effectively.
This tool also enables us to approach analytics our way, with code, low-code and no code options that allows us to collaborate on one platform. Easy to transform structured and unstructured data into analytics insights. Build and test models with best-in-class AI and analytics. The support team is generally the most proactive and supportive 24/7.

Pros

  • Increases our impact by combining BI skills with advanced analytics and machine learning in an easy to use visual interface.
  • Visualization and reporting.
  • Rapidly provides business -ready data to all users equally.
  • Manage data spread across distributed stores and clouds.

Cons

  • Price is something that affects most the small business enterprises. There should affordable pricing plans for the small organization.
  • It's takes some time to learn and grasp everything.

Most Important Features

  • End-to-end AI lifecycle.
  • Data governance and privacy.
  • Visualization and reporting.

Return on Investment

  • Saves lots of time by predicting outcomes faster using a platform built with data fabric architecture.
  • Easy to collect, organize and analyze data no matter where it is.
  • Manual catalog is eliminated to save costs.
  • Drive responsible, transparent and explainable AI workflow to operationalize AI and mitigate risks and regulatory compliance.

Alternatives Considered

Azure Databricks and Cloudera Data Platform

Perfect for hybrid and multi-cloud environments.

Incentivized
Laurie Julie BlakeView profile
System Engineer in Engineering at Mr. Cooper (5001-10,000 employees employees)

Use Cases and Deployment Scope

IBM Cloud Pak for Data is driving business productivity by reducing the time spent reading and analyzing data, we always use this tool in all departments that need to gather relevant information in the cloud from a single centralized platform for better reporting of data, it is possible to analyze data from many sources in a short period of time. Data virtualization is very simple, migrations, readings, analysis, data management from other sources are performed without problems of requirements, we have a team of experts in IBM Cloud Pak for Data to maintain security and correct data management .

Pros

  • Robust data virtualization.
  • Robust centralized data analytics.
  • Improves data reliability.
  • Compatible with hybrid and multi-cloud environments.

Cons

  • Setting up hybrid and multi-cloud environments is a long job for my entire team.
  • We have more reliable results in the company with the features of this cloud-based software.

Most Important Features

  • Configuration with hybrid and multicloud environments.
  • Robust platform capable of working with multiple data sources.
  • Automated data analysis.

Return on Investment

  • Better performance in analysis and data collection from multiple sources.
  • Our productivity in the company is growing thanks to data analysis.
  • Robust hybrid and multi-cloud access system.

DATA MANAGEMENT IN DIFFERENT ENVIRONMENTS WITHOUT THE COMPLEXITY OF BEFORE.

Incentivized
Kenzie Cranston LeeView profile
Technical Support Engineer in Engineering at GE (10,001+ employees employees)

Use Cases and Deployment Scope

This cloud-based tool is excellent for visualizing and managing all data across networks, also fulfilling fuzzy data storage, making it less complex and completely improving productivity in the organization; so everything will be managed in multiple environments without any problem. That's why since IBM Cloud Pak for Data has been implemented everything is better organized and managed across all departments with no hassle.

Pros

  • Artificial intelligence that solves everything automatically.
  • We can store in many clouds all the desired data.
  • we are much more productive.
  • Excellent customer service system, willing to help always.

Cons

  • There is no problem with this software, it offers us many services that have helped us to grow as a business and therefore economically we would implement it again.

Most Important Features

  • External data connection management.
  • MLOps and AI.
  • Distributed data processing.

Return on Investment

  • Simple data processing and no migrations.
  • Advanced data privacy control performance.
  • Access to disparate data sources.

Other Software Used

Google Analytics, IBM Data and Analytics Consulting Services

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