Building a Team of Big Data Experts for Your Business
The formation of a comprehensive data science team is not an easy task. Many businesses are still attempting to assay the various potential roles of a data scientist. The following tips may assist your effort to build a data science team:
Required Roles: A data science team requires learned and trained manpower to comprehend large datasets and the theory behind the data. For instance, data science professionals such as data software developers and engineers help understand the distributed programming of datasets along with its infrastructure and architecture. Even the size of the business needs to be considered. Project managers can lead large teams building products based on real-time data in business enterprises with a high workforce. Other required roles include data platform administrator, full-stack developer, data solutions designer, and architect.
Agility in Processes: Beyond mere monitoring and evaluation of data, the data science team also requires agility to bring about beneficial changes in different areas of the organization from the massive datasets assessed. Collaboration in the workplace between department leaders facilitates a multi-disciplinary contribution to optimum utilization of data created.
Data Platform: Gaining knowledge about the various platform options available in the market such as Hadoop and Spark is considered important for data team members. Hadoop is a leading player in big data technology, while Spark is gaining popularity for real-time processing.
Building a data science team for your business is more or less an unrushed process of selecting the right people, processes, and platform to benefit your business with professional value.
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