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Talend Open Studio and IBM Cloud Pak for Data compete in the data integration and data management category. IBM Cloud Pak for Data seems to have the upper hand with its advanced AI capabilities and data virtualization, appealing more to enterprises.
Features: Talend Open Studio offers user-friendly data integration with numerous pre-built connectors, customizable ETL jobs, and a simple interface, making it ideal for smaller businesses. IBM Cloud Pak for Data includes advanced data virtualization, AI capabilities via Watson Studio, and containerization for flexible cloud deployment, catering to larger enterprises.
Room for Improvement: Talend Open Studio needs better installation configuration, comprehensive documentation, more training resources, and improved technical support. IBM Cloud Pak for Data could benefit from streamlined installation, enhanced integration capabilities with additional connectors, and a simplified architecture.
Ease of Deployment and Customer Service: Talend Open Studio supports versatile on-premises deployments with community-driven technical support, which may be limited. IBM Cloud Pak for Data offers flexible deployment options in hybrid and public clouds, but its complexity can be challenging for smaller setups. IBM provides professional support but could improve its responsiveness.
Pricing and ROI: Talend Open Studio is cost-effective with its open-source version, suitable for small to medium-sized enterprises, though it can be expensive at an enterprise level. IBM Cloud Pak for Data is more expensive, fitting for larger corporations. It offers favorable ROI for extensive data integration needs but may not justify costs for smaller businesses.
We have been able to drive responsible, transparent, and explainable AI workflow to operationalize AI and mitigate risk and regulatory compliance easily.
Cloud Pak is a complicated system, and it's often difficult to find the right resource in IBM to help with specific issues.
Customer support should be more responsive and reach and respond on time.
IBM support is very supportive, and I would rate them an eight out of ten based on our long relationship with them.
I have not noticed any downtime or lagging, especially when dealing with large data, so it is relatively very scalable.
Setting up the hybrid and multi-cloud environments is a long job and it takes time.
I would love Cloud Pak to come with a demo database that illustrates the different components of data management in a logical way, so I can see the whole picture instead of just the area I'm specializing in.
I do not know if Cognos has all the features that users are looking for since we provide it as our standard and do not maintain infrastructure for other tools.
If we could have round-the-clock support, we would be able to resolve many issues which we encounter during the development part.
The setup cost is very expensive.
Regarding my experience with pricing, setup cost, and licensing, for a small organization, the price might be relatively high, but for huge enterprises such as ours, the price is relatively affordable.
We have been able to save approximately 80 percent of our time. We are not doing data analysis manually, so this relieves our data department of dealing with data.
The benefits of choosing IBM Cognos, in addition to saving on cost, include having institutional knowledge about maintaining this infrastructure and enough people who have developed on Cognos in the past, which creates comfort in its use.
From there, I can work my way into a more granular level, applying all of that information on top of my actual data to understand what my data looks like, where it came from, and where it went wrong, managing it throughout the cycle.
The biggest benefit of Talend Open Studio for my customers is that it is a one-stop shop for orchestrating ETL and governance.


| Company Size | Count |
|---|---|
| Small Business | 7 |
| Large Enterprise | 12 |
| Company Size | Count |
|---|---|
| Small Business | 22 |
| Midsize Enterprise | 13 |
| Large Enterprise | 18 |
IBM Cloud Pak® for Data is a fully-integrated data and AI platform that modernizes how businesses collect, organize and analyze data to infuse AI throughout their organizations. Cloud-native by design, the platform unifies market-leading services spanning the entire analytics lifecycle. From data management, DataOps, governance, business analytics and automated AI, IBM Cloud Pak for Data helps eliminate the need for costly, and often competing, point solutions while providing the information architecture you need to implement AI successfully.
Building on the streamlined hybrid-cloud foundation of Red Hat® OpenShift®, IBM Cloud Pak for Data takes advantage of the underlying resource and infrastructure optimization and management. The solution fully supports multicloud environments such as Amazon Web Services (AWS), Azure, Google Cloud, IBM Cloud™ and private cloud deployments. Find out how IBM Cloud Pak for Data can lower your total cost of ownership and accelerate innovation.
Talend Open Studio [EOL] is a user-friendly data integration tool that offers comprehensive ETL capabilities with extensive connector options. Its open-source nature and integration with a range of data sources make it a versatile choice for data integration tasks.
Talend Open Studio [EOL] provides flexibility and scalability for data integration by supporting relational and NoSQL databases. It is Java-based, allowing customization and data quality features, backed by community support. Challenges include limitations in scheduling and monitoring, technical support, resource consumption, and version control. The complex installation process and need for better documentation and easier use for beginners are notable issues. Despite these, it remains a strong option for connecting legacy applications, building data warehouses, and automating processes with data migration, synchronization, transformation, and loading from ERP systems, APIs, and databases like PostgreSQL, Oracle, and SQL Server.
What are the standout features of Talend Open Studio [EOL]?Talend Open Studio [EOL] is implemented across sectors like telecom, finance, and real estate for managing data flows, constructing information hubs, and enhancing business intelligence. Companies utilize it for data migration, synchronization, and transformation, ensuring efficient data integration in diverse applications.
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