What is the difference between business analyst and business analytics?

Business Analysis vs Data Science Difference #1: Definition Put simply, the overarching goal of a business analyst is to help grow a business in a given market under certain conditions. They have a direct influence on critical financial decisions made in the company. They use data to create and change policies, improve productivity and stabilise systems. A data scientist, on the other hand, is responsible for collecting, processing and reporting findings from a massive data dump. Data scientists convert raw data into structured, meaningful silos which are then used to generate reports on trends or make forecasts. Business Analysis vs Data Science Difference #2: Analysis A business analyst perceives data, insights and requirements from the perspective of the business and its overall operational systems. A data scientist observes and visualises the relationship between data in a database. While data analysts derive insights from data dumps, business analysts take what is needed to make the business function better and meet certain milestones. Both problem-solving roles are highly data-focused; the difference is that they enter at different stages of the operation and manipulate data to different goals. Business Analysis vs Data Science #3: Outlook Business analysts are strictly organisation-centric, though their policies might have a national or global impact. They deal with strategies, alliances and networks a lot more than data scientists. The latter is more likely to be mathematicians and statisticians in their outlook, sifting through data to find salient patterns and outliers. Whether a finding is of significance to the business or not, is up to the business analyst. That said, the business analyst heavily relies on data scientists to collect and segregate data they can work with.

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