1. I use Python first web scrapping the database with the help of AI assistant. 2. Once I get the csv files of my database I start next with Spreadsheet to create, clean, organize the tables. 3. I jump to SQL for the sake of learning how to query (here I should be focusing more now that I watch Loreeenzo's video). 4. I post & publish my datasets on Kaggle playing with some coding their helps learn more about the data I collected. 5. Finally on Tableau, I try to create some worksheet vizzes as best as I can but I've noticed that at this level most of the time I have to go back to the 1st or 2nd step to update or even add new missing data so I can complete the visualization I'm working on. 6. Once I'm more comfortable I will rework the same projects on Power BI ...
I started the same mate, but the more and more DA I do the more bored I get and I am slowly turning to SWE, so I don't know. I also acquired masters in computing and digital technologies so that might has to do with it.
However, once you can use Power Query and Power Pivot, you’re ready to work with Power BI, which is definitely worth learning. In finance, we don’t often work extensively with SQL or databases. But if the monthly expense data from SAP amounts to about 1 million rows, what tools can we use within a typical finance environment? The answer is Excel and Power Query, as they can handle millions of rows, which is incredibly helpful for managing such data.
I am currently working on a personal project - MS Excel. If it goes well, will try and see if I can replicate it with SQL and Tableau too. Not sure about the rest, but I can say this about Excel, that knowing advance features and formulas in Excel does change the way we look at data. It is indeed difficult for a non technical person to switch to a technical mindset. I guess I will have to be patient and take it slow for the transition to be impactful.
Great video!! I just finished the google certificate and as well as my first portfolio project but i still have alot to learn. Between IBM, Meta, DataCamp or anything else, what course would you recommend me to take next ?
I generally agree but please excel is usually the starting point because its used by billions of people around the planet. DO NOT skip the basics of Power Query [optionally basic M Language features like when merging excel or csv files] and Power Pivot [Including basic DAX] and basic data modelling [Star Schema]. You can easily move on to POWER BI [or Tableau]. SQL and basic data modelling including basic database building and modelling must then be your next step. This will cater for up to 90%. Good to consider certification in SQL and BI tools to attract the attention of employers and credibility but a first degree in anything is usually a good starting point but on the side lines make sure to learn the basic data analytics skills mentioned above as you study for your degree. If you can squeeze in basic statstics / research in your degree the better.... NOW if you can expand on your Python / R + Statistics knowledge as an advanced step. Consider GIS also.. Then you will be good to go. Lastly if you want to work in international organisations, a Masters is becoming a minimum requirement..
thanks for the detailed comment, agree on all apart from using Power features in Excel - I simply don't see that in the workplace unless the org is really beginner when it comes to data
It depends on how much time you put learning each of the platforms. If you're more familiar with Microsoft products Power BI may be easier to learn & use. Tableau is more advanced thou.
POWER BI is easier and has more powerful and complete learning resources for a beginner. Good to know bot if you can but start with one.. Just like Python / R
@@loresowhat Well mate, alex the analyst has included Azure and AWS for analysts in his bootcamp. The more and more job postings require Azure or AWS. So I think it is worth learning one, if not both in the future. ua-cam.com/video/wQQR60KtnFY/v-deo.html
@alexgeld7173 I worked for AWS for more than 2 years and I can assure you that the main interaction that data analysts will have with cloud platforms is simply connecting to their database which in the case of AWS is called redshift. apart from that I don’t see any use case for data analysts to know a cloud platform unless for pure curiosity and I’m saying this as Im in the data industry for more than six years. also consider that Alex the analyst as far as I know has worked on projects related to migrations to the cloud which have nothing to do with data analytics
Sorry to say but even if you do these and apply for job , the chances of even getting the resume viewed is 0.5% - from your well wisher and experienced guy
1. I use Python first web scrapping the database with the help of AI assistant.
2. Once I get the csv files of my database I start next with Spreadsheet to create, clean, organize the tables.
3. I jump to SQL for the sake of learning how to query (here I should be focusing more now that I watch Loreeenzo's video).
4. I post & publish my datasets on Kaggle playing with some coding their helps learn more about the data I collected.
5. Finally on Tableau, I try to create some worksheet vizzes as best as I can but I've noticed that at this level most of the time I have to go back to the 1st or 2nd step to update or even add new missing data so I can complete the visualization I'm working on.
6. Once I'm more comfortable I will rework the same projects on Power BI ...
I started the same mate, but the more and more DA I do the more bored I get and I am slowly turning to SWE, so I don't know. I also acquired masters in computing and digital technologies so that might has to do with it.
Hey buddy can we connect ?? I have some queries!
to be honest one of the best mentor keep going
wow thanks a lot!!!!!!
I now have a clarity on how I will use whatever I learned now.
Thank You, the video was really good and informative!
Glad it was helpful and thanks for the visit 🙂
However, once you can use Power Query and Power Pivot, you’re ready to work with Power BI, which is definitely worth learning. In finance, we don’t often work extensively with SQL or databases. But if the monthly expense data from SAP amounts to about 1 million rows, what tools can we use within a typical finance environment? The answer is Excel and Power Query, as they can handle millions of rows, which is incredibly helpful for managing such data.
Where's Is SQL used.... If not finance?
@@lavatr8322 other departments like bi developer, data analyst, data scientist etc
I am currently working on a personal project - MS Excel. If it goes well, will try and see if I can replicate it with SQL and Tableau too. Not sure about the rest, but I can say this about Excel, that knowing advance features and formulas in Excel does change the way we look at data.
It is indeed difficult for a non technical person to switch to a technical mindset. I guess I will have to be patient and take it slow for the transition to be impactful.
Hey can we connect, I have some queries!!
@sadiqahmed1529 Hi. What kind of query do you have?
Very straightforward
thanks for the visit and comment
Great video!
Had no idea you could copy a dashboard and swap out the data in Tableau.
Have you any videos on this?
Not yet but will definitely add it to my video list 🙂
Thank you for this
thanks to you for the visit!
really helpful sir
Glad to hear and thanks for the visit!
Great video!! I just finished the google certificate and as well as my first portfolio project but i still have alot to learn. Between IBM, Meta, DataCamp or anything else, what course would you recommend me to take next ?
good progress!! I would definitely consider my Data Analytics Mastercourse if you need one programme that covers it all
I generally agree but please excel is usually the starting point because its used by billions of people around the planet. DO NOT skip the basics of Power Query [optionally basic M Language features like when merging excel or csv files] and Power Pivot [Including basic DAX] and basic data modelling [Star Schema]. You can easily move on to POWER BI [or Tableau]. SQL and basic data modelling including basic database building and modelling must then be your next step. This will cater for up to 90%. Good to consider certification in SQL and BI tools to attract the attention of employers and credibility but a first degree in anything is usually a good starting point but on the side lines make sure to learn the basic data analytics skills mentioned above as you study for your degree. If you can squeeze in basic statstics / research in your degree the better.... NOW if you can expand on your Python / R + Statistics knowledge as an advanced step. Consider GIS also.. Then you will be good to go. Lastly if you want to work in international organisations, a Masters is becoming a minimum requirement..
in short are you telling to focus on
Power query
power pivot
dax? in excel
thanks for the detailed comment, agree on all apart from using Power features in Excel - I simply don't see that in the workplace unless the org is really beginner when it comes to data
GIS? How that?
Is using Tableau easier than using power bi?
I think, it's similar platforms
It depends on how much time you put learning each of the platforms. If you're more familiar with Microsoft products Power BI may be easier to learn & use. Tableau is more advanced thou.
Agree with the other comments, same as PowerBI 👍
POWER BI is easier and has more powerful and complete learning resources for a beginner. Good to know bot if you can but start with one.. Just like Python / R
why prefer tableau over power bi?
it's just my personal preference but you can definitely go for PowerBI instead
power bi or tableau which tool we can learn
Data Analysis Methodologies Overview is always neglected, that's why most people never feel like they are ready.
How to approach a project
How much statistics
Etc... I know how to use the technologies, so what do I do ?
Btw, good video
Totally agree with your comments and thanks for the visit 🙂
what if i prefer power bi over tableau?
no worries that is not a problem. tableau and powerbi are both very good and popular
❤❤❤
🙂
Forgot to Mention Cloud Azure or AWS.
Not needed for a data analyst 😉
@@loresowhat Well mate, alex the analyst has included Azure and AWS for analysts in his bootcamp. The more and more job postings require Azure or AWS. So I think it is worth learning one, if not both in the future.
ua-cam.com/video/wQQR60KtnFY/v-deo.html
@alexgeld7173 I worked for AWS for more than 2 years and I can assure you that the main interaction that data analysts will have with cloud platforms is simply connecting to their database which in the case of AWS is called redshift. apart from that I don’t see any use case for data analysts to know a cloud platform unless for pure curiosity and I’m saying this as Im in the data industry for more than six years. also consider that Alex the analyst as far as I know has worked on projects related to migrations to the cloud which have nothing to do with data analytics
How Much Power BI is Enough ?
Sorry to say but even if you do these and apply for job , the chances of even getting the resume viewed is 0.5% - from your well wisher and experienced guy
Love the accuracy of that 0.5% 🤣
Jesus loves you brother
Thanks for the visit 🙂
Is anyone willing to join me in studying Python?
Can I
join our Data Lab Community!! we are waiting for you!
join our Data Lab Community!!
Please can I