There are really two streams that we can see these days coming out of Master’s programs. One is the marketing/product Analytics practitioner and the other is data science practitioner. At the initial levels we need to learn both streams because it will not really be clear to a student where their capability or interests truly lie.
Based on this premise, I would like to suggest a few types of learning that web analyst in particular need to imbibe in the start of their careers.
Business Writing is factual journalism.
I have experienced a lot of analysts coming in with lots of capability with numbers but none with writing business stories. I also see many analysts who don’t know the first thing about how to use stats tests in real life situations. Simple questions like — Did the pricing change lead to more leads? Are the results statistically significant? — make us all go into huddles and battle stations.
Several online course providers offer creative writing, business writing or journal writing courses and I think they should be part of any Analysts formative education.
Knowledge of the tools.
We need to provide hands-on understanding of the tools that are used in typical business analytics. I have seen a lot of spreadsheets(Excel wizardry can take you lots of places) being used.
There are some statistical packages like R(open sources and free, hence very useful), SPSS and SAS that the analyst should be familiar with. More importantly, they need to be able to live and breathe statistics because the core fundamentals are always useful. Some elements of data mining and clustering should also be learnt as needed or as a person’s curiosity demands it.
These days, data visualization done correctly, explains half the analysis by itself. So, some experience in Tableau, Microstrategy, Qlikview is very important in explaining the information clearly.
I also see a lot of visualization available via Google Data Studio and Power BI.
At the end, it is all code.
Whatever the environment of development in an organization, the analyst should have a fair idea about it since all the measurement hooks are mostly encoded. Even the ubiquitous Google Analytics is run based on javascript. A solid grounding in Python, PHP and SQL is also important so we need some intermediate technical courses to get a well-rounded technical perspective.
Understand the data river as it flows downstream
Although, large amounts of data exists, we don’t get training in information architecture.. How do you get unstructured data to structured data, to BI tools and to reports and metrics is something that needs to be taught too. The analyst can use some BI tools and data warehouse development and maintenance skills. As it become more common to build self-service reporting systems, we need to be able to teach some rudiments of this skill to our budding analysts.
Project Management
Most Analysts end up in large project teams as core members in-charge of numbers. So we need to teach them principles of project management and the current techniques like Agile and kanban. This will help them build their managerial skills too.
Design and Analytics
A good analyst will have a strong creative streak, not just have a good head for numbers. We need to be able to look the system that we are trying to improve (or make profitable) from a design perspective too.
In fact, a lot of web analytics is done just to measure and influence the design and flow of the information on the site for the customer. Conversely, not many designers are just going to rely on their intuition while building a site. They would ask the analyst about measuring the success of a particular design. So, a couple of introductory courses on creative design are essential for the education of an analyst.
I hope these make sense dear reader. Please let me know your thoughts.
