Wow! You just helped crack a puzzle. Been battling with with not seeing Trend line and Forecast line on Line chart and the statement "If you don't have time series based data, you won't be able to find it on Analytics" That's it. I was using Period data like week1, week2 etc. The minute i used my date data, it came out like magic. Thank you so much
Glad that worked for you. I started creating these videos over 2 years ago to make data science and analytics available to everyone. I try my best to make it easy to understand and use real business use cases in every video. I am glad you liked this video on forecasting in Power BI. Please visit my video channel and you will see hundreds of other similarly great tutorials and walk throughs in everything from Power BI to R to Alteryx and more. As a data scientist for a Fortune Global 200 company I and my team use these same processes everyday to analyze and visualize data for our executives. Thanks again for watching and please share so that others may benefit. :)
@@techknowhow4802 Wow! David! I am hooked already. Love what you do 'cos that is what i do also. As a Data Analyst for a FMCG in Nigeria i find it logical to follow you as a Mentor. Take me as a mentee . Smiles. Cheers!
That its awesome, I have been looking for this for days. please how do you create the week column and link it to the date. do you have a video on that?
Thank you. I am working on both sentiment analysis and affinity analysis projects right now and will have videos for each of these up in the next few weeks. Any other great ideas of processes you would like to see?
Power BI does not yield a table of forecasted values. Your best bet is to use the code from the python or R videos I have on stock price forecasting. I just posted a great one on this with Bitcoin data in python. 😀
@@techknowhow4802 thanks mate! I have been scratching my head how i can display the forecasted values as oppose to them hovering my graph but this is really good, it gives me good idea how i can execute this on my business unit. Cheers mate
Thanks for the video, very helpful. Do you know what specific mathematic method Power BI uses? Is it Holt winter's smoothing? If so it would mean that there is no reason to incorporate a python code on power BI to use that method.
Using the 100% stacked bar chart on PowerBI to understand the contribution in Sales (Value) of about 4 channels. Drilling down to Category and Product levels will generate % contribution of the total business. What measures can i adopt to get insight/% contribution 1) A category within the Brand as a whole and 2) The product within the Category as an umbrella and not wrt to the Total Business. I hope this makes sense. Thank you
Good question. I have run into this before. It can be due to several reasons. If the data is too big, If there are missing values, and if the data is too variable - not easy to forecast. This is a default function and it is not meant to work with arduous, large or unclean data. For those you might need to look at some of the other videos on my channel that use arima models or LSTM (both in R and python).
The high and low values for a range. So, in the grey area there is a top value and a bottom value based upon the confidence interval values selected. So, for instance, the upper vale could be 100 and the lower value, 50 and the are in between is shaded grey and if you selected a 95% confidence interval then there is a 95% chance that your forecast data will fall inside the high and low.
Exponential smoothing. Power BI has a blog where it explains the methodology behind this along with the latest updates and more. Just Google Power BI blog and the official one will be in the top few search results. :)
Wow! You just helped crack a puzzle. Been battling with with not seeing Trend line and Forecast line on Line chart and the statement "If you don't have time series based data, you won't be able to find it on Analytics" That's it. I was using Period data like week1, week2 etc. The minute i used my date data, it came out like magic. Thank you so much
Glad that worked for you. I started creating these videos over 2 years ago to make data science and analytics available to everyone. I try my best to make it easy to understand and use real business use cases in every video. I am glad you liked this video on forecasting in Power BI. Please visit my video channel and you will see hundreds of other similarly great tutorials and walk throughs in everything from Power BI to R to Alteryx and more. As a data scientist for a Fortune Global 200 company I and my team use these same processes everyday to analyze and visualize data for our executives. Thanks again for watching and please share so that others may benefit. :)
@@techknowhow4802 Wow! David! I am hooked already. Love what you do 'cos that is what i do also. As a Data Analyst for a FMCG in Nigeria i find it logical to follow you as a Mentor. Take me as a mentee . Smiles. Cheers!
Great video! This is very easy to understand and follow. I will be adding this to my dashboards! Thanks
That its awesome, I have been looking for this for days. please how do you create the week column and link it to the date. do you have a video on that?
Keep them coming!
Thank you. I am working on both sentiment analysis and affinity analysis projects right now and will have videos for each of these up in the next few weeks. Any other great ideas of processes you would like to see?
This is awesome but how do i display forecasted values?
I dont see any options to display data
Power BI does not yield a table of forecasted values. Your best bet is to use the code from the python or R videos I have on stock price forecasting. I just posted a great one on this with Bitcoin data in python. 😀
@@techknowhow4802 thanks mate!
I have been scratching my head how i can display the forecasted values as oppose to them hovering my graph but this is really good, it gives me good idea how i can execute this on my business unit. Cheers mate
Thanks for the video, very helpful.
Do you know what specific mathematic method Power BI uses? Is it Holt winter's smoothing?
If so it would mean that there is no reason to incorporate a python code on power BI to use that method.
Using the 100% stacked bar chart on PowerBI to understand the contribution in Sales (Value) of about 4 channels. Drilling down to Category and Product levels will generate % contribution of the total business. What measures can i adopt to get insight/% contribution 1) A category within the Brand as a whole and 2) The product within the Category as an umbrella and not wrt to the Total Business.
I hope this makes sense. Thank you
Hey do you know why the forecast function is not available after i put in legend?
Good question. I have run into this before. It can be due to several reasons. If the data is too big, If there are missing values, and if the data is too variable - not easy to forecast. This is a default function and it is not meant to work with arduous, large or unclean data. For those you might need to look at some of the other videos on my channel that use arima models or LSTM (both in R and python).
do you know how to extract the forecasted table from powerBI to output in excel i.e. the values PowerBI forecasts?
Hello sir ,can i ask for dataset?
Did someone know why i didnt have forecast written in the third gadget when i mark line chart ?
Power Bi doesn't see the data as time series based? That is most likely the reason. Look at your data.
@@techknowhow4802 Yeah thank u! I made it 🙏
What is upper and lower bounds
The high and low values for a range. So, in the grey area there is a top value and a bottom value based upon the confidence interval values selected. So, for instance, the upper vale could be 100 and the lower value, 50 and the are in between is shaded grey and if you selected a 95% confidence interval then there is a 95% chance that your forecast data will fall inside the high and low.
@@techknowhow4802 On what basis this values will be determined
does anyone know what forecasting method it uses? exponential?
Exponential smoothing. Power BI has a blog where it explains the methodology behind this along with the latest updates and more. Just Google Power BI blog and the official one will be in the top few search results. :)