Sur d’autres sites (11184)

• What is Google Analytics data sampling and what’s so bad about it ?

  16 août 2019, par Joselyn Khor — Analytics Tips, Development
  What is Google Analytics data sampling, and what’s so bad about it ?

  Google (2019) explains what data sampling is :

  “In data analysis, sampling is the practice of analysing a subset of all data in order to uncover the meaningful information in the larger data set.”[1]

  This is basically saying instead of analysing all of the data, there’s a threshold on how much data is analysed and any data after that will be an assumption based on patterns.

  Google’s (2019) data sampling thresholds :

  Ad-hoc queries of your data are subject to the following general thresholds for sampling :
  [Google] Analytics Standard : 500k sessions at the property level for the date range you are using
  [Google] Analytics 360 : 100M sessions at the view level for the date range you are using (para. 3) [2]

  This threshold is limiting because your data in GA may become more inaccurate as the traffic to your website increases.

  Say you’re looking through all your traffic data from the last year and find you have 5 million page views. Only 500K of that 5 million is accurate ! The data for the remaining 4.5 million (90%) is an assumption based on the 500K sample size.

  This is a key weapon Google uses to sell to large businesses. In order to increase that threshold for more accurate reporting, upgrading to premium Google Analytics 360 for approximately US$150,000 per year seems to be the only choice.

  What’s so bad about data sampling ?

  It’s unfair to say sampled data is to be disregarded completely. There is a calculation ensuring it is representative and can allow you to get good enough insights. However, we don’t encourage it as we don’t just want “good enough” data. We want the actual facts.

  In a recent survey sent to Matomo customers, we found a large proportion of users switched from GA to Matomo due to the data sampling issue.

  The two reasons why data sampling isn’t preferable : 

  1. If the selected sample size is too small, you won’t get a good representative of all the data. 
  2. The bigger your website grows, the more inaccurate your reports will become.

  An example of why we don’t fully trust sampled data is, say you have an ecommerce store and see your GA revenue reports aren’t matching the actual sales data, due to data sampling. In GA you may be seeing revenue for the month as $1 million, instead of actual sales of $800K.

  The sampling here has caused an inaccuracy that could have negative financial implications. What you get in the GA report is an estimated dollar figure rather than the actual sales. Making decisions based on inaccurate data can be costly in this case. 

  Another disadvantage to sampled data is that you might be missing out on opportunities you would’ve noticed if you were given a view of the whole. E.g. not being able to see real patterns occurring due to the data already being predicted. 

  By not getting a chance to see things as they are and only being able to jump to the conclusions and assumptions made by GA is risky. The bigger your business grows, the less you can risk making business decisions based on assumptions that could be inaccurate. 

  If you feel you could be missing out on opportunities because your GA data is sampled data, get 100% accurately reported data. 

  The benefits of 100% accurate data

  Matomo doesn’t use data sampling on any of our products or plans. You get to see all of your data and not a sampled data set.

  Data quality is necessary for high impact decision-making. It’s hard to make strategic changes if you don’t have confidence that your data is reliable and accurate.

  Learn about how Matomo is a serious contender to Google Analytics 360. 

  Now you can import your Google Analytics data directly into your Matomo

  If you’re wanting to make the switch to Matomo but worried about losing all your historic Google Analytics data, you can now import this directly into your Matomo with the Google Analytics Importer tool.

  
  Take the challenge !

  Compare your Google Analytics data (sampled data) against your Matomo data, or if you don’t have Matomo data yet, sign up to our 30-day free trial and start tracking !

  References :

  [1 & 2] About data sampling. (2019). In Analytics Help About data sampling. Retrieved August 14, 2019, from https://support.google.com/analytics/answer/2637192

• Merge multi channel audio buffers into one CMSampleBuffer

  26 avril 2020, par Darkwonder

  I am using FFmpeg to access an RTSP stream in my macOS app.

  



  REACHED GOALS : I have created a tone generator which creates single channel audio and returns a CMSampleBuffer. The tone generator is used to test my audio pipeline when the video's fps and audio sample rates are changed.

  



  GOAL : The goal is to merge multi-channel audio buffers into a single CMSampleBuffer.

  



  Audio data lifecyle :

  



  AVCodecContext* audioContext = self.rtspStreamProvider.audioCodecContext;&#xA;        if (!audioContext) { return; }&#xA;&#xA;        // Getting audio settings from FFmpegs audio context (AVCodecContext).&#xA;        int samplesPerChannel = audioContext->frame_size;&#xA;        int frameNumber = audioContext->frame_number;&#xA;        int sampleRate = audioContext->sample_rate;&#xA;        int fps = [self.rtspStreamProvider fps];&#xA;&#xA;        int calculatedSampleRate = sampleRate / fps;&#xA;&#xA;        // NSLog(@"\nSamples per channel = %i, frames = %i.\nSample rate = %i, fps = %i.\ncalculatedSampleRate = %i.", samplesPerChannel, frameNumber, sampleRate, fps, calculatedSampleRate);&#xA;&#xA;        // Decoding the audio data from a encoded AVPacket into a AVFrame.&#xA;        AVFrame* audioFrame = [self.rtspStreamProvider readDecodedAudioFrame];&#xA;        if (!audioFrame) { return; }&#xA;&#xA;        // Extracting my audio buffers from FFmpegs AVFrame.&#xA;        uint8_t* leftChannelAudioBufRef = audioFrame->data[0];&#xA;        uint8_t* rightChannelAudioBufRef = audioFrame->data[1];&#xA;&#xA;        // Creating the CMSampleBuffer with audio data.&#xA;        CMSampleBufferRef leftSampleBuffer = [CMSampleBufferFactory createAudioSampleBufferUsingData:leftChannelAudioBufRef channelCount:1 framesCount:samplesPerChannel sampleRate:sampleRate];&#xA;//      CMSampleBufferRef rightSampleBuffer = [CMSampleBufferFactory createAudioSampleBufferUsingData:packet->data[1] channelCount:1 framesCount:samplesPerChannel sampleRate:sampleRate];&#xA;&#xA;        if (!leftSampleBuffer) { return; }&#xA;        if (!self.audioQueue) { return; }&#xA;        if (!self.audioDelegates) { return; }&#xA;&#xA;        // All audio consumers will receive audio samples via delegation. &#xA;        dispatch_sync(self.audioQueue, ^{&#xA;            NSHashTable *audioDelegates = self.audioDelegates;&#xA;            for (id<audiodataproviderdelegate> audioDelegate in audioDelegates)&#xA;            {&#xA;                [audioDelegate provider:self didOutputAudioSampleBuffer:leftSampleBuffer];&#xA;                // [audioDelegate provider:self didOutputAudioSampleBuffer:rightSampleBuffer];&#xA;            }&#xA;        });&#xA;</audiodataproviderdelegate>

  



  CMSampleBuffer containing audio data creation :

  



  import Foundation&#xA;import CoreMedia&#xA;&#xA;@objc class CMSampleBufferFactory: NSObject&#xA;{&#xA;&#xA;    @objc static func createAudioSampleBufferUsing(data: UnsafeMutablePointer<uint8> ,&#xA;                                             channelCount: UInt32,&#xA;                                             framesCount: CMItemCount,&#xA;                                             sampleRate: Double) -> CMSampleBuffer? {&#xA;&#xA;        /* Prepare for sample Buffer creation */&#xA;        var sampleBuffer: CMSampleBuffer! = nil&#xA;        var osStatus: OSStatus = -1&#xA;        var audioFormatDescription: CMFormatDescription! = nil&#xA;&#xA;        var absd: AudioStreamBasicDescription! = nil&#xA;        let sampleDuration = CMTimeMake(value: 1, timescale: Int32(sampleRate))&#xA;        let presentationTimeStamp = CMTimeMake(value: 0, timescale: Int32(sampleRate))&#xA;&#xA;        // NOTE: Change bytesPerFrame if you change the block buffer value types. Currently we are using double.&#xA;        let bytesPerFrame: UInt32 = UInt32(MemoryLayout<float32>.size) * channelCount&#xA;        let memoryBlockByteLength = framesCount * Int(bytesPerFrame)&#xA;&#xA;//      var acl = AudioChannelLayout()&#xA;//      acl.mChannelLayoutTag = kAudioChannelLayoutTag_Stereo&#xA;&#xA;        /* Sample Buffer Block buffer creation */&#xA;        var blockBuffer: CMBlockBuffer?&#xA;&#xA;        osStatus = CMBlockBufferCreateWithMemoryBlock(&#xA;            allocator: kCFAllocatorDefault,&#xA;            memoryBlock: nil,&#xA;            blockLength: memoryBlockByteLength,&#xA;            blockAllocator: nil,&#xA;            customBlockSource: nil,&#xA;            offsetToData: 0,&#xA;            dataLength: memoryBlockByteLength,&#xA;            flags: 0,&#xA;            blockBufferOut: &amp;blockBuffer&#xA;        )&#xA;&#xA;        assert(osStatus == kCMBlockBufferNoErr)&#xA;&#xA;        guard let eBlock = blockBuffer else { return nil }&#xA;&#xA;        osStatus = CMBlockBufferFillDataBytes(with: 0, blockBuffer: eBlock, offsetIntoDestination: 0, dataLength: memoryBlockByteLength)&#xA;        assert(osStatus == kCMBlockBufferNoErr)&#xA;&#xA;        TVBlockBufferHelper.fillAudioBlockBuffer(blockBuffer,&#xA;                                                 audioData: data,&#xA;                                                 frames: Int32(framesCount))&#xA;        /* Audio description creations */&#xA;&#xA;        absd = AudioStreamBasicDescription(&#xA;            mSampleRate: sampleRate,&#xA;            mFormatID: kAudioFormatLinearPCM,&#xA;            mFormatFlags: kLinearPCMFormatFlagIsPacked | kLinearPCMFormatFlagIsFloat,&#xA;            mBytesPerPacket: bytesPerFrame,&#xA;            mFramesPerPacket: 1,&#xA;            mBytesPerFrame: bytesPerFrame,&#xA;            mChannelsPerFrame: channelCount,&#xA;            mBitsPerChannel: 32,&#xA;            mReserved: 0&#xA;        )&#xA;&#xA;        guard absd != nil else {&#xA;            print("\nCreating AudioStreamBasicDescription Failed.")&#xA;            return nil&#xA;        }&#xA;&#xA;        osStatus = CMAudioFormatDescriptionCreate(allocator: kCFAllocatorDefault,&#xA;                                                  asbd: &amp;absd,&#xA;                                                  layoutSize: 0,&#xA;                                                  layout: nil,&#xA;//                                                layoutSize: MemoryLayout<audiochannellayout>.size,&#xA;//                                                layout: &amp;acl,&#xA;                                                  magicCookieSize: 0,&#xA;                                                  magicCookie: nil,&#xA;                                                  extensions: nil,&#xA;                                                  formatDescriptionOut: &amp;audioFormatDescription)&#xA;&#xA;        guard osStatus == noErr else {&#xA;            print("\nCreating CMFormatDescription Failed.")&#xA;            return nil&#xA;        }&#xA;&#xA;        /* Create sample Buffer */&#xA;        var timmingInfo = CMSampleTimingInfo(duration: sampleDuration, presentationTimeStamp: presentationTimeStamp, decodeTimeStamp: .invalid)&#xA;&#xA;        osStatus = CMSampleBufferCreate(allocator: kCFAllocatorDefault,&#xA;                                        dataBuffer: eBlock,&#xA;                                        dataReady: true,&#xA;                                        makeDataReadyCallback: nil,&#xA;                                        refcon: nil,&#xA;                                        formatDescription: audioFormatDescription,&#xA;                                        sampleCount: framesCount,&#xA;                                        sampleTimingEntryCount: 1,&#xA;                                        sampleTimingArray: &amp;timmingInfo,&#xA;                                        sampleSizeEntryCount: 0, // Must be 0, 1, or numSamples.&#xA;            sampleSizeArray: nil, // Pointer ot Int. Don&#x27;t know the size. Don&#x27;t know if its bytes or bits?&#xA;            sampleBufferOut: &amp;sampleBuffer)&#xA;        return sampleBuffer&#xA;    }&#xA;&#xA;}&#xA;</audiochannellayout></float32></uint8>

  



  CMSampleBuffer gets filled with raw audio data from FFmpeg's data :

  



  @import Foundation;
@import CoreMedia;

@interface BlockBufferHelper : NSObject

+(void)fillAudioBlockBuffer:(CMBlockBufferRef)blockBuffer
                  audioData:(uint8_t *)data
                     frames:(int)framesCount;



@end

#import "TVBlockBufferHelper.h"

@implementation BlockBufferHelper

+(void)fillAudioBlockBuffer:(CMBlockBufferRef)blockBuffer
                  audioData:(uint8_t *)data
                     frames:(int)framesCount
{
    // Possibly dev error.
    if (framesCount == 0) {
        NSAssert(false, @"\nfillAudioBlockBuffer/audioData/frames will not be able to fill an blockBuffer which has no frames.");
        return;
    }

    char *rawBuffer = NULL;

    size_t size = 0;

    OSStatus status = CMBlockBufferGetDataPointer(blockBuffer, 0, &size, NULL, &rawBuffer);
    if(status != noErr)
    {
        return;
    }

    memcpy(rawBuffer, data, framesCount);
}

@end


  



  The LEARNING Core Audio book from Chris Adamson/Kevin Avila points me toward a multi channel mixer. 
The multi channel mixer should have 2-n inputs and 1 output. I assume the output could be a buffer or something that could be put into a CMSampleBuffer for further consumption.

  



  This direction should lead me to AudioUnits, AUGraph and the AudioToolbox. I don't understand all of these classes and how they work together. I have found some code snippets on SO which could help me but most of them use AudioToolBox classes and don't use CMSampleBuffers as much as I need.

  



  Is there another way to merge audio buffers into a new one ?

  



  Is creating a multi channel mixer using AudioToolBox the right direction ?

  


• Date and segment comparison feature

  31 octobre 2019, par Matomo Core Team — Analytics Tips, Development

  Get a clearer picture with the date and segment comparison feature

  What can you do with it ? What are the benefits ?

  Make informed decisions faster by easily comparing different segments and dates with each other.

  Compare report data for multiple segments next to each other

  

  Directly compare the behaviour of visitors from different segments e.g. customers with accounts vs. customers without accounts. Segment comparisons are a powerful way to compare different audience ; learn which ones perform better ; and in what way their actions differ. 

  Compare report data for two time periods next to each other

  

  See how your website performs compared to the previous month/week/year. Including seeing trends over those periods. Say, your business always picks up at the same times within a year, or there’s a sag in business for every user segment over this year and the last except one.

  By being able to compare date ranges you are able to get a quick overview of trends and period to period performance. Has a campaign worked better in September than in October ? Get an instant look by having the side-by-side comparison in Matomo.

  What is it capable of ?

  It lets you ask the question, “What is different ?”

  If you look at reports you’ll only see how people behave overall and if you look at specific segments you’ll see how they behave at face value, however, if you compare data together you’ll be quickly informed on what makes them unique. This data is still there when you don’t use the comparison feature, it’s just buried. Comparing data highlights discrepancies and leads to important questions and answers.

  For example, perhaps some class of users have very low engagement on a specific day compared to the rest of your visitors, and perhaps those users are responsible for an outsized proportion of churn. 

  Who could benefit from it, and why ?

  Everyone can benefit from using it (and probably should use it). It’s yours to experiment with ! You shouldn’t feel restricted to only comparing between the current and last period, or having questions before you start comparing. Follow your instincts and see what pops out when data from different segments is laid out next to each other.

  Where can you find it in Matomo ?

  • Segment comparison is activated by the new icon in the segment selector

  

  • Date comparison can be found in the calendar section of Matomo

  

  • The list of active comparisons is visible at the top of the page for all pages that support comparison
  • Comparisons are visible in every report that supports comparing data, and reports that do not support it will display a message saying so

  How do you use it ?

  • To compare segments, click the icon in the segment selector
  • To compare periods, click the ‘compare’ checkbox in the period selector, then select what period you want to compare it against in the dropdown (previous period, previous year, or a custom range)
  • When comparisons are active, view your reports as normal

  Take it away !

  The comparison feature is a new tool from Matomo 3.12.0 that highlights discrepancies and differences in data that can lead to more clarity and understanding, so we’d encourage everyone to use it. 

  Try it out today in your Matomo and see the power behind this new data comparison mode !