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14 January 2018

The life of digital marketers - using Python for data analysis

It’s no secret that there is an extensive amount of data collected online at every given moment. Let’s just say it’s been a while since ‘cookies’ meant merely baked-goods.
For digital marketers this is a dream come true; an ability to customise their targeting and offers based on users’ behaviour, interests and even intent.
One major issue people are facing is the realisation that collecting the data - and understanding it - are two very different things.

Understanding data

“Knowledge is power” - this phrase goes back centuries and is still valid today; while some insist that the contemporary interpretation ought to include the word data instead of knowledge, the more correct version should actually be “data analysis is power”.
Gathering the data is only half the process; the true challenge lies in analysing it and translating it into actionable conclusions. It’s not for nothing that the appealing term “Big Data” can be intimidating. Usually used in reference to the large amount of unstructured data collected online, big data is basically unorganised, raw data with a lot of potential; the more information, the bigger the challenge, the higher the reward.
Those who have it - cherish it; those who can make sense of it - are cherished.

Over the years, many techniques and technologies have been developed in an attempt to make sense of data. Some are good, some are even better, but only one is Python

Python for data analysis

Python is a general-purpose programming language that is designed as a clean, intuitive and powerful tool. The idea was to create a code that is easy for humans to understand, and to reduce the time it takes to write code.
The beauty is that with Python data analytics has become something every digital marketer can learn; sure, like all things, it requires the time and practice. However, remember that it was designed as a code not just for other coders.
With the comprehension that data analysis is a critical element to online communication and commerce, data analytics courses have, understandably, become extremely popular.

Final note

Data analysis is power…  but the road from gathering the data > to reaching conclusions, is a winding road. It’s a good thing that there is Python, because with python data analytics is now a concept all digital marketers can learn and implement.

For digital marketers this is a dream come true; armed with that data, marketers are able to customise their offers and technique based on the surfer’s behaviour, preferences and even intent.
Data analytics courses are popular for a reason; they not only provide you with the knowledge and skills to decipher raw data, they introduce you other worlds - such as machine learning, artificial intelligence, and business intelligence.
 

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