If you want to use Revvity Signals Notebook for the first time, my advice depends on your purpose. If you need to create templates for scientists to conduct and share experiments and reference others' work, you can definitely use this product. However, if you require complex workflows, data transformations, or integration with your data systems for advanced analytics, Revvity doesn't offer a fully stable product for these needs yet. For such cases, you would need your developers to use Revvity's REST API to expose data to your data lake, which can be costly and resource-intensive. You'll need to evaluate the additional costs and resources required beyond Revvity's product. If you're a small user group needing basic experimentation features, Revvity Signals Notebook is suitable. However, consider the additional value and cost before proceeding for comprehensive use with complex workflows and data integration. From an end user's perspective, Revvity Signals Notebook is easy to learn. It's tricky for a configuration engineer but not overly complicated. With skilled resources, the learning curve is around three to six months. Overall, it's not more challenging than other SaaS products, making it reasonably easy to use. I would rate the solution a six out of ten. The reason is that their focus seems to be on just one set of products, neglecting other products. Even though big pharma clients have been consistently pushing and giving them ideas on improving, they don't seem to have enough capacity to address those ideas. Clients are eager for improvements, but Revvity needs to take their feedback seriously and address the issues quickly. They are on a good path but need to put in more effort. Our client has been using their products for more than two years, and if the environment isn't stabilized within that time, they need to rethink their approach. They need to be more dedicated to addressing client needs.
Data Preparation Tools offer streamlined methods for cleaning, transforming, and organizing raw data into usable formats for analysis and reporting.
Data Preparation Tools are key in converting large datasets from disparate sources into a unified format, ensuring data's quality and compatibility for downstream analytics. They incorporate functionalities that automate repetitive tasks, identify data discrepancies, and facilitate data enrichment, thereby improving efficiency and...
If you want to use Revvity Signals Notebook for the first time, my advice depends on your purpose. If you need to create templates for scientists to conduct and share experiments and reference others' work, you can definitely use this product. However, if you require complex workflows, data transformations, or integration with your data systems for advanced analytics, Revvity doesn't offer a fully stable product for these needs yet. For such cases, you would need your developers to use Revvity's REST API to expose data to your data lake, which can be costly and resource-intensive. You'll need to evaluate the additional costs and resources required beyond Revvity's product. If you're a small user group needing basic experimentation features, Revvity Signals Notebook is suitable. However, consider the additional value and cost before proceeding for comprehensive use with complex workflows and data integration. From an end user's perspective, Revvity Signals Notebook is easy to learn. It's tricky for a configuration engineer but not overly complicated. With skilled resources, the learning curve is around three to six months. Overall, it's not more challenging than other SaaS products, making it reasonably easy to use. I would rate the solution a six out of ten. The reason is that their focus seems to be on just one set of products, neglecting other products. Even though big pharma clients have been consistently pushing and giving them ideas on improving, they don't seem to have enough capacity to address those ideas. Clients are eager for improvements, but Revvity needs to take their feedback seriously and address the issues quickly. They are on a good path but need to put in more effort. Our client has been using their products for more than two years, and if the environment isn't stabilized within that time, they need to rethink their approach. They need to be more dedicated to addressing client needs.