Without the right data, any analytics initiative is just an illusion. For machine and deep learning efforts, new sources of data are always in demand. In a few of our Innovation at Scale study interviews, respondents pointed to the rising need for data hunters. I asked our resident guru on all things data driven, Arturo Salazar, about this concept.
By Serge Boulet, Marketing Director at SAS
Data hunters are emerging as organisations look beyond their boundaries for additional insights. Data hunters are becoming increasingly crucial as organisations start to realise that their own data is not enough to get the required competitive edge.
They therefore look for external sources of data that can be combined with internal information to generate new insights into customers, competitors and/or the market.
This is particularly important as more advanced analytics solutions, including AI, become omnipresent, and companies have to find ways to get additional value out of them.
Data hunters combine extensive knowledge, understanding, intelligence and practical ability. Data hunters have several different job titles, including data acquisition specialists and data scouts. However, the roles are all similar. Data hunters are people who really understand business drivers, needs or challenges.
They use their knowledge of both the business and the external environment to work out what new data sources - often, but not always, external - could be helpful in addressing a particular issue. They then apply their practical skills to get the data and/or develop the new data streams and make them available to the organisation. They are, therefore, the upstream partners of data scientists and analysts.
Data hunters need to have a good understanding of what is already available and what might be possible. There are increasingly large supplies of data available. Companies are seeing the value in making their own data more widely available (the open data concept). Unstructured data is also being turned into more structured forms by firms with web crawlers and text analysing software.
Data hunters need to be aware of what data sets are already available - but they also need to work with the art of the possible. This means identifying what information could help to better solve a particular challenge, and then working out how to obtain this from new sources.
Data hunters, perhaps even more than data scientists, need to work across the organisation. Data sets are often expensive to acquire, and it makes sense to get as much value as possible out of each one by sharing it across departments and using it more than once. It is also important to avoid buying the same data several times. Data hunters, therefore, have a role to play in making sure that data is discoverable within the organisation.
Data hunters play an important part in organisational data governance and management. Because of their role in making data discoverable, data hunters can provide the feedback required to keep the organisational data under control. They need a good understanding and knowledge of best practices in data management and governance. T
hey also need to be able to explain these issues to others to ensure that data quality is maintained. Finally, they need the skills to manipulate and manage data themselves to the required standards.
Data hunters are already becoming an important part of many companies. Data hunting is not something for the future: It is already here. Forrester, the research organisation, recently did some work on external data use. During a webinar, the presenters asked the audience about their experience of data hunters.
A third of those on the webinar said that their organisation already had at least one data hunter role. Almost half (44%) said that they had a formal process for sourcing external data. This sample is, of course, not likely to be representative of all companies. For a start, nobody without an interest in sourcing external data would have been attending the webinar. However, it is probably indicative of a growing trend.
Data hunting ability is a key difference between faster- and slower growing companies. In a recent report from Forrester, ability to source external data appeared to be a key distinguishing feature of high growth companies. The report suggests that 66% of data and analytics decision makers at fast growing companies were expanding their data hunting ability, with a focus on external data.
This figure dropped to just 51% in slower-growing companies. This suggests that data hunting is a key way to gain competitive advantage and drive organisational growth in an increasingly data-driven world.