How Dynamic Data Integration gets results, faster.

When integrating systems, the focus is on creating the right container to store data that may come when the system goes online. Schemas, joins, views… in systems that were traditionally not built to store the kind of data you want. When the system comes online, you realize the requirements have already changed. There is still no data.Data updates: today most integrations are one-directional. e.g. environmental data CAD. Bi-directional integrations are costly since you need to customize 2 systems instead of one. So any feedback loops are typically lost in emails, handwritten notes and issue tracking systems.When connecting systems, you are essentially doing what every single person that’s done an integration, has done before – mapping master data. For every data source, you are doing this again. and again. Laborious, prone to errors and without the ability to continuously make corrections while controlling this process. As a result, only a handful of companies have multi-dimensional data.

  • 1. Infrastructure built for purpose.

     

    » When integrating systems, the focus is on creating the right container to store data that may come when the system goes online. Schemas, joins, views… in systems that were traditionally not built to store the kind of data you want. When the system comes online, you realize the requirements have already changed. There is still no data.

     

    » Instead, we begin with mission driven data. Our platform was designed to do one thing – store, aggregate and analyze heterogeneous product data. So you start with results, and then decide on how you want them to fit into your workflow. Not the other way round.

  • 2. Mission-driven data fusion.

     

    » When connecting systems, you are essentially doing what every single person that’s done an integration, has done before – mapping master data. For every data source, you are doing this again. and again. Laborious, prone to errors and without the ability to continuously make corrections while controlling this process. As a result, only a handful of companies have multi-dimensional data.

     

    » Instead, we connect the world’s data sources so you don’t have to and have a community that continuously extends this. Multi-dimensional from the get-go.

  • 3. Transparent science means quality data.

    » Data quality is probably the most elusive activity today. Most companies don’t start on a journey because of data reliability and not having a means to maintain quality.

     

    » Instead, our platform is technically built and incentivized to create and improve the quality of product data. a community that continuously updates/improves the quality of our data. Partners that provide high-quality mission driven data.

  • 4. Pay for progress, not duplication.

     

    » Today the realm of data divides into “open” and “closed” data: paid-for commercial data vs. freely available, open science.   Both worlds are completely fragmented and disconnected. And then there is you, with a product to make, trying to make sense of of this puzzle with its thousand broken pieces.

     

    » Instead, we bring commercial data and open science together in a single system. We slice it into mission-driven components, so we can dramatically reduce cost and still solve your problem. We pay commercial data providers based on what you use, so you can focus on making better products, faster.

  • 5. Bi-directional APIs

     

    » Data updates: today most integrations are one-directional. e.g. environmental data -> CAD. Bi-directional integrations are costly since you need to customize 2 systems instead of one. So any feedback loops are typically lost in emails, handwritten notes and issue tracking systems.

     

    » Instead, standard APIs make it easy for different systems to bi-directionally connect to Makersite which holds connected data and is able to deliver that to every other system

  • 6. Empower anyone, not just experts.

     

    » But too often, expert data remains in the hands of experts. Business and Product Intelligence is for everyone, not just experts.

     

    » Deliver Product Intelligence directly to the tools your teams use everyday. Bring data into every action and every decision – in PLM, in CRM, or even in your custom applications.

  • 7. Disclose Impacts, yet protect your IP (and your supplier's)

     

    » Data privacy: Some product data is destined to be public and some is to remain confidential. You may not want to disclose exact substance compositions or proprietary processes, if they constitute a competitive advantage. Disclosing impacts (like your CO2 footprint) while protecting proprietary intellectual property, is a dilemma.

     

    » This cannot be achieved without the ability to vary the resolution of data being shared. F.ex. compliance wants to see a higher level of detail to substance composition than your supplier is willing to disclose. This requires record-level privacy. We refer to this as “IDO” level privacy – privacy at the level of a single line item. Makersite is the only platform today, able to disclose full impacts, while keeping IP protected.