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The pirate bay depuis la Belgique
1er avril 2013, par
Mis à jour : Avril 2013
Langue : français
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Autres articles (47)
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Keeping control of your media in your hands
13 avril 2011, parThe vocabulary used on this site and around MediaSPIP in general, aims to avoid reference to Web 2.0 and the companies that profit from media-sharing.
While using MediaSPIP, you are invited to avoid using words like "Brand", "Cloud" and "Market".
MediaSPIP is designed to facilitate the sharing of creative media online, while allowing authors to retain complete control of their work.
MediaSPIP aims to be accessible to as many people as possible and development is based on expanding the (...) -
Des sites réalisés avec MediaSPIP
2 mai 2011, parCette page présente quelques-uns des sites fonctionnant sous MediaSPIP.
Vous pouvez bien entendu ajouter le votre grâce au formulaire en bas de page. -
La sauvegarde automatique de canaux SPIP
1er avril 2010, parDans le cadre de la mise en place d’une plateforme ouverte, il est important pour les hébergeurs de pouvoir disposer de sauvegardes assez régulières pour parer à tout problème éventuel.
Pour réaliser cette tâche on se base sur deux plugins SPIP : Saveauto qui permet une sauvegarde régulière de la base de donnée sous la forme d’un dump mysql (utilisable dans phpmyadmin) mes_fichiers_2 qui permet de réaliser une archive au format zip des données importantes du site (les documents, les éléments (...)
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Matomo NAMED 2023 Hi-Tech Awards finalist
1er août 2023, par Lance — Press Releases -
Dreamcast Anniversary Programming
10 septembre 2010, par Multimedia Mike — Game HackingThis day last year saw a lot of nostalgia posts on the internet regarding the Sega Dreamcast, launched 10 years prior to that day (on 9/9/99). Regrettably, none of the retrospectives that I read really seemed to mention the homebrew potential, which is the aspect that interested me. On the occasion of the DC’s 11th anniversary, I wanted to remind myself how to build something for the unit and do so using modern equipment and build tools.
Background
Like many other programmers, I initially gained interest in programming because I desired to program video games. Not content to just plunk out games on a PC, I always had a deep, abiding ambition to program actual video game hardware. That is, I wanted to program a purpose-built video game console. The Sega Dreamcast might be the most ideal candidate to ever emerge for that task. All that was required to run your own software on the unit was the console, a PC, some free software tools, and a special connectivity measure.The Equipment
Here is the hardware required (ideally) to build software for the DC :- The console itself (I happen to have 3 of them laying around, as pictured above)
- Some peripherals : Such as the basic DC controller, the DC keyboard (flagship title : Typing of the Dead), and the visual memory unit (VMU)
- VGA box : The DC supported 480p gaming via a device that allowed you to connect the console straight to a VGA monitor via 15-pin D-sub. Not required for development, but very useful. I happen to have 3 of them from different third parties :
- Finally, the connectivity measure for hooking the DC to the PC.
There are 2 options here. The first is rare, expensive and relatively fast : A DC broadband adapter. The second is slower but much less expensive and relatively easy to come by– the DC coder’s cable. This was a DB-9 adapter on one end and a DC serial adapter on the other, and a circuit in the middle to monkey with voltage levels or some such ; I’m no electrical engineer. I procured this model from the notorious Lik Sang, well before that outfit was sued out of business.
Dealing With Legacy
Take a look at that coder’s cable again. DB-9 ? When was the last time you owned a computer with one of those ? And then think farther back to the last time to had occasion to plug something into one of those ports (likely a serial mouse).
A few years ago, someone was about to toss out this Belkin USB to DB-9 serial converter when I intervened. I foresaw the day when I would dust off the coder’s cable. So now I can connect a USB serial cable to my Eee PC, which then connects via converter to a different serial cable, one which has its own conversion circuit that alters the connection to yet another type of serial cable.
Bits is bits is bits as far as I’m concerned.
Putting It All Together
Now to assemble all the pieces (plus a monitor) into one development desktop :
The monitor says “dcload 1.0.3, idle…”. That’s a custom boot CD-ROM that is patiently waiting to receive commands, code and data via the serial port.
Getting The Software
Back in the day, homebrew software development on the DC revolved around these components :- GNU binutils : for building base toolchains for the Hitachi SH-4 main CPU as well as the ARM7-based audio coprocessor
- GNU gcc/g++ : for building compilers on top of binutils for the 2 CPUs
- Newlib : a C library intended for embedded systems
- KallistiOS : an open source, real-time OS developed for the DC
The DC was my first exposure to building cross compilers. I developed some software for the DC in the earlier part of the decade. Now, I am trying to figure out how I did it, especially since I think I came up with a few interesting ideas at the time.
Struggling With the Software Legacy
The source for KallistiOS has gone untouched since about 2004 but is still around thanks to Sourceforge. The instructions for properly building the toolchain have been lost to time, or would be were it not for the Internet Archive’s copy of a site called Hangar Eleven. Also, KallistiOS makes reference to a program called ‘dc-tool’ which is needed on the client side for communicating with dcload. I was able to find this binary at the Boob ! site (well-known in DC circles).I was able to build the toolchain using binutils 2.20.1, gcc 4.5.1 and newlib 1.18.0. Building the toolchain is an odd process as it requires building the binutils, then building the C compiler, then newlib, and then building the C compiler again along with the C++ compiler because the C++ compiler depends on newlib.
With some effort, I got the toolchain to build KallistiOS and most of its example programs. I documented most of the tweaks I had to make, several of them exactly the same as this one that I recently discovered while resurrecting a 10-year-old C program (common construct in C programming of old ?).
Moment of Truth
So I had some example programs built as ELF files. I told dc-tool to upload and run them on the waiting console. Unfortunately, the tool would just sort of stall, though some communication had evidently taken place. It has been many years since I have seen this in action but I recall that something more ought to be happening.Plan B (Hardware)
This is the point that I remember that I have been holding onto one rather old little machine that still has a DB-9 serial port. It’s not especially ergonomic to set up. I have to run it on my floor because, to connect it to my network, I need to run a 25′ ethernet cable that just barely reaches from the other room. The machine doesn’t seem to like USB keyboards, which is a shame since I have long since ditched any PS/2 keyboards. Fortunately, the box still has an old Gentoo distro and is running sshd, a holdover from its former life as a headless box.
Now when I run dc-tool, both the PC and DC report the upload progress while pretty overscan bars oscillate on the DC’s monitor. Now I’m back in business, until…
Plan C (Software)
None of these KallistiOS example programs are working. Some are even reporting catastrophic failures (register dumps) via the serial console. That’s when I remember that gcc can be a bit fickle on CPU architectures that are not, shall we say, first-class citizens. Back in the day, gcc 2.95 was a certified no-go for SH-4 development. 3.0.3 or 3.0.4 was called upon at the time. As I’m hosting this toolchain on x86_64 right now, gcc 3.0.4 can’t even be built (predates the architecture).One last option : As I searched through my old DC project directories, I found that I still have a lot of the resulting binaries, the ones I built 7-8 years ago. I upload a few of those and I finally see homebrew programming at work again, including this old program (described in detail here).
Next Steps
If I ever feel like revisiting this again, I suppose I can try some of the older 4.x series to see if they build valid programs. Alternatively, try building an x86_32-hosted 3.0.4 toolchain which ought to be a known good. And if that fails, search a little bit more to find that there are still active Dreamcast communities out there on the internet which probably have development toolchain binaries ready for download. -
A Guide to App Analytics Tools that Drive Growth
7 mars, par Daniel Crough — App AnalyticsMobile apps are big business, generating £438 billion in global revenue between in-app purchases (38%) and ad revenue (60%). And with 96% of apps relying on in-app monetisation, the competition is fierce.
To succeed, app developers and marketers need strong app analytics tools to understand their customers’ experiences and the effectiveness of their development efforts.
This article discusses app analytics, how it works, the importance and benefits of mobile app analytics tools, key metrics to track, and explores five of the best app analytics tools on the market.
What are app analytics tools ?
Mobile app analytics tools are software solutions that provide insights into how users interact with mobile applications. They track user behaviour, engagement and in-app events to reveal what’s working well and what needs improvement.
Insights gained from mobile app analytics help companies make more informed decisions about app development, marketing campaigns and monetisation strategies.
What do app analytics tools do ?
App analytics tools embed a piece of code, called a software development kit (SDK), into an app. These SDKs provide the essential infrastructure for the following functions :
- Data collection : The SDK collects data within your app and records user actions and events, like screen views, button clicks, and in-app purchases.
- Data filtering : SDKs often include mechanisms to filter data, ensuring that only relevant information is collected.
- Data transmission : Once collected and filtered, the SDK securely transmits the data to an analytics server. The SDK provider can host this server (like Firebase or Amplitude), or you can host it on-premise.
- Data processing and analysis : Servers capture, process and analyse large stores of data and turn it into useful information.
- Visualisation and reporting : Dashboards, charts and graphs present processed data in a user-friendly format.
Six ways mobile app analytics tools fuel marketing success and drive product growth
Mobile app analytics tools are vital in driving product development, enhancing user experiences, and achieving business objectives.
#1. Improving user understanding
The better a business understands its customers, the more likely it is to succeed. For mobile apps, that means understanding how and why people use them.
Mobile analytics tools provide detailed insights into user behaviours and preferences regarding apps. This knowledge helps marketing teams create more targeted messaging, detailed customer journey maps and improve user experiences.
It also helps product teams understand the user experience and make improvements based on those insights.
For example, ecommerce companies might discover that users in a particular area are more likely to buy certain products. This allows the company to tailor its offers and promotions to target the audience segments most likely to convert.
#2 Optimising monetisation strategies for increased revenue and user retention
In-app purchases and advertising make up 38% and 60% of mobile app revenue worldwide, respectively. App analytics tools provide insights companies need to optimise app monetisation by :
- Analysing purchase patterns to identify popular products and understand pricing sensitivities.
- Tracking in-app behaviour to identify opportunities for enhancing user engagement.
App analytics can track key metrics like visit duration, user flow, and engagement patterns. These metrics provide critical information about user experiences and can help identify areas for improvement.
How meaningful are the impacts ?
Duolingo, the popular language learning app, reported revenue growth of 45% and an increase in daily active users (DAU) of 65% in its Q4 2023 financial report. The company attributed this success to its in-house app analytics platform.
#3. Understanding user experiences
Mobile app analytics tools track the performance of user interactions within your app, such as :
- Screen views : Which screens users visit most frequently
- User flow : How users navigate through your app
- Session duration : How long users spend in your app
- Interaction events : Which buttons, features, and functions users engage with most
Knowing how users interact with your app can help refine your approach, optimise your efforts, and drive more conversions.
#4. Personalising user experiences
A recent McKinsey survey showed that 71% of users expect personalised app experiences. Product managers must stay on top of this since 76% of users get frustrated if they don’t receive the personalisation they expect.
Personalisation on mobile platforms requires data capture and analysis. Mobile analytics platforms can provide the data to personalise the user onboarding process, deliver targeted messages and recommend relevant content or offers.
Spotify is a prime example of personalisation done right. A recent case study by Pragmatic Institute attributed the company’s growth to over 500 million active daily users to its ability to capture, analyse and act on :
- Search behaviour
- Individual music preferences
- Playlist data
- Device usage
- Geographical location
The streaming service uses its mobile app analytics software to turn this data into personalised music recommendations for its users. Spotify also has an in-house analytics tool called Spotify Premium Analytics, which helps artists and creators better understand their audience.
#5. Enhancing app performance
App analytics tools can help identify performance issues that might be affecting user experience. By monitoring metrics like load time and app performance, developers can pinpoint areas that need improvement.
Performance optimisation is crucial for user retention. According to Google research, 53% of mobile site visits are abandoned if pages take longer than three seconds to load. While this statistic refers to websites, similar principles apply to apps—users expect fast, responsive experiences.
Analytics data can help developers prioritise performance improvements by showing which screens or features users interact with most frequently, allowing teams to focus their optimisation efforts where they’ll have the greatest impact.
#6. Identifying growth opportunities
App analytics tools can reveal untapped opportunities for growth by highlighting :
- Features users engage with most
- Underutilised app sections that might benefit from redesign
- Common user paths that could be optimised
- Moments where users tend to drop off
This intelligence helps product teams make data-informed decisions about future development priorities, feature enhancements, and potential new offerings.
For example, a streaming service might discover through analytics that users who create playlists have significantly higher retention rates. This insight could lead to development of enhanced playlist functionality to encourage more users to create them, ultimately boosting overall retention.
Key app metrics to track
Using mobile analytics tools, you can track dozens of key performance indicators (KPIs) that measure everything from customer engagement to app performance. This section focuses on the most important KPIs for app analytics, classified into three categories :
- App performance KPIs
- User engagement KPIs
- Business impact KPIs
While the exact metrics to track will vary based on your specific goals, these fundamental KPIs form the foundation of effective app analytics.
App performance KPIs
App performance metrics tell you whether an app is reliable and operating properly. They help product managers identify and address technical issues that may negatively impact user experiences.
Some key metrics to assess performance include :
- Screen load time : How quickly screens load within your app
- App stability : How often your app crashes or experiences errors
- Response time : How quickly your app responds to user interactions
- Network performance : How efficiently your app handles data transfers
User engagement KPIs
Engagement KPIs provide insights into how users interact with an app. These metrics help you understand user behaviour and make UX improvements.
Important engagement metrics include :
- Returning visitors : A measure of how often users return to an app
- Visit duration : How long users spend in your app per session
- User flow : Visualisation of the paths users take through your app, offering insights into navigation patterns
- Event tracking : Specific interactions users have with app elements
- Screen views : Which screens are viewed most frequently
Business impact KPIs
Business impact KPIs connect app analytics to business outcomes, helping demonstrate the app’s value to the organisation.
Key business impact metrics include :
- Conversion events : Completion of desired actions within your app
- Goal completions : Tracking when users complete specific objectives
- In-app purchases : Monitoring revenue from within the app
- Return on investment : Measuring the business value generated relative to development costs
Privacy and app analytics : A delicate balance
While app analytics tools can be a rich source of user data, they must be used responsibly. Tracking user in-app behaviour and collecting user data, especially without consent, can raise privacy concerns and erode user trust. It can also violate data privacy laws like the GDPR in Europe or the OCPA, FDBR and TDPSA in the US.
With that in mind, it’s wise to choose user-tracking tools that prioritise user privacy while still collecting enough data for reliable analysis.
Matomo is a privacy-focused web and app analytics solution that allows you to collect and analyse user data while respecting user privacy and following data protection rules like GDPR.
The five best app analytics tools to prove marketing value
In this section, we’ll review the five best app analytics tools based on their features, pricing and suitability for different use cases.
Matomo — Best for privacy-compliant app analytics
Matomo app analytics is a powerful, open-source platform that prioritises data privacy and compliance.
It offers a suite of features for tracking user engagement and conversions across websites, mobile apps and intranets.
Key features
- Complete data ownership : Full control over your analytics data with no third-party access
- User flow analysis : Track user journeys across different screens in your app
- Custom event tracking : Monitor specific user interactions with customisable events
- Ecommerce tracking : Measure purchases and product interactions
- Goal conversion monitoring : Track completion of important user actions
- Unified analytics : View web and app analytics in one platform for a complete digital picture
Benefits
- Eliminate compliance risks without sacrificing insights
- Get accurate data with no sampling or data manipulation
- Choose between self-hosting or cloud deployment
- Deploy one analytics solution across your digital properties (web and app) for a single source of truth
Pricing
Plan Price Cloud Starts at £19/month On-Premise Free Matomo is a smart choice for businesses that value data privacy and want complete control over their analytics data. It’s particularly well-suited for organisations in highly regulated industries, like banking.
While Matomo’s app analytics features focus on core analytics capabilities, its privacy-first approach offers unique advantages. For organisations already using Matomo for web analytics, extending to mobile creates a unified analytics ecosystem with consistent privacy standards across all digital touchpoints, giving organisations a complete picture of the customer journey.
Firebase — Best for Google services integration
Firebase is the mobile app version of Google Analytics. It’s the most popular app analytics tool on the market, with over 99% of Android apps and 77% of iOS apps using Firebase.
Firebase is popular because it works well with other Google services. It also has many features, like crash reporting, A/B testing and user segmentation.
Pricing
Plan Price Spark Free Blaze Pay-as-you-go based on usage Custom Bespoke pricing for high-volume enterprise users Adobe Analytics — Best for enterprise app analytics
Adobe Analytics is an enterprise-grade analytics solution that provides valuable insights into user behaviour and app performance.
It’s part of the Adobe Marketing Cloud and integrates easily with other Adobe products. Adobe Analytics is particularly well-suited for large organisations with complex analytics needs.
Pricing
Plan Price Select Pricing on quote Prime Pricing on quote Ultimate Pricing on quote While you must request a quote for pricing, Scandiweb puts Adobe Analytics at £2,000/mo–£2,500/mo for most companies, making it an expensive option.
Apple App Analytics — Best for iOS app analysis
Apple App Analytics is a free, built-in analytics tool for iOS app developers.
This analytics platform provides basic insights into user engagement, app performance and marketing campaigns. It has fewer features than other tools on this list, but it’s a good place for iOS developers who want to learn how their apps work.
Pricing
Apple Analytics is free.
Amplitude — Best for product analytics
Amplitude is a product analytics platform that helps businesses understand user behaviour and build better products.
It excels at tracking user journeys, identifying user segments and measuring the impact of product changes. Amplitude is a good choice for product managers and data analysts who want to make informed decisions about product development.
Pricing
Plan Price Starter Free Plus From £49/mo Growth Pricing on quote Choose Matomo’s app analytics to unlock growth
App analytics tools help marketers and product development teams understand user experiences, improve app performance and enhance products. Some of the best app analytics tools available for 2025 include Matomo, Firebase and Amplitude.
However, as you evaluate your options, consider taking a privacy-first approach to app data collection and analysis, especially if you’re in a highly regulated industry like banking or fintech. Matomo Analytics offers a powerful and ethical solution that allows you to gain valuable insights while respecting user privacy.
Ready to take control of your app analytics ? Start your 21-day free trial.