The Long Tail of Product Data Synchronization

When discussing with peers and interested parties about Product Data Lake, some of the alternatives are often brought up. These are EDI and GDSN.

So, what is the difference between those services and Product Data Lake.

Electronic Data Interchange (EDI) is the concept of businesses electronically communicating information that was traditionally communicated on paper, such as purchase orders and invoices. EDI also has a product catalog functionality encompassing:

  • Seller name and contact information
  • Terms of sale information, including discounts available
  • Item identification and description
  • Item physical details including type of packaging
  • Item pricing information including quantity and unit of measure

The Global Data Synchronization Network (GDSN) is an internet-based, interconnected network of interoperable data pools and a global registry known as the GS1 Global Registry, that enables companies around the globe to exchange standardised and synchronised supply chain data with their trading partners using a standardised Global Product Classification (GPC).

This service focuses on retail, healthcare, food-service and transport / logistics. In some geographies GS1 is also targeting DIY – do it yourself building materials and tools for consumers.

Product Data Lake is a cloud service for sharing product information (product data syndication) in the business ecosystems of manufacturers, distributors / wholesalers, merchants, marketplaces and large end users of product information.

Our vision is that Product Data Lake will be the process driven key service for exchanging any sort of product information within business ecosystems all over the world, with the aim of optimally assist self-service purchase – both B2C and B2B – of every kind of product.

In that way, Product Data Lake is the long tail of product data synchronization supplementing EDI and GDSN for a long range of product groups, product attributes, digital assets, product relationships and product classification systems:

EDI GDSN PDLFind out more in the Product Data Lake Overview.

Using a Publish-Subscribe Pattern for Product Data Syndication

In software architecture, publish–subscribe is a messaging pattern where senders of messages, called publishers, do not program the messages to be sent directly to specific receivers, called subscribers, but instead categorize published messages into classes without knowledge of which subscribers, if any, there may be. Similarly, subscribers express interest in one or more classes and only receive messages that are of interest, without knowledge of which publishers, if any, there are.

This kind of thinking is behind the service called Product Data Lake I am working with now. Whereas a publish-subscribe service is usually something that goes on behind the firewall of an enterprise, Product Data Lake takes this theme into the business ecosystem that exists between trading partners as told in the post Product Data Syndication Freedom.

Therefore, a modification to the publish-subscribe concept in this context is that we actually do make it possible for publishers of product information and subscribers of product information to care a little about who gets and who receives the messages as exemplified in the post Using a Business Entity Identifier from Day One. However, the scheme for that is a modern one resembling a social network where partnerships are requested and accepted/rejected.

As messages between global trading partners can be highly asynchronous and as the taxonomy in use often will be different, there is a storage part in between. How this is implemented is examined in the post Product Data Lake Behind the Scenes.

Pub-Sub pattern
Image credit: MSDN blog

How Wholesalers and Dealers of Building Materials can Improve Product Information Efficiency

MaterialsBuilding materials is a very diverse product group. As a wholesaler or dealer, you will have to manage many different attributes and digital assets depending on which product classification we are talking about.

Getting these data from a diverse crowd of suppliers is a hard job. You may have a spreadsheet for each product group where you require data from your suppliers, but this means a lot of follow up and work in putting the data into your system. You may have a supplier portal, but suppliers are probably reluctant to use it, because they cannot deal with hundreds of different supplier portals from you and all the other wholesalers and dealers possibly across many countries. In the same way that you are not happy about if you must fetch data from hundreds of different customer portals provided by manufacturers and other brand owners.

This also means that even if you can handle the logistics, you must limit your regular assortment of products and therefore often deal with special ad hoc products when they are needed to form a complete range of products asked for by your customers for a given building project. Handling of “specials” is a huge burden and the data gathering must usually be repeated if the product turns up again.

At Product Data Lake we have developed a solution to these challenges. It is a cloud service where your suppliers can provide product information in their way and you can pull the information in the way that fits your taxonomy, structure and format.

Learn about and follow the solution on our Product Data Pull LinkedIn page.

If you are interested, please ask for more information here:

 

Product Data Lake is going to the next level

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The path ahead

Until now my venture called Product Data Lake has been a rather technical quest. As with most start-ups the first years have been around building the actual software (in our case facilitated by Larion Computing in Vietnam), adjusting the market fit and run numerous trials with interested parties.

Now it is time to go to market for real. I am happy that another Henrik has joined as CEO and will emphasize on leading the marketing, sales and financial activities.

While I will be concentrating on the product strategy and product management activities it is time to recap the business outcomes we want our subscribers and partners to achieve. Let me express those towards three kinds of business partners:

Manufacturers and brand owners:

On the upstream side of Product Data Lake our goal is to let you as a manufacturer and/or brand owner:

  • Sell more: Your re-sellers will have the most complete, accurate and timely product information in front of their customers.
  • Reduce costs: Push your product information in one uniform way and let your re-sellers pull it in their many ways.

Our concept, using emerging technologies within Product Data Lake, will free you from applying many different solutions to providing product information to your re-sellers. You will avoid errors. You will be able to automate the processes and you will be easy to do business with in the eyes of your trading partners.

The people who will use your products want to get complete product information when making the buying decision wherever they are in the supply chain.

You can follow the news stream for this on our LinkedIn showcase page called Product Data Push.

Merchants (dealers and retailers):

On the downstream side of Product Data Lake our goal is to let you as a merchant (dealer or retailer) gain substantial business outcome.

  • You will sell more by having the most complete, accurate and timely product information in front of your online customers when they make self-service buying decisions.
  • You will reduce costs as you can pull product information in one uniform way and let your suppliers push it in their many ways. Hereby you can automate the processes, avoid errors and reduce product returns.

Our solution, using emerging technologies within Product Data Lake, will make you be easy to do business with in the eyes of your suppliers and make your product information transform into a powerful weapon in the quest for winning more online market share.

The people who may buy your product range deserves to know all about it and wants to get that information when making the buying decision. Remember: 81 % of visitors will leave a web-shop with incomplete product information.

You can follow the news stream for this on our LinkedIn showcase page called Product Data Pull.

Technology and service partners:

Ambassadors at Product Data Lake can sign up subscribers, assisting these subscribers in uploading their relevant product information portfolio to Product Data Lake and assisting these subscribers in linking their product information with the product information at their trading partners. As an ambassador, you will:

  • Have the opportunity to work with a big data solution within Product Information Management.
  • Have the opportunity to make data mapping and/or data integration services and cross-sell of other services for subscribers in a whole supply ecosystem.
  • Get 25 % kickback on new subscriptions in a potentially exponentially growing subscriber base in supply ecosystems

As Reservoir you can bring new life into product data portals and pools. Product Data Lake is a unique opportunity for service providers with product data portfolios for utilizing modern data management technology and offer a comprehensive way of linking, collecting and distributing product data within the business processes used by subscribers. Signing up as reservoir is free.

The linking theme also related to applying artificial intelligence / machine learning to mapping between the different product information taxonomies in use at trading partners, where we collaborate with business partners who provide such capabilities.

You can follow the news stream for this on our LinkedIn showcase page called Product Data Link.