The Dataiku platform unifies data work from analytics to Generative AI. It supports enterprise analytics with visual, cloud-based tooling for data preparation, visualization, and workflow automation.
N/A
SAP Integrated Business Planning
Score 8.4 out of 10
N/A
SAP supports supply chain management with Integrated Business Planning, the company's real-time cloud-based supply chain planning platform supporting demand response, supply planning and inventory management oriented features, with supply chain analytics to support decisioning.
Dataiku is an awesome tool for data scientists. It really makes our lives easier. It is also really good for non technical users to see and follow along with the process. I do think that people can fall into the trap of using it without any knowledge at all because so much is automated, but I dont think that is the fault of Dataiku.
One of the best parts is how it is suited to global or multi-site organizations with complex supply chains. It just operates across multiple regions with various manufacturing facilities, and that too with very much ease; it is simple, solid and very reliable in terms of working when the logistics is an issue and fetches data and insights very quickly.
The integrated windows of frontend and backend in web applications make it cumbersome for the developer.
When dealing with multiple data flows, it becomes really confusing, though they have introduced a feature (Zones) to cater to this issue.
Bundling, exporting, and importing projects sometimes create issues related to code environment. If the code environment is not available, at least the schema of the flow we should be able to import should be.
The system does not work as smoothly when processing large volumes of data. There are processing delays when we are busy planning.
Moreover, because inventory exceptions are not automatically alerted, employees have to check them manually, which takes extra time. Upgrades in these sections could raise our operational efficiency.
The user experience is very good. Everything feels intuitive and "flows" (sorry excuse the pun) so nicely, and the customization level is also appropriate to the tool. Even as a newer data scientist, it felt easy to use and the explanations/tutorials were very good. The documentation is also at a good level
User experience has various issues, from the way to represent data on the Dashboard to complex graphical interfaces for making the right report of something that is easiest to make on other similar platforms. SAP Integrated Business Planning is difficult to integrate into other operating systems and ecosystems. Activity planning, in some cases, is confused, and access is limited if customers or end-users don´t use the platform over the internet using a desktop computer.
The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.
Set up a supply chain strategy. Define your north star. Follow it with good consultants. Get know how from consultants with a deep know how in the system. Do proper change management.
Anaconda is mainly used by professional data scientists who have profound knowledge of Python coding, mainly used for building some new algorithm block or some optimization, then the module will be integrated into the Dataiku pipeline/workflow. While Dataiku can be used by even other kinds of users.
System integration: CPI DS landscape allowed to integrate with the SAP ECC and SAP S4HANA with ease. Ecosystem: As most of the systema were of SAP landscape, choosing SAP Integrated Business Planning has given a sense of confidence. Higher Futuristic roadmaps: SAP Integrated Business Planning had gen AI and AI incorporated roadmap making it more impressive.
