The term ‘alternative data‘ is gaining traction via the US ( of course!), but is actually somewhat misleading.
What this actually refers to is supplementary data, in the sense that it may add value to existing datasets. For instance, leading asset management companies in the US are now actively seeking other forms of data beyond the purely financial, in order to better understand their asset base, and make value increase from improved decision-making. In case you think this is a bit remote, just ponder on Google’s recent feature: the ability to highlight structured data sources on your website, the Google Data Highlighter. Enterprises are now on the hunt for data as a means of increasing their value and digital corporate footprint, for competetive advantage.
There are several hurdles:
- Companies find it hard to determine what the content of the supplemental data might be? If a potential data acquisition is identified, how will you know (before you buy) what data is relevant; what condition it’s in; and exactly how much ‘dark data’ there is that may or may not be of use but you are still going to be paying for?
- Once they have identified and acquired it, they need some serious data wrangling and tooling to make it:
- suitably formatted;
- of sufficient quality; and
- capable of comparative use – and in some cases, of using the same canonical model.
- The business case (compliance-permitting) may point towards hosted datamart solutions – which may take away some of the technical pain providing the incumbent datasets are relevant.
If you are in this position, we can help with addressing your data problems and advise on the best route forward.
Alternatively, if you hold alternative data, you may wonder who to approach with it, how, and how to monetise that data (assuming you have rights to do so and are not breaching any data protection or privacy laws).