Creado el 27 Jun. 2017

An API is used for many things, including improving business results. This is the case of Dolby Laboratories, which has become a more productive company since it started using the Google Analytics API through ShufflePoint.

ShufflePoint is a tool that automates Excel reports and can generate queries directly from the spreadsheet. You can also convert data from your web analytics into colorful and dynamic PowerPoint reports.

How does Dolby Laboratories take advantage of the Google Analytics API?

There are several actions that have made the combination between ShufflePoint and the Google Analytics API a perfect team for Dolby Laboratories.

  1. ShufflePoint uses the Google Analytics API to provide enterprise integration tools.
  2. ShufflePoint has developed an SQL query language, allowing it to obtain and update information from any website or database, as done by Google Analytics. 

Dolby Laboratories uses GAQL, which allows you to view data for a particular week even years later. It also takes advantage of other ShufflePoint tools that are used to simplify its web analytics workflow, incorporate spreadsheets with complex update rollups, filters and calculations from intermediate tables or the aforementioned presentations.

How has Dolby Laboratories improved?

Dolby Laboratories has reported that the use of the tool has enabled them to substantially streamline the workflow: "They improved our custom reports, which we used to do manually in Google Analytics, combining them with the automation and flexibility of using the Google Analytics Data API".

Thanks to the help of ShufflePoint, it is now updated dynamically, allowing the whole Dolby team to quickly and effectively draw conclusions, and thus make appropriate decisions.

BBVA also offers a data-based API. Do you want to find out more about it?

Are you interested in financial APIs? Discover all the APIs we can offer you at BBVA




Creado el 21 Jun. 2017

Chatbots are the current hot trend in the technology world. They may be becoming better known among the general public, but conversational bots are not a recent development. Some companies have been experimenting with the developments that today underpin everything that is being done with bots for a long time: basically, this involves processing natural language to enable a machine to have an intelligent conversation with the user. This would be totally impossible without these developments.

When we look at the natural evolution of IT and how users relate to it, it is easy to understand what some of the world's biggest companies are up to. In the mid-2000s, smartphones entered our lives, with their mobile operating systems (iOS and Android), native applications and native mobile-user experiences, all on the client side.

Current trends are still focused on smartphones, but now on messaging apps, where direct contact through chatbots has become king. The diagram below shows how technology has developed since the 80s

This has been made possible by the enormous push to natural language processing, automatic learning, virtual assistants and artificial language in general by companies such as Facebook and Google.

A number of smaller companies have also understood the real business opportunities in the creation of platforms for easy creation of conversational chatbots, some of which do not need you to write a single line of code. We describe some of the most interesting platforms for creating bots below, based on the need for flexibility in introducing an MVP:

1. must be doing something right to catch the eye of Google. The creators of this platform are fostering a space for the creation of bots for third-party scenarios, such as: Slack, the project management and internal communication project for companies; Facebook Messenger, the Menlo Park company's chat program; Kik, an instant messaging app competing with Facebook Messenger; other players in the sector, such as WhatsApp, Telegram and WeChat; and more purely social products, such as Snapchat.

The best thing about is that you can create a chatbot for Slack or Facebook Messenger without any programming knowledge: you do not need to know a programming language or memorize any commands. The idea is to create the bot, generate the paths for different messages, implement integration in a messaging platform and publish. 

2. is a simple chatbot creation platform for two of the leading messaging apps - Facebook Messenger and Slack - of the moment. It can also create bots for browsing, email and SMS. There is a free version, which can develop bots with up to 1,000 messages per month; and three paid versions: one for $15 per month (5 bots and 5,000 messages); one for $50 (with 25 bots and 20,000 messages per month) and the most expensive, at $100 per month (50 bots and 50,000 messages per month). also offers its own API REST for integration with its own interface.

All you have to do to create your bot is register, enter the site and go to the ‘My Bots’ menu on the left. Here you can create as many chatbots as you want, by clicking ‘Create Bot’ and selecting the channel where you want to create your product (for Facebook Messenger, Slack or a bot for email, a browser or SMS). All the technical information you need to start to create your chatbot is available on the documentation page. 

Once you have named your bot, you can go to the edit page and configure the modules for the chatbot's user conversations. Each of these modules represents a specific reply by the bot, which can be edited using the ‘Configuration’ button. These modules form the various elements in the conversation pipelines, which are represented by connections shown by colored lines and a flow chart. offers many types of modules, and you can choose the type of content you want by clicking ‘Add Module’. It also has direct access to testing functionality for the bot and its metrics. 

3. describes itself as an interface-creation platform for companies. It offers a wide range of integrations with third-party solutions, including all of the big boys (Facebook Messenger, LINE, Twillio, WeChat and Telegram), and both cell-phone operating systems, iOS and Android. also offers its own API REST for personalized integration. The idea is to offer a seamless customer experience (incorporating all types of content formats - text, images, gifs, videos, etc. and visual elements, such as buttons), providing developers with the flexibility and scalability needed to connect chatbots to Customer Relationship Management (CRM) systems.

This is one of the things that really sets apart: it can connect conversational interfaces with a company's CRM system or internal customer-management platform. It also offers a full range of metrics and reports on the combined working of these platforms. 

4. is a chatbot development platform for practically all of the messaging tools, social networks and VoIP solutions on the market, Facebook, Twitter, Telegram, Slack, Hipchat, Twillio, Line and Skype, etc., and will be expanding to Google Hangouts, Viber and Kakao in future. offers a simple code-editor solution (this is a major difference compared to the other platforms - you have to program), a publication service and a testing system for each chatbot handles the installation of the libraries and packages needed to create the bots with no need for input from the developer, and a secure server for roll out, meaning you don't need your own server.

It then leaves the creation of the functional logic for the chatbot in the hands of the programmers. Gupshup bots are developed in the upper part of the Amazon AWS Lambda service, in a serverless computing service that executes code in response to events. It also offers a testing service, enabling developers to test their product as if they were already live on Slack, Telegram or Facebook Messenger. 

Creado el 12 Jun. 2017

The most common is, without a doubt, RSS: the standard of syndication. RSS has allowed newsrooms around the world to capture content from external sources and distribute it to readers. RSS, or Really Simple Syndication, is an XML standard to create tools that automatically share content updates with a common pattern.

Although customers' use of RSS has declined in recent years in favor of social media, RSS remains at the core of many tools. Podcasting, for example, continues to rely on RSS to distribute new episodes, and behind the scenes it remains one of the preferred newsroom formats.


On a sports level, there is no other channel as complete as ESPN. The Disney division offers developers (who are fortunate enough to gain access) an incredibly rich API. It has much more than just sports results: information about athletes, schedule of events, and an almost infinite library of interconnected data.

An example of the latter could be requesting interesting information about an American football team and getting data to fill in a report such as "The Dallas Cowboys have a 3-0 record against teams with new Quarterback on Thanksgiving". All the crazy statistics that any sports newsroom could ever want are on this ESPN API.

USA Today also has an API dedicated to sports professionals from the great United States leagues, which is useful for getting quick and accurate information for computer graphics.


ProPublica is an American non-profit organization. It's an independent entity that bases its business model on creating research journalism thanks to donations from its supporters. Working with IFTTT, a platform that serves as a link between various sources and destinations, has managed to create automation tools that are extremely useful for newsrooms around the world.

The ProPublica channels on IFTTT make it possible to automate tasks that, until now, involved a huge amount of resources:

-     Organizing when each new piece of legislation is going to be voted on in a schedule. As well as receiving it in an email or saving it in Google Docs.

-     Receiving an alert every time the President approves a new law.

-     Keep an up to date spreadsheet with the new legislations.

Traditional APIs

Media and agencies such as The New York Times, AP, Reuters, NPR and BBC have their own respective platforms with similar aims. Their APIs are focused on the possibility of sharing the journalistic content they generate for their partners.

The New York Times expands its book and film critiques with a semantic API to get information about people, events or places, in addition to access to its complete newspaper library since 1851.

On the other side of the pond, the BBC maintains extra interfaces based on its obligations as a public organization. It provides access to the broadcast times of its programs and information about them and their presenters.

Market data

Knowing the strata of the population to which the media are directed is paramount. The interests, intentions and motivations of citizens can help shape the resources of a story. There is nothing better for that than using the many marketing tools available to these departments.

Used for journalistic purposes, they become a powerful weapon. One example would be Facebook's Topic Data, information from the infinite social conversation that users have on the largest social network in the world.

Twitter, Instagram, Tumblr and other social platforms also offer this tsunami of rather accessible information through companies such as Dataminr, Gnip and DataSift. Companies specializing in capturing the full value of social data establish a privacy firewall. This acts between the networks where users interact and the end clients get access to them.

Are you interested in financial APIs? Discover all the APIs we can offer you at BBVA

Creado el 06 Jun. 2017

Numerous observers have identified chatbots as a potential replacement for native applications, representing a new primary channel for interaction with users. However, there has been less discussion of the natural evolution of APIs toward conversation APIs.

Conversation APIs are evolving out of existing interfaces for application development. Yet they are far more than just chatbots, and retain their API functionality. To some extent their role is unchanged; they serve as a vehicle for communication between applications, platforms and devices. But future versions of such platforms will be able to do this in a far more enriching manner. APIs capable of natural language processing.

From REST APIs to conversation APIs

Most companies around the world currently use REST APIs. These are app programming interfaces that harness only the usual HTTP requests (POST -create-, GET -read and query-, PUT -edit- and DELETE), and in response receive data in JSON and XML format. Such APIs have done a perfectly good job of exchanging data and supporting machine-to-machine connectivity. This has been true even in user interfaces designed for information exchanges between machines and humans. However, the natural evolution of such platforms should usher in the era of conversation APIs, capable of adding significant value to machine-human interactions, although they would make less sense in M2M data exchanges.

There are so many different concepts out there at the moment that they tend be lumped together in an amorphous mess in the heads of less tech-savvy users. The end result is largely the same, even though the processes and objectives are radically distinct. A user interface is not the same as a conversation user interface, and likewise an application programming interface (API) is different from a conversation API.

● A user interface is the platform that allows users to interact with an application or platform. Most current user interfaces are graphic (GUI), supporting interaction via screens or buttons. When such user interfaces are capable of interacting with humans, via natural language processing, they are conversation interfaces, or one of those chatbots that have caused such a commotion. A bot that is capable of answering users' questions.

● Application programming interfaces (APIs) are the perfect vehicle for interaction between applications and platforms. They exchange data. This is the norm for REST APIs. Meanwhile, conversation APIs support enquiries stated using natural language, the language that users speak. They exchange ideas, not data.

The evolution of conversation APIs

This is leading us toward a world in which two kinds of APIs coexist. There are those used to exchange data in internal processes, whether they be REST or other kinds of APIs, and those that serve to establish a new type of relationship with clients, first to provide them with commercial information using natural language, and secondly to establish real conversational interaction between user and machine whenever the latter makes any kind of query.

The future for such technology is users being able to make commercial or customer service enquiries via a conversation user interface, such as a chatbot. Conversation APIs will then be able to provide a response that is not merely made up of data or a dataset structured in a table, but a real answer using natural language that makes sense.

For example, in the banking industry a user might enquire after the origin of a specific charge made to their account on an exact date. In this case, the conversation API would access structured data and provide a response via a chatbot, which would go something like this: "The charge of 40 euros made on August 3, 2016, was for payment of dinner at Miramar Restaurant in Cadiz". This kind of information generation differs greatly from a jSON data structure:

“name”: “Juan”,

"surname": "Fernández",

“date”: “08/03/2016”

"amount": "EUR 40"

“balance”: “EUR 2,340”

Such enquiries are now well within the realms of possibility. Users asking for information should be able to get a natural response from APIs and conversational user interfaces. The difficulty is managing to ensure that these interfaces, and therefore the APIs that search, generate and provide the answers in natural language, are capable of holding real and unpredictable conversations with users. So that users get the feeling that the machine is human.

One technique that may lead to a major breakthrough in this regard is the so-called thought vectors approach, one of the latest developments from Google's groundbreaking guru in Artificial Intelligent, Geoffrey Hinton. Thought vectors allow numeric weightings to be allocated to words in their various contexts, helping machines to understand the meaning of words in different positions in sentences constructed by users. 

Thought vectors allow a context to be established around a specific line of thinking. By allocating numeric weightings to words and their contexts (the groups of words used around them), machines are able to understand the true meaning of messages as part of unpredictable conversations with users. Machines can thus follow a series of thoughts within a chain of reasoning. This would be true artificial intelligence.

Creado el 29 May. 2017

Alaska Airlines needed to compete with other major airlines like American Airlines and Delta, and given its lack of marketing budget, decided to place the emphasis on innovation.

Thanks to this change of course it became one of the first airlines to allow the introduction of electronic devices on its planes and offer its users a new way of enjoying their journey. It also pioneered the online check-in process, a move which made the airline company an electronic innovation leader.

The goal was to improve the user experience

Alaska Airlines was one of the first to develop an iPhone app to enable users to access their boarding passes, a system that has today been copied by many airlines. But this app was very limited at the start, and the user experience left much to be desired.

The executives at Alaska Airlines realized the app alone was not sufficient and decided to incorporate an API, as part of an initiative they called “Innovation at the Edge”. Their aim was to develop apps that offered their users and employees added value.

To achieve their goal, the company needed a API proxy that would carry out the work of security and management, both to receive incoming requests and to guarantee the operation of its back-end services. The API they used was CA API Gateway, because it offers flexibility and good integration between the development and test environment.

How has it improved?

Using this API they managed to create an app that has streamlined the boarding process while enabling passengers to check their flight status in real-time. This API has also allowed the Alaska Airlines partners to develop other apps to improve their customers’ experience:

  • Users can send an SMS with their dispatch number using Alaska Mobile Track to see the current status of their package.
  • And FlyingSocial enables Facebook users to access all current Alaska Airlines offers.

By implementing an API, Alaska Airlines has been able to securely showcase itself to others, thereby increasing its commercial activity.

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See other success stories with APIs





Creado el 05 May. 2017

The range of available APIs for developers is ever expanding. Turning to an external service that provides the tools that otherwise would have had to be built from scratch not only saves time but also resources.

Therefore, in order for those who turn to your API to be happy with the results, there is no need to provide them with all possible options; instead, it is important to make sure that your service is working properly and that there are no bumps on the road. The only way to fulfil this premise is to monitor its performance and consider possible changes to make it compatible with the software of third parties. Undoubtedly, the work becomes more difficult as complexity increases as well as the number of dependencies (components that the applications can use) of the API.

Thus, the key to assess the success of your API is to monitor traffic (incoming calls), the developers and applications that use it, the quality of service offered (this includes error rate, code failures and efficiency of responses) and the income provided by its use by third parties.

Resources: APImetrics, Visual Studio Application Insights and APIscience

Fortunately, there are different tools to keep an eye on your API and swiftly detect possible failures and solve them fast. One is APImetrics, a sort of scorecard from which to analyse different parameters of the programming interface.

This software solution allows measuring the time the API takes to respond to requests from apps, the effectiveness of its response and the reaction capability it presents for each dependency or type of call. Thus, it offers a holistic view of the performance of the service.

Another monitoring tool is Visual Studio Application Insights, available in the Microsoft Azure service. In this case, analysis includes checking data bases, HTTP calls, Java and databases, as well as the evaluation in real time of interactions between the API’s and the external interfaces.

It is worth noticing that the program facilitates the analysis of the response produced by a particular type of call, so that it is possible to evaluate if the versions of the API interface and those of third parties are compatible. On the other hand, faults and exceptions are detailed in the reports provided by the tool.


Turning to the past to understand the present

Unlike the previous ones, the kind of analysis provided by APIscience is staggered; it first evaluates the integration of external APIs with its own, and then assesses the results of their interactions. It serves to monitor, among other styles of software architecture, REST, JSON and OAuth APIs.

One of the main advantages of this tool is that it allows to compare previous versions of the programming interfaces with the current one, a comparison used to detect errors, slow responses and integration problems.

The tool is based on a system that monitors variations in the functioning of the API as well as its performance on the basis of time. Next, it represents the data by means of useful dynamic graphics. These reports help developers to analyse the code of the programming interface in search of possible errors.

Meanwhile, AlertSite offers a three-for-one solution, allowing to monitor the performance of the API along with that of websites and applications. For the first, the solution is called SmartBear, a complete manager of the status and health of programming interfaces. It is based on a network of nodes to monitor the speed of interactions and responses at a global level (it includes a map in the report of results), subsequently relating this flows to the degree of performance exhibited in each case.

Another useful feature of the AlertSite solution is that it offers different types of analysis adapted to third-party APIs, public APIs and those of partners, as each of them presents different problems. SmartBear also accepts scripts, so that internal assessment tools, such as Ready! API and SoapUI, are integrated into the service. Thus, developers can then execute these other services from the same product.

Ideally, a combination of tools

Although the existing tools and solutions are varied, the choice of one over the other should depend on the needs of each case. If only global assessments apply, and there is no need to look too much into the detail of the functionalities of the API, this latter may seem perfectly functional with respect to third-party applications despite being an outdated or obsolete version.

On the other hand, checking only the basic elements of the API, without considering the overall picture, it is also a partial approach. The best is to combine both strategies to achieve complete monitoring.

Are you interested in financial APIs?  Discover all the options offered by BBVA

Creado el 03 May. 2017

Data Validation used to send around 247 billion emails a day, i.e. it was as if each person received 38 emails per day. Using this platform, marketing teams can validate email addresses quickly and easily. This is a solution targeted at email service providers.

The sender's reputation is protected since invalid email accounts and spam are identified. The API also checks the capacity for delivering an email, loads lists of email addresses and identifies email addresses that are not valid. MailChimp is one of Data Validation's partners.

With the aim of improving user experience and expanding its services, Data Validation decided to implement an API. Also, this technology fulfilled the need for metric integration and usage limits.

Firstly, they created test accounts on several API management platforms. At this stage, they used various fictional APIs to check which of the platforms fulfilled their specific requirements.

They tested four tools and rejected two since they were too expensive and Data Validation did not want to make such as huge initial investment without being able to test the service.

Data Validation kept searching until it found 3Scale, an API administration platform that offers scalable and flexible solutions for packaging, distributing, controlling and obtaining benefits through the APIs.

At little cost, they were able to expand and improve their offerings to email service providers while their team focused on improving the product's functionality.

In short, the API played a vital role in achieving good resource management at a key moment in Data Validation's corporate strategy.

Results and benefits of using the API


  • Provides new aggregation criteria without disturbing the users
  • Improves the platform's recording/logging and use
  • Partners can use Data Validation's API by batches to automate and streamline how their users perform validation


  • Support for multiple applications in each account or user
  • Collection, measurement, billing and package scalability
  • Administration of an API with countless metrics and validation criteria

Data of interest

Founded in



SME: 11 – 50 employees




Marketing and Advertising

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Creado el 24 Apr. 2017

If we're developing apps that deal with information on books, we're going to have to take a tour of several fairly powerful and relatively open APIs. Although this is not very complicated terrain, some aspects, such as identifiers, are not as simple as they might appear.

Some years ago the standard book identifier was created so that publishers could automatically classify the books they issued. The ISBN (International Standard Book Number) began as a 10-digit code, and was extended to 13 digits in 2007. Both formats –10 and 13 digits– coexist, and have internal verifications to validate their structure.

The ISBN, including their control digits, can be a headache, so the best idea is always to verify the validity of your code before calling any API. A simple verification could be this:

function codigo_ISBN_valido (isbn) {

  isbn = isbn.replace(/[^\dX]/gi, '');

  if(isbn.length != 10){

    return false;


  var caracteres = isbn.split('');

  if(caracteres[9].toUpperCase() == 'X'){

    caracteres[9] = 10;


  var suma = 0;

  for (var i = 0; i < caracteres.length; i++) {

    suma += ((10-i) * parseInt(caracteres[i]));


  return ((suma % 11) == 0);


In addition to the ISBN, there is also the EAN (European Article Number) with which some publishers and commercial groups label their books. Then there is ASIN (Amazon Standard Identification Number) which the eCommerce giant uses as a unique identifier for every product in its catalog. Amazon also uses ISBN as ASIN, adding to the confusion of some novice developers.

Once we've learned the different standard identifications for books in the various APIs, we can begin to play with them. There are a wide range of free and corporate APIs with varying degrees of flexibility that will certainly allow us to find an application or book management for almost any need in our app.

ISBNdb: comparing prices

One of the oldest platforms, founded in 2002, has almost 8 million titles in its database. In addition to searching by identifier, its API offers the possibility of browsing by categories and obtaining the price of each title with different retailers.

If we look at this last aspect in more detail, according to the documentation we can make a request as follows:$CLAVE_API/prices/$IDENTIFICADOR

This will return a historic list of prices and retailers where we can find this product, and is useful for tracking changes in price or comparing between suppliers. The result would be a response in JSON:


   "result_count" : "2",

   "page_count" : 1,

   "current_page" : 1,

   "index_searched" : "isbn",

   "min_time_unix" : 0,

   "max_time_unix" : 1368820663,

   "data" : [


         "store_title" : "Principles of solid mechanics",

         "store_id" : "amazon",

         "currency_code" : "USD",

         "is_historic" : "1",

         "price_time_unix" : "1367763531",

         "is_new" : "0",

         "in_stock" : "0",

         "price" : "65.66"




Google Books: see content

The Google Books API is incredibly powerful and requires us to authenticate ourselves through a OAuth 2 protocol, not very complex, if we've worked with this secure method before.

It has three different parts. The first part allows users to search for chains of text among the millions of books Google has scanned and indexed. With the second part, these books can be embedded in web apps. Finally, the last part of the API offers a way of managing our own digital library with our own titles.

The text search is certainly the most powerful and interesting part. Once authenticated it can be accessed as follows: PHRASE

If successful, it will return the traditional headers HTTP 200/OK with a list of titles containing the phrase:


 "kind": "books#volumes",

 "items": [


   "kind": "books#volume",

   "id": "_ojXHRcCNuzg",

   "etag": "OTDqn42tB19",

   "selfLink": "",

   "volumeInfo": {

"title": "Libro de ejemplo",

"authors": [





  "totalItems": 3


It has programming libraries ready to use the API in almost any modern programming language.

Amazon Books

The vast catalog of Amazon APIs includes several related with the traditional book search that served as the basis for the service in its early years.

The eCommerce giant offers two related APIs in this category: ItemSearch and ItemLookUp. Both need an Amazon Web Services user account.

The first allows us to search and find books using multiple variables: title, author, publication date, ASIN/ISBN, publisher, etc.$AWS_KEY&

AssociateTag=$TAG_DE_AMAZON&Operation=ItemSearch&Keywords=$TERMINO_A_BUSCAR&SearchIndex=Books&Timestamp=[YYYY-MM-DDThh:mm:ssZ]&Signature=[Request Signature]

It will return an XML with the usual attributes of each book, in addition to a brief description:











        <Title>Título del libro</Title>



Once we've obtained these results, we can go to ItemLookup to see more data on the title or volumes selected. For example, the fictitious identifier B08OE6I000 would return the following result:













    <Title>Título del libro</Title>




With this second Amazon API we can obtain and verify extra details on each book or catalog item when we need to refresh the data. But it will generally be sufficient with the ItemSearch API.

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Creado el 20 Apr. 2017

Technology has permeated into every aspect of everyday life, both at work and in our personal lives. Perhaps you look at your tablet first thing in the morning to check the news, have a coffee brewed by your latest generation coffee machine, head to work in a car that would impress even Michael Knight from Knight Rider, and so on throughout the day. In fact, there is practically nothing that we do on a daily basis that is not underpinned by some kind of technology. However, do you know how many of these activities also conceal an underlying API?

Programming interfaces make life so much easier for programmers and developers, and for you too. Below is a list of things that you may be surprised to find out have an API running under the hood:

  • Home: Imagine a house that you can control completely via your smartphone, even when you're not at home. And now stop imagining, because this is no longer the realm of fiction. The Samsung Smart Home gives users control over any domestic appliance or home device connected to Samsung, whether it be the fridge, oven or TV, all thanks to an API operating in the cloud. Full information on this API for the home can be found here.
  • Siri: The Apple personal assistant that reacts to natural language, and can answer questions and provide recommendations, uses a private API only available to Apple developers. The Siri API has two functions: the first to reveal what actions are available, and the second to offer a means of running said actions. Despite huge demand among developers, this API for third parties would be very difficult to run in other environments. More information on how it works.
  • Play Station 4: The console already uses a number of APIs, and a new one, called Vulkan, is now set to be included. This multi-platform API is used to develop applications with 3D graphics. This means Play Station will be able to compete directly with DirecX12, the API used by Microsoft for its Xbox. Vulkan allows developers to harness the full potential of the console's hardware, with one such benefit being a higher frame rate per second, thus providing a considerably superior visual experience. This article discusses how it works in greater detail. As well as consoles, video games also harness APIs to support social network-style features.
  • Roomba vacuum cleaner: That's right, even vacuum cleaners can use APIs. Roomba, the vacuum cleaner that works autonomously, is supported by RooWifi (1.1) as it goes about its various cleaning functions. The API is compatible with Windows, MAC, GNU / Linux and other operating systems. The latest version of the API can be cloned from a Github repository or downloaded directly in a compressed ZIP file. Full details are available here.
  • Sony digital cameras: Sony digital cameras use a beta API called “Camera Remote”, which provides wireless access to the devices. The API allows users to manage several Sony cameras from a different device and control aspects such as the zoom, remote display and automatic timer, as well as take photographs and record videos. More information on the Camera Remote API is available at the Sony developer site.
  • Cars: Self-driving cars that interact with users are now a reality. Vehicles are increasingly connected, ranging from voice interaction through to storing favorite routes. Such features are supported by hidden APIs. A couple of examples include Dash Chassis API, a connected vehicle platform that provides access to fuel usage, cost and efficiency information, and GM Developer API, a programming interface that can be used to unlock doors, activate the car alarm and access data on the subscriber or the vehicle.

These are just a few everyday examples of activities underpinned by hidden programming interfaces, but many more ordinary objects also operate thanks to APIs. Smart Cities likewise benefit from them.

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Creado el 18 Apr. 2017

Learn how financial institutions are betting on the Big Data and Artificial Intelligence through APIs that help banks to define products, segmenting customers and detect possible fraud. Throughout this ebook we offer a review of the APIs bank data aggregation it is done, and Paystats, BBVA API that provides information to third parties so that they can provide services and apps that add value to the customer is presented. In addition, we analyze how banks are adapting to consumer information through various mobile devices and how they are redesigning the services they offer to their users.