Data Wrangling

If you have data from a source that was never meant to feed a graph data visualization tool, but that’s exactly what you need it to do – we’ve got you covered.

We’ve been wrangling data longer than we’ve been making Social System Maps – since before we developed sumApp – and for most of that time, our data-wrangling efforts have been about transforming standard survey or relational database outputs to work with graph visualizations (i.e. those dots and lines you see in Kumu, Gephi, Graph Commons, etc.).

We wouldn’t claim to be the most well-rounded data scientists, but when it comes to preparing survey or CRM data for network visualization, we’re probably the best option you have.

We understand what’s needed to prepare data for a network graphing tool (and we know all the little differences that the different tools require) – we’ve run into all the common (and not so common) snags and mistaken assumptions. We know the sneaky little places where things can go wrong and how to make them right.

You won’t have to know precisely what to ask for – such as text-to-columns, concatenating, piping, fuzzy-matching, v-lookups, depivoting (wtf is that!?! right?) – or understanding which info goes on which sheet. You won’t have to know what to look for in the output & how to be sure it’s good.

We know the fundamentals, we’ll see the decision-points and explain to you the impacts of the choices. You won’t have to think about anything technical, just how you want to be able to present your data. We’ll not only deliver the cleanest and most appropriately prepared data-set you could ask for, we’ll also save you a lot of time, because you won’t need to explain everything to us and double-check that we understood every little point.


Potential use-cases:

      • Converting CRM or spreadsheet data to load into sumApp (to take advantage of the ability to load pre-existing data into sumApp in Tiers III & IV).
      • Converting flat network survey outputs into node and connection sheets (data-sets that can be imported into Kumu, Gephi, Graph Commons, Polinode & others).
      • Converting data from other SNA tools into the format needed to load into sumApp (to take advantage of the ability to load pre-existing data into sumApp in Tiers III & IV).

Contact us to discuss your situation