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Machine Learning For Time-series Forecasting

Machine learning is taking the world by storm, performing many tasks with human-like accuracy. In the medical field, there are now smart assistants that can check your health over time. In finance, there are tools that can predict the return on your investment with a reasonable degree of accuracy. In online marketing, there are product recommenders that suggest specific products and brands based on your purchase history.

In each of these fields, a different type of data can be used to train machine learning models. Among them, time-series data is used for training machine learning algorithms where time is the crucial component.

Source de l’article sur DZONE

Maps are a fascinating method for delivering content. At their best, they can create an intuitive way of presenting information and interacting with it. This is the advantage that digital maps, through mobile apps and websites, have over print maps and images where no interactivity is possible.

But it’s important to understand that more data ≠ better experiences. We all now have so much data available to us through multiple services that, arguably, the greatest challenge isn’t sourcing information but filtering it out. We can only handle so much information input before we become overloaded. This issue risks being omnipresent with maps. There are so many potential points of interest on a map that it’s essential to be clear about what needs to be exposed to users.

Also, UX design, map design, and user interface are all critical. While maps can be a powerful way of drawing people in, if end-users feel that you didn’t even consider the visual design, they’ll ‘bounce off’ your site or app in moments.

Common Use Cases

When are maps useful, and what problems do they solve? Let’s dive right into the most common use cases for maps used in web design.

Navigation and Direction

Like Google Maps shows, navigation and direction are arguably the classic case study for interactive maps. You are in one place and need to get to another. You can enter your destination, your current location, and the map will present suggestions for getting there. You can select the method of travel and adjust desired departure or arrival times. But you need to understand first what functionality your users need. How these options are exposed to users is a critical piece of UX design.

Also, if users are searching for options such as somewhere to eat, it’s not so straightforward. Then, how your map handles panning in real-time as users swipe around a city is going to be a big issue.

Showing Relationships and Trends Geographically

This is something that you’ll see in every election in any western country. We’re all used to seeing maps that give us a state-of-play for which state or seat is held by which party. Then, we might see projections based on voter intentions and projected voting swings deriving from that. Then, exit poll data can be projected with the map updated on an ongoing basis until the final result is confirmed.

The capability to do this is essential because if a static map were used, it’d be out of date any time a new poll was released. Also, voting intentions can change over a campaign, so such maps need to be dynamic. Of course, such maps are only as accurate as the available data, as the US 2016 election map showed.

Show Points of Interest

As mentioned previously, there’s a lot of data that can be exposed to map users. However, that doesn’t automatically mean that it should be. Usability is key. For example, when you look at a map, you’ll typically first see key points of interest. Which points of interest are going to be presented to you can vary.

One variant is zoom level. If your map is currently showing an entire city, the level of detail the map presents is deliberately limited. You’ll see districts, large roads, or geographic features such as rivers. If more detailed information were presented, users on mobile devices, in particular, would be overwhelmed. Even at this level, you’ll notice typography differences. These can include the city name being in bold or the names of different areas in capital letters. So the level of detail is coupled with the scale of the map. Zooming in a few notches will expose significant points of interest, such as museums. Zooming in to specific districts will reveal restaurants, coffee shops, and universities. This visual hierarchy is a critical way of managing the exposed level of information.

But information is still being abstracted away. It’s not until you tap on the museum that you’ll see information on opening hours and busy times. This is also typically presented with user photos and reviews. Context is also taken into account, so you’ll start to see local hotels and restaurants. So it’s not just individual points of interest that are important, but the connections between them.

6 Tips For Improving Interactive Maps

What are the challenges of creating effective maps, and how do people address the data overload problem? We’ll answer this question and go over the must-know aspects of map creation.

1. Ensure Security and Brand Trust

GDPR or General Data Protection Regulation. This is a critically important European law that extends a wide range of legal protection to European citizens regarding personal data. It’s not possible here to cover the full extent of the law, but here are some quick key points:

  • Consent is required for the processing of personal data; it cannot be assumed
  • You need to have a retention policy for information that’s capable of identifying people

Be aware that the latter doesn’t just cover commercial purposes. Research students have to submit GDPR forms that address what kind of data they’re sourcing and how they’ll be retaining it.

But the most crucial context is commercial. If a business suffers a data breach, it can be fined up to 20 million euros or 4% of annual worldwide turnover in the preceding financial year, whichever is greater. Therefore, any business storing data that could identify their customers will need to assess risk and compliance. Remember: it’s 4% of worldwide turnover, not EU turnover.

Also, anything of your business that you expose to your customers or users is an extension of your brand. Therefore, you need to assess your maps for brand compliance too. If you have primary brand colors and your map doesn’t abide by them, that’s a very poor look. Source the color hex codes directly from your brand team and involve them in design.

2. Use the Appropriate Type of Map

It’s also important to consider what type of map is most appropriate for your use case. Think carefully about what your users need, what you’re trying to communicate, what information you need to present, and how best to present it.

For example, points of interest style maps in a tourist app will be way more helpful than heat maps: people want to know where something is, key data like opening hours, and how to get there. A heat map showing the number of visitors to each attraction or area of a city is unlikely to be useful to tourists. However, it could be useful to the attractions themselves to map their visitors by heat map over time. This could help larger museums chart which exhibits are most popular.

Transport for London is charting passenger movement on the London Underground by detecting when a device with Wi-Fi comes into range and then passes out of range. They’re using this to understand overall user journeys and movements within individual stations to better manage disruptions.

3. Avoid Pop-Ups

It should go without saying by now that auto pop-ups are despised. It doesn’t matter what they’re doing or what they’re offering; an unwanted pop-up can only get in the way. The level of impact is even greater on a phone where pop-ups take up even more screen space.

Given this, many users close them without even reading them. So if you’re using pop-ups, don’t kid yourself. You’re likely just irritating users and increasing the likelihood that they’ll ‘bounce off’ or uninstall.

4. Avoid Auto-Geolocation

Auto-geolocation sounds incredibly convenient but can result in some real problems. For example, if there are any bugs with auto-geolocation, you could get false results. If someone connects through public building Wi-Fi, you could get false results. If they’re connecting through a VPN then, unless you get the user’s IP address and check if it’s the exit portal of a VPN, you could get false results.

The problem is most significant with mobile maps. If a map user is looking at a points of interest map, they likely have a specific and immediate use. This means it’s in their best to get the most accurate results possible. So why not just ask them?

Precision and Accuracy

These terms have specific meanings in geolocation. ‘Precision’ is the exactness of the data. ‘Accuracy’ is how closely the information on a map matches the real world. So you want precision and accuracy to be spot on, or data risks losing value. This applies not just to the gathering of data but to the representation of it. For example, if you have street-level data but your maps don’t present individual streets, then any representation of data on that map is likely to have poor accuracy. That map might succeed in abstracting irrelevant information but presenting an imprecise and inaccurate view.

5. Avoid Map Legends as Much as Possible

In many cases, primarily points-of-interest maps, they’re just not needed anymore. An essential part of user experience design isn’t just visual hierarchy but information hierarchy. You can mouse over on a desktop or laptop to get the essentials of a location, e.g., the museum’s name and its opening hours. On a mobile device, you can tap on that location to get the essentials, and you can tap on another location to move on; you don’t even have to press back. Given that, a legend would get in the way. So this simple piece of information design solves information overload issues.

As with all rules, there are exceptions. A good one is a heat map where a density of what’s being measured needs to be communicated. It doesn’t matter what the data is; it just needs to be something where mapping provides greater insight, especially if it informs decision-making. Sales is an excellent example for a national or multinational company. Of course, weather forecasting can make use of literal heat maps.

6. Accessibility Compliance

Not everyone has perfect eyesight. Even if someone has excellent vision, they could still be colorblind (8% of men and 0.5% of women are). Given that, take the W3C’s accessibility standards into account and treat them as a baseline or minimum barrier to entry for compliance. You shouldn’t feel good about the possibility of excluding 8% of your potential audience or customers. Ensure you keep your UX designers involved and don’t shy away from creating senior-friendly web designs.

Put simply: imagine if you could appeal to a new demographic that’s not catered to. If your competitors ignore them, you could give them a real reason to choose you instead by taking some straightforward steps. If your competitors are catering to them, you also need to. If you don’t, you’re just giving potential customers a big reason to ignore you.

Conclusions

The key takeaway is that there’s far more to creating good maps than just good cartography. That can be critical, too, though this may vary depending on the use case.

This will be a team effort because your map will involve data sets, design decisions, and, yes, cartography. You’re going to need to involve brand and IT too. So think about design principles and development methodologies.

First and foremost, what are your users’ needs? If you haven’t done any user research or taken the time to understand the customer journey, are you adding anything or getting in the way? It’s easy to see the department that requested the map as stakeholders, but you should probably view your users as stakeholders too.

This sounds complex, but as you hopefully now appreciate, a map is probably more complicated than you thought.

 

Featured image via Pexels.

Source

The post The UX of Maps in Web Design first appeared on Webdesigner Depot.

Source de l’article sur Webdesignerdepot


Regard croisé : pourquoi SAP S/4HANA est un ERP intelligent ?

Qu’est-ce qu’une Entreprise Intelligente et qu’est-ce qu’un ERP Intelligent ?

Pierre-Édouard Hamon, SOA People, et Christian Charvin, SAP, partagent leur vision de l’évolution du SI des entreprises.

Aujourd’hui, la plupart des entreprises ont à leur disposition un certain volume de données qu’elles n’exploitent pas. Cela représente pourtant une richesse qui permettrait aux organisations de mieux comprendre leur activité et leur marché. Être une Entreprise Intelligente, c’est savoir exploiter ces données afin d’optimiser son organisation, automatiser ses processus et se mettre en ordre de marche afin de relever de nouveaux défis.

Pierre-Édouard Hamon 

 

C’est la raison d’être de l’ERP Intelligent SAP S/4HANA. Cette nouvelle génération d’ERP simplifie l’accès à la donnée et en assure l’exploitation en temps réel. SAP S/4HANA propose des avancées clés pour aider les équipes au quotidien : le reporting opérationnel intégré et la gestion par exceptions permettent aux utilisateurs de se concentrer sur les points nécessitant une attention particulière ; la gestion avancée des workflows, associée à des fonctions collaboratives, fluidifie les échanges entre utilisateurs.

Christian Charvin

 

Une porte ouverte vers les nouvelles technologies

 

Le fait que l’ERP propose des tableaux de bord où l’information utile est directement remontée aux utilisateurs rend l’ERP SAP S/4HANA particulièrement facile à utiliser. Ceci permet de se concentrer sur les tâches les plus urgentes et aide à la prise de décision. Son interface de nouvelle génération est très proche de celles utilisées dans les applications desktops et mobiles du quotidien. Un atout pour accélérer la prise en main de l’ERP.

De nouvelles technologies permettent d’aller encore plus loin. Le RPA permet ainsi d’améliorer l’automatisation des processus, en mettant en place des robots capables de prendre en charge les tâches répétitives, libérant ainsi du temps aux équipes métiers. Le Machine Learning et l’Intelligence Artificielle s’appuient sur l’historique de données de l’entreprise pour prédire son futur. Ces technologies de forecasting automatique sont directement intégrées dans l’ERP.

Lorsque les entreprises vont mettre en œuvre ces technologies intelligentes, elles pourront s’appuyer sur des préconfigurés adaptés à leur secteur d’activité. Cela leur évitera de partir d’une feuille blanche et de se lancer dans l’inconnu. Y compris en cas de déploiement de l’ERP en mode cloud.

Pierre-Édouard Hamon

 

Cap vers le cloud !

 

Le cloud devient le mode de déploiement majoritaire des utilisateurs d’ERP SAP. Depuis le début de l’année 2021, 80% des clients SAP optent pour un déploiement de leur ERP SAP S/4HANA en mode cloud. Le cloud permet d’avoir une meilleure prédictibilité sur les coûts, de déléguer la gestion des infrastructures à des spécialistes et de disposer d’une flexibilité sans égale permettant d’adopter de nouvelles technologies et fonctionnalités au fil des besoins. Sans compter que le cloud est accessible de partout et permet donc une utilisation facilitée de l’ERP sur des sites distants, en mobilité ou en télétravail.

Christian Charvin

 

L’offre RISE with SAP permet de profiter de tous les avantages du cloud sans avoir à gérer la complexité de la relation avec les hyperscalers. Le contrat est directement pris en charge par SAP, qui se charge de garantir la disponibilité, la sécurité et la flexibilité de la solution, avec une prédictibilité totale sur les coûts. RISE with SAP permet de bénéficier de tous les avantages du cloud, avec une mise en œuvre rapide au travers des préconfigurés, et ce sans faire une croix sur les spécifiques. Et des mises à jour régulières de l’ERP donnent accès à de nouvelles fonctionnalités.

La SAP Business Technology Platform permet de déployer le code spécifique, mais aussi d’accéder à des technologies avancées, comme des systèmes de reconnaissance d’images, des outils d’analyse de l’expérience client ou même des agents conversationnels, qui vont à la fois assister les utilisateurs et faciliter la collaboration au sein de l’entreprise. La SAP BTP permet d’ouvrir l’ERP à un nombre illimité de technologies innovantes, proposées par SAP, ses partenaires ou tout autre fournisseur de services.

Pierre-Édouard Hamon

 

L’occasion de se réinventer

 

Ce mouvement massif vers le cloud s’accompagne d’un changement de paradigme chez nombre de nos clients. Ils adoptent une approche Fit to Standard consistant à utiliser un ERP aussi proche que possible de la version originale, afin de faciliter les montées de version. Les spécifiques, auparavant déployés dans le cœur de l’ERP, sont déportés sur la SAP BTP, qui sert également d’interface pour adopter des technologies innovantes : Chatbots, Blockchain, Internet des Objets, etc.

Christian Charvin

 

Pierre-Édouard Hamon  Christian Charvin

 

Pour en savoir plus :

The post Pourquoi SAP S/4HANA est un ERP Intelligent ? appeared first on SAP France News.

Source de l’article sur sap.com

In the tech world, DevOps is a word frequently tossed around to describe the blending of development and operations teams. It’s a melting pot where engineers work in tandem across the application lifecycle, revamping the typical « silo » framework. Adopting this model requires a necessary change of antiquated company culture to dismantle and reorganize the traditional structure, ultimately reducing operational inefficiencies. Once optimized, these DevOps teams produce benefits like increased speed and reliability, rapid delivery and scaling ability, and improved collaboration and security. 

Typically, this philosophy is hailed as a superior organizational approach; however, Uri Zaidenwerg voices a different opinion in his article « Why DevOps Will Cease to Exist. » In his article, Uri, a DevOps engineer himself, begins by briefly summarizing what the path to becoming a DevOps engineer looks like. Following this career outline, he identifies what he sees as « signs of the end » for DevOps engineers before forecasting his prophecy.

Source de l’article sur DZONE

Machine Learning (ML) gets a lot of hype, but its Classical predecessors are still immensely powerful, especially in the time-series space. Error, Trend, Seasonality Forecast (ETS), Autoregressive Integrated Moving Average (ARIMA), and Holt-Winters are three Classical methods that are not only incredibly popular but are also excellent time-series predictors.

In fact, according to Statistical and Machine Learning forecasting methods: Concerns and ways forward, ETS outperforms several other ML methods including Long Short Term Memory (LSTM) and Recurrent Neural Networks (RNN) in One-Step Forecasting. Actually, all of the statistical methods have a lower prediction error than the ML methods do.

Source de l’article sur DZONE