Product Data Lake is a cloud service for sharing product data in the business ecosystems of manufacturers, distributors, merchants, marketplaces and large end users of product information.
Yesterday some new capabilities have been included in the service.
As a manufacturer you can now utilize Product Data Lake even more as a cloud based lightweight Product Information Management (PIM) system. We have added better views of uploaded product information and better means of managing product data within the service. This will be of benefit for manufacturers who already handles product data in ERP and Product Lifecycle Management (PLM) solutions and needs a cost-effective solution to share these data with trading partners. Learn more about this option on our Product Data Push site.
Also, independent providers of hubs of product information within a given industry and/or geography can now self-register as a reservoir inside Product Data Lake and thus add a modern and generic way of collecting and distributing product information to existing specialized product data pools.
But we do not stop there. The next version 1.4 will be live just before our Far East development team takes some time off for the Lunar New Year. This version adds new possibilities for pushing product information through Product Data Lake. We already support file drops via FTP domains, traditional interactive upload from network drives and direct data entry. Next option is APIs.
Further versions during the coming months covers deeper integration of popular product information standards such as ETIM, eClass and UNSPSC. Learn more about these standards in the post Five Product Classification Standards.
If you want a presentation of current and future capabilities within Product Data Lake, please make contact below:
In here Joe examines how data warehouses can be modernized to augment architectures supporting data lakes and Mater Data Management and the case for moving data warehouses to the cloud.
In my view, a lot of data management disciplines will eventually move to the cloud as one follows the other. By adding “beyond” I suggest, that cloud solutions will not only be something that is supported company by company. Eventually you will be able to get business outcome by sharing data management burdens within your business ecosystem.
My current venture called Product Data Lake is an example of such a solution. It modernizes the data warehouse thinking within product information sharing by using a data lake concept in the cloud ready-to-use by trading partners within business ecosystems:
If you are a provider of product information, typically as a manufacturer of goods, you can harvest your business outcome by using us for Product Data Push
If you are a receiver of product information, you can harvest your business outcome by using us for Product Data Pull
In his post Andrew connects the classic dots: How does technology lead to business outcome? Especially the use of cloud solutions and the multi-tenant aspect is in the focus. Andrew asks: What do you see “out there”?
My view is that multi-tenant is not just about offering the same subscription based cloud solutions to a range of clients. It is about making clients sharing the same business ecosystem work in the same MDM realm. This is the platform described in Master Data Share.
Oh, and what does that have to do with business outcome? A lot. Organizations will not win the future the race by optimizing there inhouse MDM capabilities alone. With the rise of digitalization, they need to connect with and understand their customers, which I believe is something Reltio is good at. Furthermore, organisations need to be much better at working with their business partners in a modern way, including at the master data level. The business outcome of this is:
Having complete, accurate and timely data assets needed for understanding and connecting with customers. You will sell more.
Having a fast and seamless flow of data assets, not at least product information, to and from your trading partners. You will reduce costs.
Having a holistic view of internal and external data needed for decision making. You will mitigate risks.
In here Julie says: “Adoption of cloud-based MDM or MDM-as-a-Service is on the rise, opening up new dimensions for how organizations take advantage of MDM and data governance.”
Julie’s article is part 3 of a six part series on the “New Age of Master Data Management”, so I may touch on a dimension that is covered in the upcoming articles. This dimension is how business ecosystems must be a part of your organizations MDM roadmap, and that dimension is, according to Gartner, the analyst firm, covering 8 underlying dimensions as told in the post From Business Ecosystem Strategy to PIM Technology.
Working with MDM in a business ecosystem context does require MDM in the cloud of some sort. Inhouse Mater Data Management and Product Information Management (PIM), which may be on premise or in the cloud or perhaps a hybrid, is only the beginning. Collaboration with business partners in a sophisticated environment will be controlled by a cloud solution.
In his article, Aaron Zornes looks at the slow intake of multi-domain MDM, proactive data governance, graph technology and Microsoft stuff ending with stating that MDM as MANAGED SERVICE = HOT:
“Just as business users increasingly gave up on IT to deliver modest CRM in a timely, cost effective fashion (remember all the Siebel CRM debacles), so too are marketing and sales teams especially looking to improve the quality of their customer data… and pay for it as a “service” rather than as a complex, long-time-to-value capital expenditure that IT manages”.
I second that, having been working with the iDQ™ service years ago, and will add, that the same will be true for product data as well and then eventually also multi-domain MDM.
Since then the use of the term blockchain has been used more and more in general and related to Master Data Management (MDM). As you know, we love new fancy terms in our else boring industry.
However, there are good reasons to consider using the blockchain approach when it comes to master data. A blockchain approach can be coined as centralized consensus, which can be seen as opposite to centralized registry. After the MDM discipline has been around for more than a decade, most practitioners agree that the single source of truth is not practically achievable within a given organization of a certain size. Moreover, in the age of business ecosystems, it will be even harder to achieve that between trading partners.
This way of thinking is at the backbone of the MDM venture called Product Data Lake I’m working with right now. Yes, we love buzzwords. As if cloud computing, social network thinking, big data architecture and preparing for Internet of Things wasn’t enough, we can add blockchain approach as a predicate too.
In Product Data Lake this approach is used to establish consensus about the information and digital assets related to a given product and each instance of that product (physical asset or thing) where it makes sense. If you are interested in how that develops, why not follow Product Data Lake on LinkedIn.
In my eyes, this trend will have a huge impact on how data management platforms should be delivered in the future. Until now much of the methodology and technology for data management platforms have been limited to how these things are handled within the corporate walls. We will need a new breed of data management platforms build for business ecosystems.
Such platforms will have the characteristics of other new approaches to handling data. They will resemble social networks where you request and accept connections. They will embrace data as big data and data lakes, where every purpose of data consumption are not cut in stone before collecting data. These platforms will predominately be based in the cloud.
Right now I am working with putting such a data management service up in the cloud. The aim is to support product data sharing for business ecosystems. I will welcome you, and your trading partners, as subscriber to the service. If you help trading partners with Product Information Management (PIM) there is a place for you as ambassador. Anyway, please start with following Product Data Lake on LinkedIn.