SPECIALISTS

off their skill , acquires new ones , gets the gadgets they need , and starts to think as part of the team .

While we can ’ t montage away the training process in real life , it ’ s just as important for data transformation .

Team Members

Taxonomist & Ontologist

Your data is only useful if it ’ s contextualized and tagged for search and query . Data classification has to be consistent across the organization — errors in tagging can lead to incomplete results or broken queries .

Data Taxonomists classify data in a hierarchical structure — think of the way biologists sort animals into kingdom , phylum , class and species . Data Ontologists create dynamic structures to build and maintain relationships between data . Both are essential members of a data paradox-beating team .

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It may seem like the easiest way to get data experts on your team is to hire specialists . But candidates with advanced data skills can be hard to find . Only 19 % of companies are actively recruiting data scientists / software developers *, since there ’ s far more demand than supply .

One way to handle the shortage is to upskill your existing employees . You ’ ll need both the “ hard ” data skills , like classification and analysis , as well as the “ soft ” skills of interpretation and generating insight .

However , just having the right set of skills isn ’ t the end of the journey . The most highly-qualified teams can be hamstrung by manual , low-value tasks . It ’ s crucial to intelligently automate processes so employees can focus on higher-value analysis and generating insights .

A complementary strategy to upskilling is to partner with a “ data-as-a-service ” provider . Data-as-a-service lessens the load on in-house expertise and allows organizations to scale up their data strategy more quickly .

Beat the Data Paradox | 7