Myth #1--Data science is just about science, Myth #2--Data science is just a trendy rebrand of business intelligence
Mo Data stashed this in Big Data Hype Cycle
Myth #1--Data science is just about science
Data science is often linked to big data, partly because data scientists often work with the extremely large and complex datasets. There is much more to it than that. Data science uses the scientific method to create experiments that test hypotheses based on available data. These concepts may glean unique insights from smaller datasets as well as large ones.
Myth #2--Data science is just a trendy rebrand of business intelligence
Data science and business intelligence are very different. Business intelligence and its associated analysis is typically a backwards-looking exercise, intended explicitly for reporting purposes. Data science, meanwhile, involves running experiments on data, rather than seeking particular outcomes. It's a forward-looking approach that relies on asking 'What might happen in the future?', rather than stating 'this happened in the past.'
Myth #3--You can buy software that will do the hard work for you
At its core, data analysis involves people. It requires skilled professionals who can speak the language of business, as well as the language of data. It requires critical thought, scientific judgment, creativity, pragmatism and common sense. This is very difficult to outsource to software (for now at least).
Myth #4--Data science is too complex for 'normal' business people
Data science is only successful if the insight it uncovers can be articulated to non-specialists and key decision makers. This element of the analytics chain--which we at Deloitte Analytics Institute call 'data artistry'--requires a particular set of skills, and is one of the most crucial aspects of data science.
Myth #5--Data scientists work best alone
Yes, there are some people who can do it all, but these people are rare and expensive. It is clear that the most successful data science is done by teams of people--scientists, communicators, other analytical professionals, those with domain expertise and consultants--combining their expertise to derive real insights that businesses can use.