Hi Guys,
It’s been excited learning Power BI from EDNA as a beginner but slightly as am progressing I need to add some more skills like Python, R language and SQL to make myself prepare to be a Data Analyst.
Is there any roadmap to learn all these skills or only Power BI will alone help me to be a Data Analyst ?
Please guide me guys…am basically a Excel user I know nothing about programming language except Power BI which am learning from EDNA…
Great question. I’m sure others will weigh in here as well, but my $0.02 is that while Power BI is an exception tool that serves as my analytical “home base”, additional skills are needed to maximize its power.
SQL is a great skill to have, since as we’ve discussed in many forum posts, videos, etc. data prep should typically be done as far “upstream” as possible. @Greg is one of our resident SQL experts here, and I would invite him to comment further on the value of combining SQL and PBI expertise.
R is a must in my view for really rigorous data analysis. R and Power BI work beautifully together, and knowing R gives you access to 20,000+ custom analyses via, open source “packages” that you can load into R and access in PBI to perform almost any complex analysis imaginable. In addition, R provides you access to an enormous range of visualization options that you can pull into your PBI reports dynamically.
I don’t know much about Python, but invite eDNA Experts @bradsmith, @AntrikshSharma and @Greg to comment on its value with regard to PBI.
I would also work on adding geospatial skills to your arsenal. Spatial analysis provides deep insight as well as compelling visualizations to a wide range of data analyses.
In terms of a learning roadmap for many of these skills, you’re in luck. These topics are the focus of many of the new Enterprise DNA in-depth portal courses that we are rolling out every month in 2021. You can see the plan for the availability of these courses here:
I hope this is helpful.
Hi @Dharma. Admittedly I’m biased, but of the 3 I’d learn SQL first, especially if you’ll be involved in the data preparation. If you’ll not (or very rarely) be involved in data prep, and will be charged with extracting detailed insights from (especially large) datasets, then R or Python would likely be more appropriate (I know Python a bit, and R not at all, but understand that R is quite good, so I’d start there). All are good, and so I can only give the standard consultant’s answer, “it depends”.
Greg
(P.S.: knowing SQL has made my Power BI journey easier, as my data is most often clean (or can be cleaned-up) in the source, and hence it doesn’t need extensive [or any] transformations once in Power Query.)
@Dharma All great points above, if you are a non - programmer like me then I would suggest that you start with VBA + SQL and leave Python/R for future, VBA is easy and its English like constructs make it easier to read and understand, it will give you a flavour of programming. Python has Pandas with which you can do anything that can be done in Power Query but is it worth learning it over M if you take into consideration the learning curve and the ease of use with Power BI? I had say no.
There is nothing that you can’t do in Excel that you can do in Power BI. Keep maintaining your grip on Excel. It is and will always be the number 1 tool for analysts, I am yet to find someone who disagrees. Also, you can run both Python and JavaScript in it!
I can’t stress enough on how much participating on forums helps in growing and making your portfolio, forum participation shows that you actually care about the field, every time I look at the questions and answers on forums it feels like someone is literally stretching my brain. Also, it helps in making some great connections!! Even if you end up providing a solution that doesn’t work at all, don’t worry! people like @BrianJ are here to motivate and guide you.
But also, remember Power BI has an array of things to learn, so you would end up spending all your time in learning it. Divide your time equally between DAX and Power Query, preferably more on Power Query. And once you are comfortable with SQL then SQL over Power Query.
I am just crazy about DAX Language that’s why I spend 90% time on it. I wouldn’t advise others to that, haha!! 
Also note that organizations look for SSAS/AAS as well so you will have to learn it too.
Thank you all for your answers guys am really proud to be part of this community
Kindly share me any platform or source where I can learn SQL and SSAS/AAS from a beginner to advanced level…
@Dharma One of the key skills of an analyst is scavenging, so I will leave it up to you to find the resources. 
I couldn’t agree more with @AntrikshSharma. Besides, I began my SQL journey longer ago than I’d care to admit, so I’m completely unfamiliar with relevant learning resources.
Greg
I agree wholeheartedly with @AntrikshSharma and @Greg’s statements. I started with VBA and it gave me a great understanding of how programming languages work. I moved into R right after and I wish I had built a stronger base in SQL first because SQL’s greatest strength is in the backend in the data storage side of analytics and the relationships different data have between each other. No matter what type of analytics you do you will eventually need to have a base understanding of SQL. R and Python are two extremely powerful programming languages and each have their strengths in Power BI but there’s really no system out there that doesn’t either interact with or is built on some version of SQL. If you’re interested in learning R or Python, my post on Machine Learning in Power BI has some great resources and in the comments section there’s a few of us discuss some of the pros and cons of each language (Power BI & Machine Learning - Part 1: The Basics - #16 by bradsmith)
Hi @Dharma
everyone contributing to this thread makes great points.
I’ve found myself a bit overwhelmed at times with the amount of things I feel I need to learn to improve myself. Power BI, DAX, Data Viz, Data Modelling, Power Query, M Code, SQL, Power Apps, Power Automate, Power Virtual Agent, should I learn R and/or Python, Tableau (boooooo 
)
I ended up spreading myself too thinly, trying to learn too many things at one time, even though I’ve been using Power BI for a bit over 2 year now, I’m not where I’d like to be in terms of my knowledge/expertise.
So my main focus is on Power BI (Visualisation, Data Modelling, Power Query, M Code) with focus on SQL to a lesser extent. I’ll confess I’m doing about 5-10 minutes a day on R too but not trying to overload myself.
James Clear’s book, Atomic Habits, talks about trying to improve yourself by 1% everyday, so I set aside time everyday to learn on this Forum or the EDNA Training Hub. I’d love to spend hours every day learning but it’s just not possible, or always advisable, so I’m making sure I spend quality time each day and making learning a habit.
Lot of great points and wisdom in your post. It absolutely does feel overwhelming at times, and once you start feeling competent, BOOM! another new monthly update with a bunch more new stuff to learn (which is both one of the reasons I love Power BI, and also why at times it feels like being on a gerbil wheel…)
I think your focus on the four Power BI pillars primarily is spot-on. Even with “just that”, with a solid foundation there, you will be far ahead of most of the world, who are still manually cranking out Excel reports and analyses.
We should have a side conversation about your R study. How you optimally study and learn R as a PBI user is VERY different IMO than how you do so as a standalone R user, since the vast majority of the data cleaning/prep in R can be done in PQ, which then calls the analytical and/or visualization functions in R. I’ve actually never seen an R course designed around PBI users, which is why I decided to develop one for the Enterprise DNA Portal. Just want to make sure you’re not spending valuable and limited learning/practice time on stuff you don’t need to know.
The 1% concept is gold. When I was younger I used to powerlift, and my coach was focused on a training regimine that added 1-2 pounds to the bar each week. As he used to say “doesn’t sound like much, but in five years that’s 250-300 pounds added to each lift, and in ten years that’s the ability to lift a school bus”.
Hey @BrianJ, thanks for the kind response. I’ve already felt the benefit of focusing on the Power BI pillars, had a couple of nice moments this week when I’ve managed to utilise some nice M code that I picked up a few weeks ago which kinda re-inforced my approach.
Would be happy to have a side conversation about R, I’ve been using the content at an online provider that sounds like Bandcamp 
. Awesome to hear about the R/Power BI course you are developing, the upcoming content from EDNA has me salivating.
Hello @Dharma, you can check out the Enterprise DNA Learning Map. This is our recommended sequence guide for our courses and learning resources.
We’ve recently launched the Enterprise DNA Forum User Experience Survey, please feel free to answer it and give your insights on how we can further improve the Support forum. Thanks!
Hi @Dharma, did the responses help you solve your query? If not, how far did you get and what kind of help you need further? If yes, kindly mark as solution the answer that solved your query. Thanks!
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To create a roadmap for learning those abilities, you can start by prioritizing the areas wherein you experience the most want for development. Since you are already acquainted with Power BI, you would possibly want to focus on mastering Python, R, and SQL in parallel or sequentially, depending on your preferences and learning fashion.
For Python and R language, there are many on-line training publications available that cater to beginners and provide a based curriculum that will help you study those programming languages from scratch. Platforms like Udemy, Edureka, and edX provide courses on Python and R for information analysis, which cowl topics such as facts manipulation, visualization, and statistical analysis using those languages.
Similarly, for SQL, you may locate online courses that educate database querying and management. Websites like Codecademy, Udemy, and Coursera provide SQL publications for novices, wherein you can study SQL syntax, database design, and question optimization.
As you development through these guides, you can also complement your learning with palms-on projects and actual-international datasets to apply your abilties in practical scenarios. Building a portfolio of tasks showcasing your skillability in Power BI, Python, R, and SQL will demonstrate your competencies to capability employers and clients as a well-rounded Data Analyst.
Ultimately, combining your know-how of Power BI with skillability in Python, R, and SQL will allow you to address a much broader range of facts analysis responsibilities and make greater knowledgeable decisions based totally on statistics insights. It’s important to pace yourself and prioritize non-stop mastering to achieve your desires as a Data Analyst.