Sandboxes instead of walls

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The mission of date warehouses (DWH) is to be the source of “undoubted” information. To have the “single version of truth” they operate with strict rules. However, this leads to the problem that they are not able to adapt to a rapidly changing business environment. Therefore most of the time it is essential to attach some “explanations” or “corrections” to the reports created from the DWH to amend it with information from other sources.  No wonder that executive reports are usually created manually in MS Excel or PowerPoint. In this case, careful hands add important information from outside the regulated DWH to the DWH reports. The concept of “DWHs collect all information” is nothing else, but: an utopia.

Therefore, it can be said that managing a company based on “hard” data (i.e. standard reports) only, is not possible. However, decisions should not be based exclusively on “soft” data (i.e. coming from unregulated channels).

The optimal solution is to take both sources into account.

If IT departments were willing to admit that both “hard” and “soft” worlds have solid grounds, they could support the union of the two by providing “sandboxes” for the various business units.

Business units would be able to load their own data into the sandbox without any regulation and would be able to access even the DWH. No more need for data “downloads” or “exports” from the DWH, no more need for mediocre crafts – e.g. think about the vlookup function in Excel – to merge the two sources.

Clearly, sandboxes are server-side environments with a performance that is better than desktop computers’. It’s obvious that these environments have to be administered (CPU performance, storage distribution, version upgrades…) but the IT department does not take responsibility over the content. Sandboxes could also include Big Data infrastructure giving the possibility to business users to get familiar with unstructured data as well.

It is important to look after the work in the sandbox – both the technical and organizational aspects – to notice if different units are working on similar tasks. In this case, coordination of these approaches are necessary.

It is not from the devil to place “professional” scheduler functions similar to professional ETL tools into the sandbox to support the regularly executed commands. Running a process put together by business analysts every night or every Monday morning fits into the concept of sandboxes.  Obviously, the maintenance and error handling of these processes are managed by the business users.

It must also be recognized that sandboxes come with risks of data security and access management. As the data structure is not as strict as of DWHs, access management is also more unbound. The problem of one of the users having access to data relevant only to his region is hard to resolve. On the other hand, there is less probability that data will end up outside the regulated areas as attached to emails, on shared drives, etc.

If the sandbox is created and operated well enough, the big moment will come. Success is – as I interpret –when polished data manipulating processes advance into the DWHs by the business units. This demonstrates that pure purpose overcomes the power oriented aspect: a business unit shares its results with the whole organization.

With this, corporate data assets are enriched by something really valuable. And explorers can take another step further.

Hiflylabs creates business value from data. The core of the team has been working together for 15 years, currently with more than 50 passionate employees.

The picture is created by Johan Eklund. (

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