How To Become A GREAT Data Analyst - 5 Skills And Best Practices For Data Analysts

Published 2022-02-03
Data analysis is abstract. It is not math (although math is involved) and it is not English or accounting. It requires a hands-on approach to truly understand the pitfalls good analysts will run into.

Yet, most students have not dealt with vague parameters and large data sets by the time they get their first job, which is a shame! Many students haven’t even heard of a data warehouse and this is where most of the data, which helps managers make critical decisions, resides.

In the modern business world, data analysis is not limited to data scientists. It is also key for analysts, system engineers, financial teams, PR, HR, marketing, and so on.


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0:00 Intro
2:15 Set Up A Clear Data Analytics Process
4:56 Don't Bury The Lede
6:39 Data Analytics Peer Review
8:51 Triple Check Your Data
11:46 Know When To Stop Your Analysis
13:05 Recap

Tags: Data engineering projects, Data engineer project ideas, data project sources, data analytics project sources, data project portfolio

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About me:
I have spent my career focused on all forms of data. I have focused on developing algorithms to detect fraud, reduce patient readmission and redesign insurance provider policy to help reduce the overall cost of healthcare. I have also helped develop analytics for marketing and IT operations in order to optimize limited resources such as employees and budget. I privately consult on data science and engineering problems both solo as well as with a company called Acheron Analytics. I have experience both working hands-on with technical problems as well as helping leadership teams develop strategies to maximize their data.

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All Comments (15)
  • @gilbi
    I always tell my analysts to: 1. Check that they don’t fall down the rabbit hole by reviewing the business question and the hypothesis several times mid-analysis. 2. When finalizing the analysis, start with one simple concise sentence of the bottom line of your analysis (a tl;dr) then build your (data) case. 3. Use charts that support your analysis and, for the love of God, highlight the important data point in them to maintain focus. 4. Know your audience, use the terms they are familiar with and don’t use any made-up abbreviations. 5. Honestly, outside of your team, no one really cares what model you use or how accomplished your technical skills are as long as you are confident with your analysis results
  • @naheliegend5222
    Theoretically I am a Data Analyst in my company, practically I have to write a lot of code, build models, ETL pipelines and so on. Be aware of , especially in smaller companies, that you have to be a Data Analyst, Data Scientist and Data Engineer at once. They just call it Data Analyst, because so they can pay you less.
  • @DataProfessor
    Great insights for becoming a data analyst. Certainly agreed with you about having a clear scope and objectives of an analysis so as to mitigate against a prolong or run-on report that may arise when the scope/objectives are unclear.
  • @subtleteez5619
    You mentioned it once, but personally I feel it is the single most important aspect of all the data roles in a company: The Stakeholder. The great analyst will recognize immediately that the stakeholder is not the IT manager, but the business champion that has sponsored the effort and will align their insights to speak directly to the stakeholder. As for data quality, IMHO, if they ever actually figure out how to clean it up without manual effort, we will all be out of a job ;) Been that way all of my career (30+yrs) and for every step closer to clean, the messier it gets.
  • Very useful video for Data analysts, agree with you completely on having a clear scope and objectives for analysis of data 👍🙂
  • @lukeivanov2327
    Just because job postings are requiring more technical skills does not mean that new hires will have those skills. A lot of hiring managers don’t know how to write a proper job description and overestimate what a role should have so don’t take job postings seriously.
  • @LukeBarousse
    But what if I just want to be an AVERAGE analyst?!? 🤷🏼‍♂jk Great vid as always Ben; Love the support for data analysts!
  • @Thahid
    Thanks I wished more people made videos of how to improve the day-to-day work processes. It really makes a difference over time.
  • @ryanhatch4012
    As an analyst being given a lot of responsibility early, I found this video at the right time. A process and goal to an analysis/project is definitely necessary. Only realize you should be more concise once you have to explain your findings in a meeting with people unfamiliar with the project lol