On this page we offer you the opportunity to take a closer look at SynerScope’s unique business offering.

Written by experts in the field, these white papers provide comprehensive information about our products and how it helps solve your problem of understanding the data in your data lake, where a large collection of structured and unstructured data is merged.

Open Government and Archiving: How to benefit from cloud technologies


As digital data grows fast, and government organizations embrace and expand their use of cloud technology to tackle the challenges of scale associated, the importance of secure and compliant cloud solutions cannot be overstated.

For Dutch local and national government organizations, the scale of digital data coupled with the regulations and laws about handling data, present three major challenges: How to select data for archiving, how to provide good quality data and easy access to the archived data.

The Dutch Open Government law (Woo) demands transparency combined with a timely response to information requests but also Privacy protection in line with the demands of the GDPR

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Open Government

Shining a Light on Dark Data: Ixivault by SynerScope

whitepapers SynerScope

by Dr. Robin Bloor | The Bloor Group (2023)

When we store data in a database, we tend to assume that we have captured most of its meaning. This is never the case.

Let’s be clear. This is not about the meaning of secret correlations buried in the data that might be unearthed by clever AI algorithms. Neither are we talking about the bulk of what Gartner began to describe as “Dark Data” about a decade ago—the data that organizations gather which they fail to exploit because they ignore it. Such data is no longer so murky. The building of well-designed data lakes exhumed such data.

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SynerScope in Detail: impressive data visualization

white papers

by Philip Howard | InDetail Paper Bloor (2018)

The idea behind SynerScope’s products – Ixiwa and Iximeer – is that the industry has been more focused on the volume and velocity of big data and not enough on its variety.There is justification for this argument.There has been a lot of emphasis on scaling data lakes on the one hand and deploying stream processing on the other. However, these are essentially hardware issues.

Of course, there is a software element but the advent of more powerful processors, the reduction in price of in-memory processing, and the use of graphical processing units all mean that the volume and velocity issues of big data can be readily resolved. However, variety is another matter.

Certainly, there has been a focus on sensor data within Internet of Things environments, but sensor data is much more nearly structured, and can fairly easily be put into, say, a relational table format, than data that is in a Word document, or an image or an audio file.

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