Data Science for Marketers  -  Tomorrow's Knowledge Today!
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Tomorrow's Knowledge Today!

Marketing Analytics or Data Science - The Fundamental Difference

It is easy to understand why data-driven marketing is quickly becoming the status quo, but what do you need - analytics, data science or both?

Data science and analytics compliment each other but there are fundamental differences between the two. At a basic level, analytics tend to be more tactical and departmental, while data science is more strategic and organizational.

Data analysts leverage analytic tools to read and study historical marketing data. A subset of data science, analytics are adept at identifying historic trends and communicating the results of previous performance.

Data science, on the other hand, is responsible for understanding how all available 1st, 2nd and 3rd party data can be leveraged to gain competitive business intelligence.

Data scientists are business analysts that are typically more concerned with forecasting the impact of future business decisions than looking back at historical trends.

Where analytics are needed to understand past marketing performance, data science is needed to answer more difficult forward looking business questions.

Both disciplines and technologies are needed to extract marketing intel from data and turn that intel into business knowledge.

Quick Tip

Leadership can achieve results beyond the ordinary through foreknowledge.

Additional Tips


Fast Fact

There are three different skills that make up the field of data science.

1. Business
2. Technology
3. Mathematics

Fast Fact(s)

Data Science as a Service (DSaaS)

Gain a distinct competitive advantage with the following Data Science as a Service (DSaaS) offerings.

- Aggregation
- Visualization
- Data Modeling

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