Intel, Toyota and Ericsson Join Forces in the Big Data Car

To exploit the enormous amounts of data generated by connected cars, a handful of industrial players (including Toyota, Intel or Ericsson) have agreed to adapt edge computing, a method of data exchange using new network infrastructures and in order to exploit BigData in the automotive sector.

With the advent of autonomous driving, connected cars promise to generate billions of gigabytes of data that will not only store but know how to exploit to pull the full essence of this pool of information.

Before this, it will also be necessary to make these data intelligible and exchangeable. Intel has agreed with Toyota, NTT Docomo, Ericsson or Denso to collaborate to facilitate the exchange of this data in the cloud.

These players recently announced the <a href="http://newsroom.toyota.co.jp/en/detail/18135029/&quot; target="_blank" rel="noopener"

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To exploit the enormous amounts of data generated by connected cars, a handful of industrial players (including Toyota, Intel or Ericsson) have agreed to adapt edge computing, a method of data exchange using new network infrastructures and in order to exploit BigData in the automotive sector.

With the advent of autonomous driving, connected cars promise to generate billions of gigabytes of data that will not only store but know how to exploit to pull the full essence of this pool of information.

Before this, it will also be necessary to make these data intelligible and exchangeable. Intel has agreed with Toyota, NTT Docomo, Ericsson or Denso to collaborate to facilitate the exchange of this data in the cloud.

These players recently announced the creation of the automation consortium Edge Computing, which has set itself the main objective of working on data generated by intelligent vehicles.

“The goal is to develop an ecosystem for connected cars to support emerging services such as smart driving, map generation with real-time data, and cloud-based driving support,” reads the statement issued by Toyota.

The Automotive Edge Computing will focus on increasing the network capacity to accommodate the large volume of data that will land in the coming years. The consortium plans to invite “world leaders in the technology industry” to join its ranks in the coming months.

The premise of the Automotive Edge Computing is based on the belief that all connected cars will send 10 exabytes of data per month by 2025.

According to the founding members of the agreement, this will require a new architecture for the networks and machines that will have to process all this data. With edge computing, the consortium imagines that it can find a solution based on a technology whereby the data is first processed locally and then transferred to the cloud.

When Search Becomes the Business Advantage

The data companies need for their processes are becoming more and more complex, heterogeneous, and unstructured: they no longer fit into the predefined data structures provided by many database technologies.

This new data landscape is not about storing data, but rather about finding new and better ways to make the growing data treasures useful for business purposes. Companies need to look beyond the boundaries of static applications and repetitive data queries. In order to use all available data, users need a real-time tool – so that inquiries can arise when new ideas arise and new data sources allow new questions.

Exactly for this challenging search was created. And yet, only a few searches see as a fundamental answer to their business challenges and as a basis for new business solutions.

More and more advantages with search

Databases and data storage will n

The data companies need for their processes are becoming more and more complex, heterogeneous, and unstructured: they no longer fit into the predefined data structures provided by many database technologies.

This new data landscape is not about storing data, but rather about finding new and better ways to make the growing data treasures useful for business purposes. Companies need to look beyond the boundaries of static applications and repetitive data queries. In order to use all available data, users need a real-time tool – so that inquiries can arise when new ideas arise and new data sources allow new questions.

Exactly for this challenging search was created. And yet, only a few searches see as a fundamental answer to their business challenges and as a basis for new business solutions.

More and more advantages with search

Databases and data storage will not be a thing of the past. Transactions are the focus of business and transaction systems are best managed in a relational database environment. In addition, many companies have already invested large sums in ERP, CRM, and other relational business systems and will continue to try to squeeze non-transactional data into tight structures.

Much faster is the source, from which companies gain competitive advantages. The older the relational business applications, the less efficient they deliver. Although these systems are often an integral part of the business, they offer less and less competitive advantages.

This is where dynamic applications come into play that builds on search. They serve companies as valuable new sources of insights with which they can stand out from the competition. Many leading digital transformation companies are already using Search to rebuild their customer services through deeper insights.

Thanks to search-based applications, users can link different records to provide a comprehensive overview of given situations. An underlying logic defines data, but this is no longer restricted or tied to individual applications.

A clear overview of the connections between heterogeneous data from different sources can be obtained without difficulty. And new data from new sources can be added at any time, giving users an increasingly better understanding of the overall picture and giving end users innovative features.

The insights of the search are increasingly used internally in the banking and financial sectors, whether for the operation of data centers, monitoring applications or information about cyber threats; By monitoring card and ATM transactions and fraud detection; In human resources, recruitment and customer analyze.

It is particularly clear that the use of data searches for new business areas, whether for internal insights or the provision of innovative digital services for customers, is quickly becoming one of the most important modern competitive advantages for companies across all industries.

Data Analytics in Clear Language

You have allocated a budget to innovate; you’re on the verge to work with the new “oil” Data. You decide to take data scientists. A good start, and now? Where to begin? What tools they should use and what data sources are appropriate? What is the duration of a data science process if the result is acceptable and how you bring a beautiful model in practice?

Big Data, Artificial Intelligence, Machine Learning, Deep Learning; Nowadays you can not ignore. But … what do these terms actually is and how it is used in the business?

What is Data Science really?

In recent years, the amount of collected and available data grew exponentially. Until 2020, the data will grow by approximately 42% per year. Here we not only talk about data and numbers in tables (structured data) but also documents, chats, posts, photos, videos, audio clips, etc. (<a href="https://learningsimp

You have allocated a budget to innovate; you’re on the verge to work with the new “oil” Data. You decide to take data scientists. A good start, and now? Where to begin? What tools they should use and what data sources are appropriate? What is the duration of a data science process if the result is acceptable and how you bring a beautiful model in practice?

Big Data, Artificial Intelligence, Machine Learning, Deep Learning; Nowadays you can not ignore. But … what do these terms actually is and how it is used in the business?

What is Data Science really?

In recent years, the amount of collected and available data grew exponentially. Until 2020, the data will grow by approximately 42% per year. Here we not only talk about data and numbers in tables (structured data) but also documents, chats, posts, photos, videos, audio clips, etc. (unstructured data).

To take advantage of these data, it is important to translate these data into useful information. The transformation of the quantity of data to information is done through data analytics. This newly acquired knowledge can then be used to make-driven systems, processes, and decisions.

Data Analytics Process

An average data analytics process can be divided into three phases: data processing, transformation, and visualization.

The process starts with the business itself, where a set of data is available where information can be removed. You can consider data from your customer base, from financial systems or, for example, logistics administration. It is also possible to integrate external data sources into your analysis, such as weather data and social media.

Processing

In this phase, there is scooped outline in a large amount of data is present, so that it can be used for the transformation and the visualization step. This processing phase is the most time-consuming, it takes on average 70% of the time. During this period, the data is put in the correct format.

Transformation

During the transformation phase, different data are combined and transformed into analytics models. In this way, new information extracted from the data. The analytics models search for hidden trends and relationships so that you understand about your business.

Visualization

In the visualization phase, the results of the transformed data will be made transparent to the user by means of visualization. By using the appropriate visualization methods and tools, it is possible to understand and use the information hidden in your data.

Google is Now Measuring Air Pollution in the US Cities

Google has used its Street View vehicles to measure air pollution in US cities. The first result of the study was the detailed maps of Oakland, California, where the dioxin and CO2 exposure is highest.

The cars of Google Street View can do more than just take shots from the streets of this world. In Oakland, California, Google has used its vehicles for the study High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data to capture air pollution in the 400,000-inhabitant city accurately.

[youtube https://www.youtube.com/watch?v=mFnE8r0RoYg%5D

For the project, Google collaborated with the University of Texas at Austin, the NGO Environmental Defense Fund (EDF), and the company Aclima. Between May 2015 and May 2016, street-view cars drove a

Google has used its Street View vehicles to measure air pollution in US cities. The first result of the study was the detailed maps of Oakland, California, where the dioxin and CO2 exposure is highest.

The cars of Google Street View can do more than just take shots from the streets of this world. In Oakland, California, Google has used its vehicles for the study High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data to capture air pollution in the 400,000-inhabitant city accurately.

For the project, Google collaborated with the University of Texas at Austin, the NGO Environmental Defense Fund (EDF), and the company Aclima. Between May 2015 and May 2016, street-view cars drove a total of more than 25,000 kilometers across Oakland and collected specific airborne data in the metropolitan area using special sensors. Typically, such data is determined with fixed stations, and Google vehicles have been given the opportunity to work much more precisely thanks to their mobility.

During the study period, the vehicles rolled an average 30 times over each street in Oakland, resulting in a total of 2.7 million measurement points. Google generated an interactive Google Maps card that the EDF published on its website.

google_maps_pollution

The environmental organization shows which streets the exposure to CO2 or nitrogen is the highest. As you would expect, the values on and in the vicinity of Highways are the highest as heavy trucks drive along the way.

High buildings also ensure that people are exposed to health risks because the fresh air exchange is disturbed in such areas. Due to the high levels of air pollution, there are twice as many asthmatics in Oakland as Alameda County, also located in the San Francisco Bay Area.

According to a blog post from Aclima, the study was a pilot project to be expanded in the future. The company, which offers sensors and cloud solutions among other things, reached an agreement with Google in September 2015 that the street-view vehicles in other US cities should measure the air pollution.

To date, the converted cars have driven nearly 130,000 kilometers through California to collect data for further environmental studies in San Francisco and Los Angeles. They are to be published in the coming months.

DataLakes: Bringing Big Data to Your Organization

With the creation and management of DataLakes, companies will grow up to 317% due to the exploitation of large amounts of data supported in better decision making and the development of more competitive companies.

With the objective of overcoming the challenges of administration and handling large amounts of information in organizations, today there is the implementation of what is called DataLakes.

The DataLakes are repositories of large amounts of data that help companies generate additional value in operation and organization of all this information.

By 2020, it is expected that there will be 40 Zettabytes of information, meaning each inhabitant of the planet will contribute 5,247 GB of information. These data will be generated by what is called IoAT (Internet of All Things) – sensors, intelligent cities, etc., through the mobile teams and interactions with the Internet of the people and in the organ

With the creation and management of DataLakes, companies will grow up to 317% due to the exploitation of large amounts of data supported in better decision making and the development of more competitive companies.

With the objective of overcoming the challenges of administration and handling large amounts of information in organizations, today there is the implementation of what is called DataLakes.

The DataLakes are repositories of large amounts of data that help companies generate additional value in operation and organization of all this information.

By 2020, it is expected that there will be 40 Zettabytes of information, meaning each inhabitant of the planet will contribute 5,247 GB of information. These data will be generated by what is called IoAT (Internet of All Things) – sensors, intelligent cities, etc., through the mobile teams and interactions with the Internet of the people and in the organizations.

However, the sector faces several problems today: more than 80% of information is not used for decision making, which is called “blind spot.”

The cost of storing information in Data Warehouse, relational databases or SAN-type infrastructures is highly costly and scarcely scalable. To grow 20% of the shelf space, projects are carried out with a duration of 3 to 6 months.

DataLakes architectures ensure that the organization collects information from internal or external data sources at rest, On the move or in data warehouses to be processed and exploited so that the organization is able to react and make decisions before things happen.

It will get companies more competitive and organizations with more capacity for reaction in the face of the vertiginous changes in the Information Technology sector and also in our society.

Today’s large IT companies like Google, Facebook, LinkedIn, Twitter and Netflix have developed technologies to collect, safeguard, process and exploit their data. These technological tools have been evolving and have led to other sectors showing significant benefits.

One of them is the growth of up to 317% of companies that support their business in the exploitation of large amounts of data in DataLakes architectures.

All that data universe called Big Data will be the differentiating variable of success, since all decision-making processes are supported in as much information as possible, giving a competitive advantage to organizations that have the ability to analyze and understand the largest amount of information. The cost savings in DataLakes architectures vs Data Warehouses is 15% of what organizations currently invest.

How do companies spend?

Big Data tools are helping organizations understand the tastes and buying habits of their customers. With DataLakes, they offer great discounts in the major moments to increase their sales, turning sales into personalized experiences.

How do they operate?

Big Data implementations lead organizations to make decisions in terms of their value propositions and operations, seeking to make their productive processes as effective as possible.

An example of these implementations is in the monitoring of gas or energy networks to understand the state of the network and consumptions in real time to maximize their distribution and provisioning of the service, even detecting problems before they happen.

How to minimize risks or seize opportunities?

Identifying unusual events, anomalies or incidents that can be exploited or controlled by the organization is a fundamental implementation of analytical models of large amounts of data.

Understanding how your organization works, allows you to predict and counteract computer attacks, fraud and service failures. Anomalies or incidents that can be exploited or controlled by the organization is a fundamental implementation of analytical models of large amounts of data.

Total Intelligence: The New Era of Travel

Traveling has always been one of the most rewarding experiences for people. Travel is that situation where people are encouraged to explore places, its inhabitants, cultures, and gastronomy different from those that live day by day.

Historically, a trip began with planning: buy airline tickets, book hotels, search for the main attractions and keep in mind those places that could not be missed. All this is what was originally called “pre-trip” and was one of the most important stages of the process.

Once in the destination, and you are already in the “in-trip” stage, only look for a place for the enjoyment. You take enough photographs, tour and visit different attractions to meet local people and enrich the experience.

Once you are back from the trip, it is nothing compared to the feeling of having the photos revealed and share the experience with friends and family. It was the “post-trip” stage, and for many, it is the most significant.

With the advancement of technologies

Traveling has always been one of the most rewarding experiences for people. Travel is that situation where people are encouraged to explore places, its inhabitants, cultures, and gastronomy different from those that live day by day.

Historically, a trip began with planning: buy airline tickets, book hotels, search for the main attractions and keep in mind those places that could not be missed. All this is what was originally called “pre-trip” and was one of the most important stages of the process.

Once in the destination, and you are already in the “in-trip” stage, only look for a place for the enjoyment. You take enough photographs, tour and visit different attractions to meet local people and enrich the experience.

Once you are back from the trip, it is nothing compared to the feeling of having the photos revealed and share the experience with friends and family. It was the “post-trip” stage, and for many, it is the most significant.

With the advancement of technologies and mainly with the massification of smartphones, that process “pre-en-pos” journey has changed drastically.

The Total Intelligence

Today, only air tickets have a precise relationship to the anticipation of demand, but the trend is increasingly marked that hotels, attractions, and experiences to live are chosen once in destination and based on the recommendations that other travelers have realized.

Memories are kept in posts on social networks like Facebook and Twitter, Which allows visitors to express their conformity (or disconformity) instantly with certain aspects of the experience. It reconfiguration forces us to rethink the way in which from the industry we approach the travelers.

We can identify at least 5 technology events that make possible a new way of managing travel.

Internet of Things

With Internet of Things, millions of connected devices manage to generate a quantity of information never before imagined by the human being.

At the same time, the phenomenon of Social Networks exposes billions of contents, texts, images, videos that represent in a disorderly way qualitative aspects of the people and that allow us to understand states of mind, interests, opinions, values, Influence groups, etc.

Big Data

The events mentioned above could not accomplish their task without the ability to store and process large volumes of data. Only with the advancement of these variables can the known “Big Data” offer its advantages, making it possible to efficiently and efficiently store a quantity (and variety) of data never before imagined.

These events as a whole give us the possibility to act and intervene the 3 characteristics of the new configuration of the trip. Demand, Experience, and Relationship.

Demand

Each day, we face the challenge of achieving an efficiency of resources invested in developing and promoting it. The air supply today is such that it allows us to move with a simplicity perhaps never before seen.

The beaches of northern Brazil are as accessible as CancĂșn or Dubai and that the Colombian coffee industry is as attractive as the wine route on the west coast of the United States. This is where Destination Marketing Organizations and government advocacy organizations have the biggest challenge.

Working on demand means understanding which markets are my competitors, which are the most attractive markets with the greatest potential for growth.

It leads to the intention to buy these markets, the anticipation with which passengers buy their tickets, average duration, pleasure or business, sales channel and specific behaviors by home market.

These are the variables on which any destination should start working today, and they should keep in mind that there are already destinations that do it very well.

Experience

Internet of Things gives destinations the possibility to know a little more about their visitors even without asking them. From information from Facebook’s public profiles to eating or sporting habits that a person can have and express through the use of smart watches.

Imagine as a passenger that the destination welcomes you and recommends, the 10 best places to perform your morning routine exercises in the city.

The information gives us ways to improve the experience of people with a relatively low effort. For many visitors, these benefits are more than enough to provide compliance that is responsibly shared information.

In this sense, organizations can provide the tools to mold the basic experiences and allow the traveler to discover possibilities that he had not thought existed in this destination. The role in creating experiences (Product) can not be delegated and must be central to a destination because it allows diversifying the attractions and thus captures the attention of more diverse stakeholders.

Relationship

Technology also gave the traveler the ability to express their appreciation of the experience in real time, and that also forces us to adapt the way we relate to them.

A post on social networks can encourage or make a decision change to future visitors in just seconds. This is where the way in which the destinations relate to their guests becomes unimportant.

Since a process of communication and promotion of destiny begins, the relationship must be thought in the long term, not only to attract people in a specific situation but also because they will become “ambassadors” promoting and recommending the experiences to other interest groups.

Finally, the relationship in time of a destination with a client is not very different from what any other brand would like to have with it and that over time the number of interactions (visits) increase.