How to get started on being a data/business analyst ( not scientist)

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Understand how to present data well.

This is not just learning how to use Tableau or Power BI proficiently - its about distilling messy or complex info into something that is simple and clear. Whether its numerical data, processes, words, or large datasets - this skill is so crucial

In addition to Data Viz, a bit of python (pandas, numpy, matplotlib), Alteryx, SQL, Excel, PowerPoint, & Data Architecture (ie. understanding how to use containers and some high-level data pipelines) are good tools to have

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In true consulting form, try to run through a mental checklist whenever you are analyzing data/information

Q1 = who will be looking at your end product (more senior – typically less detail, if business user – don’t go into the technical weeds)

Q2 = If working with figures and numbers, ask yourself what you are trying to highlight in the data (ie. are you trying to call out a specific figure, show an outlier, show a few outliers, show the entire scope of data, show a particular variance, show a few variances, compare two figures etc..)

-> this will affect how you choose to present the data. If you are calling out 1 figure, highlight it – if you are showing variances, don’t clutter the diagram with a million #’s , just highlight the variance delta and maybe the odd figure)


Q3 = If its text or processes, it’s a similar set of questions to those using numerical data (ie. are you trying to show the entire scope of the process or hone in on a specific step [or both?]. Are you trying to provide a general case/structure or list a series of exceptions [or both?].

-> Again, this will affect how you choose to present the data. For example, if you need to show both, the question you're solving for is how can you show this idea without cluttering the page or confusing folks. For example, I often use (& re-use) an overview diagram and zoom into "phase 2" or "phase 3" on the lower parts of the “page real estate”. The art to presenting data is keeping it as clear + simple as possible - nobody cares how deep the analysis is if its unclear and confuses everyone.


After these three steps (and only after these steps), you can now start to look at different charts, graphs, colours. This is the easy stuff – trust me. Your analysis of the first 3 points will typically point you in a good direction (ie. should this be a table or chart, how detailed/specific should I make this process diagram etc..)


Feel free to DM me btw - happy to help

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It’s way easier if you have someone outline a tactical plan to get started. A YouTube named Ken Jee helped me a lot in this regard. Start by learning SQL, basic Python (pandas,numpy, matplotlib), and some understanding of the statistical math for regressions, segmentations, and then practice your skills with synthetic datasets in Kaggle. Kaggle also has great, hands-on, microcourses to get you dangerous enough with those skills. Good luck!

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Learn sql and data visualization tools. Python is good to know but heavy knowledge of it is not a requirement. Also, identify opportunities on your current team to implement some of these skills. That’ll give you some actual real world experience.

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AM1 - seems more like the scope of a ML engineer. Do the data analysts do this on your team?

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