When you start your journey in the data science career path, you will come across these terms quite often: data science, business intelligence, and big data. They are very much interconnected and rely heavily on each other.
Data Science is the technology that uses Big data to draw insights and assist organizations with their data-driven decision-making. At the same time, Business Intelligence involves the analysis of structured data to provide actionable insights for strategic decision-making within an organization.
Data Science and Business Intelligence may seem similar but they have significant differences. When it comes to their applications, a data science model can be used for prediction in finance, healthcare, manufacturing, and other industries. But business intelligence is used to generate reports, make interactive dashboards, and offer other data visualizations to help businesses monitor KPIs, and identify trends and areas of improvement. Big data simply refers to huge amounts of data usually in terabytes or pentabytes that fuel the data science and business intelligence processes.
For all the students and young professionals looking to get started with their data science career, they must be well-versed in the basic concepts of these three broad terms. They must understand what each of these actually means, which tools are required to handle the relevant processes, and how they are applied in the real world.
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