Removing filters from drill paths

Hello,

 

Is there a way to remove filters from drill paths?

 

For example, if I have a stacked bar by month and by business unit and I want to add a drill path that filters ONLY by business unit and not by business unit AND month?

 

Thanks

Comments

  • Hi all,

     

    Can anybody help @wwood out?

    Thanks!

  • @wwood I tried to find a way in which to do this exact same issue.  I opted to instead create a second card and link it as a "related card"  

     

    I left the drill down so that they have the option to see the data using that filter, but keep in mind if they use the drill they will no longer see the related card unless you decide to add it into that path as well.

     

     

  • @wwood, did VinceGhost's reply help you out?

  • Yes, you can remove a filter. I do this all the time. 

     

    When you click a data point to drill down, you'll see the "filter" automatically applied as a blue box to the top left of the chart. If you click the x on the filter box you can remove that filter. I find this particularly useful if I want to see a larger time frame and the drill path filtered me to a single week or month.

  • I will be very interesting that I can create one card 2level without filter of card 1Level. It´s very useful

    Is possible this option?

  • I am frankly amazed that this is not a feature yet. 

     

    You offer combo charts. I use combo charts to compare things like Forecast vs. Actual. If I want to drill into a particular month, one of the two Forecast or Actual will be filtered out. This is a horrible user experience and makes me and this product look like **bleep** in front of executives.

     

     

    CFO: "Why does this only show Forecast when I drill in?"

    Me: "Oh its just a limitation of Domo! EVERY TIME you drill in, youll need to remove the filter :D"

  • Same problem for me.  Nobody is going to know they have to remove a filter unless they are trained, and it's annoying to have to do so every time there's a drill down.

  • In you example that is actually the whole point of drilling down to a filtered view. if your users wish to look at a specific month or any time period then they can use the date grain drop down next to the title of the card. now if what they want is to filter the card for an specific let say department, without getting rid off one of the series, then they can use the card filter or analyzer. even page filters. I am sorry but what you are describing is just a filter action on a card . not a drill down to a deeper level.  I think Domo give us all plenty of ways to accomplish what we and our users want , even more than any other platform out there.

  • Not true.  In my example, the top-level chart plots each department as a line.  The drill down chart plots individual staff members as a line.  Two different groupings.

     

    What I want is that the user can click on the department line and then get a chart that shows them the lines of the staff within that department.

  • I agree with the main body. What Domo needs is to have the ability to expand data instead of drill (filter) the data. The thing I want to know is why there is no action towards this. It seems like there is a large enough user group here to get traction to this basic function.

     

    @DaniBoy What would it take to get this actually implemented at Domo? I know the idea exchange is a possbility, but I feel like that is just a location Domo likes to send users to make them think their idea is actually considered. @Wolfram 

  • Wolfram
    Wolfram ⚪️

    Hello, three years later!

     

    I am super disappointed that this is still not a feature. After three years? I was designing a dashboard with the design dashboard feature, but it is totally unviable because I cannot control the drill path.

     

    See the image. Each line represents a group of people. I want users to be able to click a line and see the trends for all the individuals. But when you click the line, you only see results for a specific month.

     

    So now my users get to live with the typical dashboard experience, where they still have to deal with this terrible experience of removing a drilldown filter every **bleep** time 

  • Rather than drilling, you could set this card up on a dashboard and have the interaction apply a filter.  This way you could place another card below this one that would provide individual user trends.  When a user clicks on a group from the top card, it would filter the second card to only the users in that group.

  • Hi,

    I solved it a little differently. I created a new modified dataset from the original. As per the requriement in the first visualization i had to build the metrics using the last recordvalues in the dataset. But in the drill down second visualization, i wanted to build the metrics using entire time-line from the beginning of the table and not just a slice which happened to be the last record in my dataset.

     

    Solution :

    First Part :Was to join the original table with the subset of the table itself for the entire time period. By using ETL in DOMO, i added new columns where each column had duplicate values that i needed from the last record (as per the requirement for the first visualization).

     

    Seecond Part : To solve the problem of duplicate column values in the first visualiztion, in the visualization process, i made a new calculated field which was just an average of each column value (this was done for the new columns having duplicate values). This correction gave me the values to build metrics for the first visualization card and when i drilled down to build the second visualization, i still had the original data for the entire time period.

     

    To visualize further, In the spread sheet attached the original columns for the two visulaization were;

     

    dateregionmeanmedianlower_90upper_90lower_50

    upper_50

     

    After ETL process, here are the new duplicate columns for each row

    date_newmean_newmedian_newlower_90_newupper_90_newlower_50_newupper_50_new

     

    Here is the sample snapshot of State of Arkansas, where each row in orange is having the last value in the dataset (i.e. from the 3rd May for the state of Arkansas).

    dateregionmeanmedianlower_90upper_90lower_50upper_50mean_newmedian_newlower_90_newupper_90_newlower_50_newupper_50_new
    3/16/2020AK1.193525971.1481674680.8536104821.5633614050.9906870591.2553469910.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/17/2020AK1.185434411.146538410.8725466771.5234596140.9790340131.2245316980.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/18/2020AK1.1748803781.1410862040.8634529521.4948484391.0168220271.2468346410.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/19/2020AK1.1611297031.1360886960.8512678511.4419442580.9930824861.2050285490.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/20/2020AK1.1447880761.1213793790.8484513821.4060538040.9850505071.1777095310.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/21/2020AK1.1250664041.0949687020.8768863531.3888882940.9963491121.1685321150.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/22/2020AK1.1066525121.0848642120.8657334631.351354930.9734528121.1461650830.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/23/2020AK1.0903753431.0667381170.8363646831.3288591810.9545643511.1222008410.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/24/2020AK1.0712918561.0517877650.8495670151.3228674440.9358090831.104665270.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/25/2020AK1.0492042741.0363932090.8361155911.2860424850.9518331341.1074859040.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/26/2020AK1.0257286461.0169945590.8181847241.2694400290.9240915761.0701900690.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/27/2020AK1.0028724910.9994104240.7625201941.2098342340.9233072421.0699744470.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/28/2020AK0.9801641980.9838852450.7647662861.2061774050.9224073441.0660306940.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/29/2020AK0.9541660050.9625304920.7571442841.1651014330.9106994731.0506209060.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/30/2020AK0.926845380.940164720.6969610421.1300878960.8831802751.0160034390.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    3/31/2020AK0.9041003360.9216248310.6957935611.1255942340.8593154171.0014939590.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/1/2020AK0.8842004670.9056236140.6579508781.1105546570.8379228150.9871252380.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/2/2020AK0.8658255050.8881350980.6515656631.1228935810.8124335620.9661798260.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/3/2020AK0.8454489770.8707170890.5900428831.0882864330.8137180430.9815994320.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/4/2020AK0.8206127040.8544322880.5261568781.0603399490.8057577010.9812850460.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/5/2020AK0.7977530640.8420509530.4943793741.0502374080.7977232250.9838404520.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/6/2020AK0.7836659470.8244659590.5033818051.0644495820.7815992470.9751939150.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/7/2020AK0.7740907510.8167244870.4828056921.0693295290.7479563670.9490026760.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/8/2020AK0.7665329980.8140982060.4475374281.0480558450.7528128690.9552420150.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/9/2020AK0.752624850.7981304720.4555081811.0487957480.7206467360.9349160940.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/10/2020AK0.7414617260.7887785690.4091389791.0500001480.7472193930.9664636280.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/11/2020AK0.7351043560.7868806970.4059433031.065955080.7206449480.9389969030.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/12/2020AK0.7307648240.7809294480.4080402591.0559805170.7276961090.959755320.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/13/2020AK0.7247926380.7718442450.4052811681.0566789920.7004157130.9375009280.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/14/2020AK0.7210289950.7716833380.4068371681.0715300290.7296370560.9735279340.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/15/2020AK0.7190789860.7649275290.3853030881.0416015510.7099579350.955430790.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/16/2020AK0.7183292710.7663474380.411407821.0943136420.6958467930.9472194640.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/17/2020AK0.7254402210.7731051110.3405950351.0549274840.6850285290.9352999120.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/18/2020AK0.7299689660.7738642320.3910476221.119348510.6884482970.9458776550.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/19/2020AK0.7280657840.7753768120.3125958491.0779716650.6984664370.9702462150.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/20/2020AK0.736344250.7777341140.3240380681.1065830020.6851148640.9565266670.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/21/2020AK0.7342413290.7778509230.2918027361.1102437210.7003622780.9700068590.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/22/2020AK0.7361388320.7838397750.3106314841.1366106560.7259012121.009831970.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/23/2020AK0.7410973860.7827106520.2473773811.1074736490.7016639530.9862474740.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/24/2020AK0.7353860640.7866317710.2089670671.1153018020.686417750.9801831820.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/25/2020AK0.7324800160.7824870970.2212854011.1525521270.6431633630.948102360.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/26/2020AK0.7312528310.7864164940.19728921.1438557160.6417958260.9532637940.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/27/2020AK0.7296772310.7902734990.1868178021.1344288570.7164829171.0290124240.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/28/2020AK0.7263122650.7888504090.1818200351.1527728750.7118643671.0348027180.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/29/2020AK0.7284354510.7852549820.1674874561.1478148480.6889298891.0162179370.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    4/30/2020AK0.726008560.7836306620.1628647841.2158270260.6524300710.9940026570.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    5/1/2020AK0.7257925150.7818615930.1209149681.2048552650.6527450260.9991406570.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    5/2/2020AK0.7230635710.7875509140.1308296691.2655009330.5971713770.9542771030.7203129040.7744421930.1268694531.2925576970.6687097741.031813743
    5/3/2020AK0.7203129040.7744421930.1268694531.2925576970.6687097741.0318137430.7203129040.7744421930.1268694531.2925576970.6687097741.031813743

     

     

    In building out the first visualization metrics, i will use the orange columns, but (remember) you will have to average or min or max the duplicate column to get the actual value you need in the first visulaization.

    That way all the original columns for the entire time period will be available to you in the drill down path visualization without any filter to build the second visulaztion.

     

    If there are multiple visualizations that are needed to be build, then you will have to repeat the process of creating redundant orange colored columns with duplicated values to send the original dataset columns one step down in the drill path.

     

    Thanks

    Salman Ahmed

     

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