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The future of data analytics will be in the joining up of currently disparate datasets. When data is pooled the insights become more valuable. The value of joined data presents businesses with new opportunity but also presents consumers with added risk.
Data inside the firewall
Data science today is mostly restricted to the data available to a single organization. This helps that one organization become more efficient and competitive. Each retailer analyses data from customer loyalty schemes, supply chain data, store transactions, product sales, store traffic, and online ad conversion.
The insights uncovered help improve customer acquisition and retention, and reduce supply chain and inventory costs.
Data driven organizations are manufacturing data. Good data science seeks to enrich the data available. Google gained access to phone and vehicle data through its acquisition of Android and Waze. The Facebook ‘like’ button is one of the most valuable data enrichment tricks of all time.
It enabled Facebook to collect preference data for the billions of users on the platform. Analysis of preference by age group, location, job function, and family relationship allowed Facebook to build the social graph.
First and third party data
Marketers used Data Management Platforms (DMPs) to augment its own customer data (first party data) data from the total population of customers in its database (third party data). That data was being combined without the users’ permissions. New privacy regulations are ending this practice.
Safely joining personal data
Data analysis will need to adopt the network effect to deliver benefits of a new order of magnitude. Over the next 5 years data will join up across organizations. Advances in data science and semantic technologies permit the analysis of disjoint data that crosses organizational and domain boundaries.
These new standards and new alignment technologies will create a more semantic web where enrichment data is made available and consent to combine will be explicitly granted.
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