Cloudera DataFlow is fully compatible with Cloudera's ecosystem and offers high efficiency through native connectors for various ecosystems. However, the learning curve is high, and there is a shortage of skilled professionals. My overall rating for Cloudera DataFlow is eight out of ten.
The tool ensures data preparation and data delivery for ML products. We would recommend Cloudera DataFlow to customers with strong requirements for data security and governance and those dealing with large volumes of data or a high frequency of events per day. Additionally, it's suitable for customers with complex infrastructures that require interaction among numerous in-house services. Overall, I rate the solution a nine out of ten.
I don't find anything valuable in DataFlow. It's an outdated legacy product that doesn't meet the needs of modern data analysts and scientists and their requirement for agility for workers' teams and support for data ops processes versus software development/dev ops processes. If you're a traditional systems software development project needing a Cloudera-type capability, DataFlow is good. But it's no use if you want to empower a federated capability across your organization with data analytics and data-science themes. I would give DataFlow a rating of five out of ten.
Manager at a tech services company with 201-500 employees
Real User
May 23, 2021
If you're interested in using this solution, first perform some return on investment analysis to make sure that this platform is mature enough for your requirements. Compare it with some other solutions first and determine which solution is best. It really comes down to your company's needs and what features you require. Overall, on a scale from one to ten, I would give Cloudera DataFlow a rating of eight.
Streaming Analytics allows businesses to process data in real-time for immediate insights and decision-making. This technology is crucial for industries that rely on timely data processing, such as finance, telecommunications, and e-commerce.Streaming Analytics processes continuous data flows, enabling businesses to react promptly. It helps detect trends, anomalies, and patterns for more informed decisions. This technology enhances data visibility and operational efficiency by enabling...
Cloudera DataFlow is fully compatible with Cloudera's ecosystem and offers high efficiency through native connectors for various ecosystems. However, the learning curve is high, and there is a shortage of skilled professionals. My overall rating for Cloudera DataFlow is eight out of ten.
The tool ensures data preparation and data delivery for ML products. We would recommend Cloudera DataFlow to customers with strong requirements for data security and governance and those dealing with large volumes of data or a high frequency of events per day. Additionally, it's suitable for customers with complex infrastructures that require interaction among numerous in-house services. Overall, I rate the solution a nine out of ten.
Overall, I rate the solution a seven out of ten.
I don't find anything valuable in DataFlow. It's an outdated legacy product that doesn't meet the needs of modern data analysts and scientists and their requirement for agility for workers' teams and support for data ops processes versus software development/dev ops processes. If you're a traditional systems software development project needing a Cloudera-type capability, DataFlow is good. But it's no use if you want to empower a federated capability across your organization with data analytics and data-science themes. I would give DataFlow a rating of five out of ten.
If you're interested in using this solution, first perform some return on investment analysis to make sure that this platform is mature enough for your requirements. Compare it with some other solutions first and determine which solution is best. It really comes down to your company's needs and what features you require. Overall, on a scale from one to ten, I would give Cloudera DataFlow a rating of eight.