Infograph: 5 Steps To Select A Data Science Vendor

Data Science is not an entirely new field, but has seen a massive rise in importance within enterprise organizations and startups alike. Across the business landscape where data science is now a “must-have” core competency, finding data science and machine learning experts is a hard and expensive task which is why companies have started considering data science outsourcing as a reasonable substitution of in-house specialists. As a result, business managers are becoming the primary information technology buyers, empowered to assemble a custom array of data science solutions which all work together seamlessly in the cloud or company infrastructure.

While this shift puts more control in the hands of managers, most lack a fundamental understanding of the real drivers of success when applying data science. Add to this the bewildering number of companies offering varying levels of data science-related services making it extremely challenging and difficult task for business managers to navigate.

Since there is no tried and tested recipe to select the right vendor, business managers should first define business needs and follow an iterative process that includes organisation’s preferences related to data storage, scripting language, and preferred usage tools.

Additionally, here are five steps that business managers should follow when developing a solid strategy for vendor selection in the data science technology space:



We at Valiance provide Data Strategy Consulting, Analytics Solutions Development and Business Intelligence. We are proud of our quality and on time delivery of traditional machine learning and big data projects. If you are looking to introduce AI or data science in your organization, contact us on how we can help.

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