Want to get data right? When you first decide to “do data better”, it often leads to a second decision – build vs buy. This results in the consideration of hiring a data scientist and/or data engineer to help get you there. If you decide to go down the build route you’ll need data professionals to create, implement and manage your data infrastructure.
A complete data team in a large organisation will likely feature Data Analysts, Data Engineers and Data Scientists. Unsure of the difference between the roles? Before you start the recruitment process, make sure you understand the roles and responsibilities of data jobs.
Too many businesses attempt to cheat the system with ‘Do Not Pass Go: Proceed Directly to Data Science’; however, once you’ve established a single version of the truth and core analysis, data science is a fantastic way to empower major decisions.
Data Scientists gather and analyse large sets of data, usually in the data lake or file store, rather than data warehouse, specialising in building machine learning and Artificial Intelligence models. A Data Scientist’s role combines computer science, statistics and mathematics with business knowledge.
They use advanced techniques to build data products, algorithms that add value to stakeholders in a tangible manner. Often they are creating the data foundation to enable analytics.
kleene’s SaaS software makes this easy, so you won’t need to make expensive Data Engineer hires. You can hopefully save on some Data Science headcount too, by cutting down significantly on data cleaning and preparation time. We provide scale-ups with the data infrastructure necessary to build their single source of truth and empower Analysts to deliver value (without the need for data engineering!)
Our end-to-end automation and analysis removes the headache of data. Don’t worry if there isn’t in-house data expertise, kleene can handle your strategy, report building and much more!
Book a demo today to start solving your data problem!
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