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    Unfortunately a software is never perfect.
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  • Data Privacy in Business : A Risk Leading to Major Opportunities

    9 août 2022, par Erin — Privacy

    Data privacy in business is a contentious issue. 

    Claims that “big data is the new oil of the digital economy” and strong links between “data-driven personalisation and customer experience” encourage leaders to set up massive data collection programmes.

    However, many of these conversations downplay the magnitude of security, compliance and ethical risks companies face when betting too much on customer data collection. 

    In this post, we discuss the double-edged nature of privacy issues in business — the risk-ridden and the opportunity-driven. ​​

    3 Major Risks of Ignoring Data Privacy in Business

    As the old adage goes : Just because everyone else is doing it doesn’t make it right.

    Easy data accessibility and ubiquity of analytics tools make data consumer collection and processing sound like a “given”. But the decision to do so opens your business to a spectrum of risks. 

    1. Compliance and Legal Risks 

    Data collection and customer privacy are protected by a host of international laws including GDPR, CCPA, and regional regulations. Only 15% of countries (mostly developing ones) don’t have dedicated laws for protecting consumer privacy. 

    State of global data protection legislature via The UN

    Global legislature includes provisions on : 

    • Collectible data types
    • Allowed uses of obtained data 
    • Consent to data collection and online tracking 
    • Rights to request data removal 

    Personally identifiable information (PII) processing is prohibited or strictly regulated in most jurisdictions. Yet businesses repeatedly circumnavigate existing rules and break them on occasion.

    In Australia, for example, only 2% of brands use logos, icons or messages to transparently call out online tracking, data sharing or other specific uses of data at the sign-up stage. In Europe, around half of small businesses are still not fully GDPR-compliant — and Big Tech companies like Google, Amazon and Facebook can’t get a grip on their data collection practices even when pressed with horrendous fines. 

    Although the media mostly reports on compliance fines for “big names”, smaller businesses are increasingly receiving more scrutiny. 

    As Max Schrems, an Austrian privacy activist and founder of noyb NGO, explained in a Matomo webinar :

    “In Austria, my home country, there are a lot of €5,000 fines going out there as well [to smaller businesses]. Most of the time, they are just not reported. They just happen below the surface. [GDPR fines] are already a reality.”​

    In April 2022, the EU Court of Justice ruled that consumer groups can autonomously sue businesses for breaches of data protection — and nonprofit organisations like noyb enable more people to do so. 

    Finally, new data privacy legislation is underway across the globe. In the US, Colorado, Connecticut, Virginia and Utah have data protection acts at different stages of approval. South African authorities are working on the Protection of Personal Information Act (POPI) act and Brazil is working on a local General Data Protection Law (LGPD).

    Re-thinking your stance on user privacy and data protection now can significantly reduce the compliance burden in the future. 

    2. Security Risks 

    Data collection also mandates data protection for businesses. Yet, many organisations focus on the former and forget about the latter. 

    Lenient attitudes to consumer data protection resulted in a major spike in data breaches.

    Check Point research found that cyberattacks increased 50% year-over-year, with each organisation facing 925 cyberattacks per week globally.

    Many of these attacks end up being successful due to poor data security in place. As a result, billions of stolen consumer records become publicly available or get sold on dark web marketplaces.

    What’s even more troublesome is that stolen consumer records are often purchased by marketing firms or companies, specialising in spam campaigns. Buyers can also use stolen emails to distribute malware, stage phishing and other social engineering attacks – and harvest even more data for sale. 

    One business’s negligence creates a snowball effect of negative changes down the line with customers carrying the brunt of it all. 

    In 2020, hackers successfully targeted a Finnish psychotherapy practice. They managed to steal hundreds of patient records — and then demanded a ransom both from the firm and its patients for not exposing information about their mental health issues. Many patients refused to pay hackers and some 300 records ended up being posted online as Associated Press reported.

    Not only did the practice have to deal with the cyber-breach aftermath, but it also faced vocal regulatory and patient criticisms for failing to properly protect such sensitive information.

    Security negligence can carry both direct (heavy data breach fines) and indirect losses in the form of reputational damages. An overwhelming 90% of consumers say they wouldn’t buy from a business if it doesn’t adequately protect their data. This brings us to the last point. 

    3. Reputational Risks 

    Trust is the new currency. Data negligence and consumer privacy violations are the two fastest ways to lose it. 

    Globally, consumers are concerned about how businesses collect, use, and protect their data. 

    Consumer data sharing attitudes
    • According to Forrester, 47% of UK adults actively limit the amount of data they share with websites and apps. 49% of Italians express willingness to ask companies to delete their personal data. 36% of Germans use privacy and security tools to minimise online tracking of their activities. 
    • A GDMA survey also notes that globally, 82% of consumers want more control over their personal information, shared with companies. 77% also expect brands to be transparent about how their data is collected and used. 

    When businesses fail to hold their end of the bargain — collect just the right amount of data and use it with integrity — consumers are fast to cut ties. 

    Once the information about privacy violations becomes public, companies lose : 

    • Brand equity 
    • Market share 
    • Competitive positioning 

    An AON report estimates that post-data breach companies can lose as much as 25% of their initial value. In some cases, the losses can be even higher. 

    In 2015, British telecom TalkTalk suffered from a major data breach. Over 150,000 customer records were stolen by hackers. To contain the issue, TalkTalk had to throw between $60-$70 million into containment efforts. Still, they lost over 100,000 customers in a matter of months and one-third of their company value, equivalent to $1.4 billion, by the end of the year. 

    Fresher data from Infosys gives the following maximum cost estimates of brand damage, companies could experience after a data breach (accidental or malicious).

    Estimated cost of brand damage due to a data breach

    3 Major Advantages of Privacy in Business 

    Despite all the industry mishaps, a reassuring 77% of CEOs now recognise that their companies must fundamentally change their approaches to customer engagement, in particular when it comes to ensuring data privacy. 

    Many organisations take proactive steps to cultivate a privacy-centred culture and implement transparent data collection policies. 

    Here’s why gaining the “privacy advantage” pays off.

    1. Market Competitiveness 

    There’s a reason why privacy-focused companies are booming. 

    Consumers’ mounting concerns and frustrations over the lack of online privacy, prompt many to look for alternative privacy-centred products and services

    The following B2C and B2B products are moving from the industry margins to the mainstream : 

    Across the board, consumers express greater trust towards companies, protective of their privacy : 

    And as we well know : trust translates to higher engagement, loyalty, and – ultimately revenue. 

    By embedding privacy into the core of your product, you give users more reasons to select, stay and support your business. 

    2. Higher Operational Efficiency

    Customer data protection isn’t just a policy – it’s a culture of collecting “just enough” data, protecting it and using it responsibly. 

    Sadly, that’s the area where most organisations trail behind. At present, some 90% of businesses admit to having amassed massive data silos. 

    Siloed data is expensive to maintain and operationalise. Moreover, when left unattended, it can evolve into a pressing compliance issue. 

    A recently leaked document from Facebook says the company has no idea where all of its first-party, third-party and sensitive categories data goes or how it is processed. Because of this, Facebook struggles to achieve GDPR compliance and remains under regulatory pressure. 

    Similarly, Google Analytics is riddled with privacy issues. Other company products were found to be collecting and operationalising consumer data without users’ knowledge or consent. Again, this creates valid grounds for regulatory investigations. 

    Smaller companies have a better chance of making things right at the onset. 

    By curbing customer data collection, you can : 

    • Reduce data hosting and Cloud computation costs (aka trim your Cloud bill) 
    • Improve data security practices (since you would have fewer assets to protect) 
    • Make your staff more productive by consolidating essential data and making it easy and safe to access

    Privacy-mindful companies also have an easier time when it comes to compliance and can meet new data regulations faster. 

    3. Better Marketing Campaigns 

    The biggest counter-argument to reducing customer data collection is marketing. 

    How can we effectively sell our products if we know nothing about our customers ? – your team might be asking. 

    This might sound counterintuitive, but minimising data collection and usage can lead to better marketing outcomes. 

    Limiting the types of data that can be used encourages your people to become more creative and productive by focusing on fewer metrics that are more important.

    Think of it this way : Every other business uses the same targeting parameters on Facebook or Google for running paid ad campaigns on Facebook. As a result, we see ads everywhere — and people grow unresponsive to them or choose to limit exposure by using ad blocking software, private browsers and VPNs. Your ad budgets get wasted on chasing mirage metrics instead of actual prospects. 

    Case in point : In 2017 Marc Pritchard of Procter & Gamble decided to first cut the company’s digital advertising budget by 6% (or $200 million). Unilever made an even bolder move and reduced its ad budget by 30% in 2018. 

    Guess what happened ?

    P&G saw a 7.5% increase in organic sales and Unilever had a 3.8% gain as HBR reports. So how come both companies became more successful by spending less on advertising ? 

    They found that overexposure to online ads led to diminishing returns and annoyances among loyal customers. By minimising ad exposure and adopting alternative marketing strategies, the two companies managed to market better to new and existing customers. 

    The takeaway : There are more ways to engage consumers aside from pestering them with repetitive retargeting messages or creepy personalisation. 

    You can collect first-party data with consent to incrementally improve your product — and educate them on the benefits of your solution in transparent terms.

    Final Thoughts 

    The definitive advantage of privacy is consumers’ trust. 

    You can’t buy it, you can’t fake it, you can only cultivate it by aligning your external appearances with internal practices. 

    Because when you fail to address privacy internally, your mishaps will quickly become apparent either as social media call-outs or worse — as a security incident, a data breach or a legal investigation. 

    By choosing to treat consumer data with respect, you build an extra layer of protection around your business, plus draw in some banging benefits too. 

    Get one step closer to becoming a privacy-centred company by choosing Matomo as your web analytics solution. We offer robust privacy controls for ensuring ethical, compliant, privacy-friendly and secure website tracking. 

  • is possible to "hash" a ssim from original image so i dont have to read the image again ?

    6 septembre 2022, par Vaguiner Gonzalez

    Currently I started working on a personal project where you will constantly receive images, similar or not. Every new image received do I need to loop through absolutely every other image already saved to compare ssim ?

    


  • Is Google Analytics Accurate ? 6 Important Caveats

    8 novembre 2022, par Erin

    It’s no secret that accurate website analytics is crucial for growing your online business — and Google Analytics is often the go-to source for insights. 

    But is Google Analytics data accurate ? Can you fully trust the provided numbers ? Here’s a detailed explainer.

    How Accurate is Google Analytics ? A Data-Backed Answer 

    When properly configured, Google Analytics (Universal Analytics and Google Analytics 4) is moderately accurate for global traffic collection. That said : Google Analytics doesn’t accurately report European traffic. 

    According to GDPR provisions, sites using GA products must display a cookie consent banner. This consent is required to collect third-party cookies — a tracking mechanism for identifying users across web properties.

    Google Analytics (GA) cannot process data about the user’s visit if they rejected cookies. In such cases, your analytics reports will be incomplete.

    Cookie rejection refers to visitors declining or blocking cookies from ever being collected by a specific website (or within their browser). It immediately affects the accuracy of all metrics in Google Analytics.

    Google Analytics is not accurate in locations where cookie consent to tracking is legally required. Most consumers don’t like disruptive cookie banners or harbour concerns about their privacy — and chose to reject tracking. 

    This leaves businesses with incomplete data, which, in turn, results in : 

    • Lower traffic counts as you’re not collecting 100% of the visitor data. 
    • Loss of website optimisation capabilities. You can’t make data-backed decisions due to inconsistent reporting

    For the above reasons, many companies now consider cookieless website tracking apps that don’t require consent screen displays. 

    Why is Google Analytics Not Accurate ? 6 Causes and Solutions 

    A high rejection rate of cookie banners is the main reason for inaccurate Google Analytics reporting. In addition, your account settings can also hinder Google Analytics’ accuracy.

    If your analytics data looks wonky, check for these six Google Analytics accuracy problems. 

    You Need to Secure Consent to Cookies Collection 

    To be GDPR-compliant, you must display a cookie consent screen to all European users. Likewise, other jurisdictions and industries require similar measures for user data collection. 

    This is a nuisance for many businesses since cookie rejection undermines their remarketing capabilities. Hence, some try to maximise cookie acceptance rates with dark patterns. For example : hide the option to decline tracking or make the texts too small. 

    Cookie consent banner examples
    Banner on the left doesn’t provide an evident option to reject all cookies and nudges the user to accept tracking. Banner on the right does a better job explaining the purpose of data collection and offers a straightforward yes/no selection

    Sadly, not everyone’s treating users with respect. A joint study by German and American researchers found that only 11% of US websites (from a sample of 5,000+) use GDPR-compliant cookie banners.

    As a result, many users aren’t aware of the background data collection to which they have (or have not) given consent. Another analysis of 200,000 cookies discovered that 70% of third-party marketing cookies transfer user data outside of the EU — a practice in breach of GDPR.

    Naturally, data regulators and activities are after this issue. In April 2022, Google was pressured to introduce a ‘reject all’ cookies button to all of its products (a €150 million compliance fine likely helped with that). Whereas, noyb has lodged over 220 complaints against individual websites with deceptive cookie consent banners.

    The takeaway ? Messing up with the cookie consent mechanism can get you in legal trouble. Don’t use sneaky banners as there are better ways to collect website traffic statistics. 

    Solution : Try Matomo GDPR-Friendly Analytics 

    Fill in the gaps in your traffic analytics with Matomo – a fully GDPR-compliant product that doesn’t rely on third-party cookies for tracking web visitors. Because of how it is designed, the French data protection authority (CNIL) confirmed that Matomo can be used to collect data without tracking consent.

    With Matomo, you can track website users without asking for cookie consent. And when you do, we supply you with a compact, compliant, non-disruptive cookie banner design. 

    Your Google Tag Isn’t Embedded Correctly 

    Google Tag (gtag.js) is a web tracking script that sends data to your Google Analytics, Google Ads and Google Marketing Platform.

    A corrupted gtag.js installation can create two accuracy issues : 

    • Duplicate page tracking 
    • Missing script installation 

    Is there a way to tell if you’re affected ?

    Yes. You may have duplicate scripts installed if you have a very low bounce rate on most website pages (below 15% – 20%). The above can happen if you’re using a WordPress GA plugin and additionally embed gtag.js straight in your website code. 

    A tell-tale sign of a missing script on some pages is low/no traffic stats. Google alerts you about this with a banner : 

    Google Analytics alerts

    Solution : Use Available Troubleshooting Tools 

    Use Google Analytics Debugger extension to analyse pages with low bounce rates. Use the search bar to locate duplicate code-tracking elements. 

    Alternatively, you can use Google Tag Assistant for diagnosing snippet install and troubleshooting issues on individual pages. 

    If the above didn’t work, re-install your analytics script

    Machine Learning and Blended Data Are Applied

    Google Analytics 4 (GA4) relies a lot on machine learning and algorithmic predictions.

    By applying Google’s advanced machine learning models, the new Analytics can automatically alert you to significant trends in your data. [...] For example, it calculates churn probability so you can more efficiently invest in retaining customers.

    On the surface, the above sounds exciting. In practice, Google’s application of predictive algorithms means you’re not seeing actual data. 

    To offer a variation of cookieless tracking, Google algorithms close the gaps in reporting by creating models (i.e., data-backed predictions) instead of reporting on actual user behaviours. Therefore, your GA4 numbers may not be accurate.

    For bigger web properties (think websites with 1+ million users), Google also relies on data sampling — a practice of extrapolating data analytics, based on a data subset, rather than the entire dataset. Once again, this can lead to inconsistencies in reporting with some numbers (e.g., average conversion rates) being inflated or downplayed. 

    Solution : Try an Alternative Website Analytics App 

    Unlike GA4, Matomo reports consist of 100% unsampled data. All the aggregated reporting you see is based on real user data (not guesstimation). 

    Moreover, you can migrate from Universal Analytics (UA) to Matomo without losing access to your historical records. GA4 doesn’t yet have any backward compatibility.

    Spam and Bot Traffic Isn’t Filtered Out 

    Surprise ! 42% of all Internet traffic is generated by bots, of which 27.7% are bad ones.

    Good bots (aka crawlers) do essential web “housekeeping” tasks like indexing web pages. Bad bots distribute malware, spam contact forms, hack user accounts and do other nasty stuff. 

    A lot of such spam bots are designed specifically for web analytics apps. The goal ? Flood your dashboard with bogus data in hopes of getting some return action from your side. 

    Types of Google Analytics Spam :

    • Referral spam. Spambots hijack the referrer, displayed in your GA referral traffic report to indicate a page visit from some random website (which didn’t actually occur). 
    • Event spam. Bots generate fake events with free language entries enticing you to visit their website. 
    • Ghost traffic spam. Malicious parties can also inject fake pageviews, containing URLs that they want you to click. 

    Obviously, such spammy entities distort the real website analytics numbers. 

    Solution : Set Up Bot/Spam Filters 

    Google Analytics 4 has automatic filtering of bot traffic enabled for all tracked Web and App properties. 

    But if you’re using Universal Analytics, you’ll have to manually configure spam filtering. First, create a new view and then set up a custom filter. Program it to exclude :

    • Filter Field : Request URI
    • Filter Pattern : Bot traffic URL

    Once you’ve configured everything, validate the results using Verify this filter feature. Then repeat the process for other fishy URLs, hostnames and IP addresses. 

    You Don’t Filter Internal Traffic 

    Your team(s) spend a lot of time on your website — and their sporadic behaviours can impair your traffic counts and other website metrics.

    To keep your data “employee-free”, exclude traffic from : 

    • Your corporate IPs addresses 
    • Known personal IPs of employees (for remote workers) 

    If you also have a separate stage version of your website, you should also filter out all traffic coming from it. Your developers, contractors and marketing people spend a lot of time fiddling with your website. This can cause a big discrepancy in average time on page and engagement rates. 

    Solution : Set Internal Traffic Filters 

    Google provides instructions for excluding internal traffic from your reports using IPv4/IPv6 address filters. 

    Google Analytics IP filters

    Session Timeouts After 30 Minutes 

    After 30 minutes of inactivity, Google Analytics tracking sessions start over. Inactivity means no recorded interaction hits during this time. 

    Session timeouts can be a problem for some websites as users often pin a tab to check it back later. Because of this, you can count the same user twice or more — and this leads to skewed reporting. 

    Solution : Programme Custom Timeout Sessions

    You can codify custom cookie timeout sessions with the following code snippets : 

    Final Thoughts 

    Thanks to its scale and longevity, Google Analytics has some strong sides, but its data accuracy isn’t 100% perfect.

    The inability to capture analytics data from users who don’t consent to cookie tracking and data sampling applied to bigger web properties may be a deal-breaker for your business. 

    If that’s the case, try Matomo — a GDPR-compliant, accurate web analytics solution. Start your 21-day free trial now. No credit card required.