It only takes 3 days (to integrate your data)

Anyone who’s ever been involved in data integration will confirm: integration projects are usually cumbersome and very time- and resource-intensive. Those facts alone take the wind out of the sails of many a company. Most, in fact, don’t even begin data integration projects.
But it doesn’t have to be like that. Integrating your first datasets into our semantic platform DISQOVER, happens in just 3 days. There’s no need for long trajectories! Within 3 days, your first internal datasets are searchable and you’re even trained to add additional datasets yourself.
Here’s how it works.

The preparation phase

Before we go into the 3-day integration workshop with you, we need around 1 week to get acquainted with your data. We interpret a representative set of your data (to learn more about the properties and variables) and see how it potentially links to the public data sources in DISQOVER. Your private data, as such, is linked to the public ontologies, and vice versa, so that, when you search in DISQOVER, you immediately get combined private and public data results. In fact, during this phase, your data is turned into 5-star data, making it available, structured and linked.

FYI: inconsistencies and ambiguities in the data are compiled in an error report, so that these can be clarified and tackled later on.

The goal of this preparation phase? To be able to work as interactively as possible during the 3-day workshop.

3-day workshop

At all our customers, we always start by setting up a pilot project.

Day 1: set-up and show you how data is integrated.

During Day 1, we upload your first full dataset(s), which was(were) already semantically enriched in the preparatory phase, into DISQOVER. During this day, we demonstrate and explain to you how DISQOVER can be installed and maintained, how data is uploaded, how our federated search engine  functions, how you can customize DISQOVER to your brand and tastes and how you can move things into production.

Day 2: integrate 2 to 4 datasets with your data scientists so that they can do linked data integration in future.

Day 2 is all about visualizing your data. During an iterative process along with your own data scientists, we co-create logical search patterns for your data. By trying out different search paths, we begin to extract value out of your private and public data. Day 2 makes your data visible and searchable in DISQOVER.

 Day 3: test use cases live with end-users.

Day 3 consists of a series of sessions with end-users. Their feedback is implemented on the spot, improving the search paths within DISQOVER and making everything more intuitive and user-friendly.

You’re ready!

At the end of the 3 days, we’ve installed DISQOVER and explained to you how you can add additional data yourself and how you can configure and visualize the platform. That means that from there on, you can work with DISQOVER without our intervention. So you don’t have to worry about long and extensive consultancy trajectories further down the road. Nope. From now on, you’re in the driver’s seat. Your data scientists, along with a server architect, can handle DISQOVER all by themselves.

An ongoing journey

What we see happen at many customers, is that the implementation usually starts at one specific department. But gradually, as more projects are defined, additional data from various teams within the organization is added. As such, the number of datasets available within DISQOVER and the value that can be derived from it, is continuously extended.

Thanks to our federated search method, there is literally no limit to the number of datasets that you can add! So the broader DISQOVER gets, the more relevant and more valuable it becomes. And all this, you can handle yourself!

Want to learn more about searching your private data through DISQOVER? Do reach out to me or one of my colleagues!

Sign up for DISQOVER for free! Our Community license gives you direct access to the public data sources within DISQOVER.


Photo ‘Calendar’ by Droid Gingerbread via Flickr.

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