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Technology

Home ownership is everyone’s dream. We spend a lot of time finding the best property for us. Consequently, it is one of the crucial decisions of our lives.

Real estate clients have enormous needs for as many insights as possible. In other words, they want to acknowledge the surrounding, transportation, to compare it with other options, find out the nearest mall, kindergarten or school.

Home key | New home| A man giving a new home key to a owner| real estate buyer

Real estate challenges

Real estate businesses are developing globally. Real estate industry, like other markets, faces a lot of real estate challenges. Interestingly, here are some of the substantial real estate challenges; to decrease the risk of buying a wrong property, to cut time of finding the right home, to develop a practical business approach, and to come to a buying decision easier. Most importantly, for investors, it’s important to make sure, that they invest in the right property, which represents the real value of its advertisement.


World leading real estate companies has already accepted the challenge of using new and innovative technologies, which is, in fact, the need of your customer in a contemporary market.


Most discussed tech challenges for real estate are A/B testing, machine learning, business intelligence (BI), and cloud computing. Big Data and analyses are changing all the imagination about real estate challenges.

 

What does big data mean for real estate data visualization?

Big data is a large volume of structured and unstructured data. Big data is usually collected from a large amount of information. The information often comes from the recent analysis.

The other interpretation of Big Data is Business Intelligence, which uses statistics to measure items and find out new trends.

Data visualization can help real estate companies track the actions, assess risks, optimize the process, analyze, and get the visualization of GEO analytics.


Why visualize real estate data?

Visualized Data has a lot of benefits for real estates.  Real estate data analyzing is an essential factor when buying or renting the most desired property.

BI helps us get visualized context which is more straightforward for an eye for obtaining the information. It shows infographics, charts, pies, as well as maps.

This is a de facto standard for modern business intelligence (BI)

It Cuts Your time

A watch in a hand. Drinking a cup of coffee. ofee

WIth data, you reduce your agents and brokers time, and the money You need to pay them for finding the best home for customers. Sometimes the process takes a long time. For example, the price for a car to accompany your home buyers for the first view. You can have all AI data of the view from the house, the malls, the kindergartens. With data visualization, the buyers will get all the answers regarding the property. If a buyer doesn’t have any interest in it, you will not visit the house. If you’re a realtor, you’ll evaluate, that this is a time-consuming process, and cutting down this, undoubtedly, is beneficial. You will make sure that you don’t wast your time for the wrong options.

Personalized experience

Losing one real estate buyer will cost too much for your company than paying a company to create Mapbox for You. If you don’t give personalized experience, there is a lot of chances to lose the potential client.

Now it’s easy for you to create software that can help your customers reveal their expectations and housing aspirations, as well as to uncover the types of ideal buyers. As a result, this will help you improve your targeted marketing.

It makes Your realtors’ life easier

Salesman | Sales manager | A businessman sitting at the office with notebook|

Does the house have a garden? Whats the facade like? Is it close to a bus station or a subway? We know how it feels, and sometimes you are becoming tired of these questions. It’s better to show the property than to speak about something intangible. Your customers and brokers will appreciate your care. 

 

Be an innovative real estate agency

Innovation | Innovative lamps| Innovative real estate

In the contemporary market place, businesses are dying without taking the chance to innovate their approach. Real estate numbers are increasingly growing, and the ones who are innovative will survive, unlike the others who are doing dinosaur marketing.

It reduces financial risks

Data visualization helps real estates to track investment details. For example, it’s easy to find out whether the home repaired recently or not, to uncover the status of loans and investment.

FIlters and comparisons

Sometimes it’s hard for customers to remember all the aspects of the home they have seen. Their lousy experience of recognizing the ideal house for them will turn into disappointment. Data visualization will help you always compare each aspect and find the best set of variables for the client. For example, if John wants to buy a house he can view the prices of properties which are located on street X, he can compare it with the features in Y location. He can see the pros and cons of these houses. Also, the homes in X location are cheaper, but they are way more far from the station, consequently, but this one has a beautiful balcony in comparison with the houses of Y location.

 

The importance of data visualization tools?

Data Visualization | BI-business intelligence| Data on A notebook screen

Digital Map market revenue is projected to grow in a short period. The reason for this is that smartphones, and other mobile devices or navigation tools have their specific role in each aspect of our life.

Data visualization tools are essential for getting analyses, data-driven insights for the workers through organizations. Data visualization software also plays a vital role in big data and advanced analytics projects.

Visualization software is based on customers behavior and needs. It helps them find their desired home. They can discover how many bedrooms it has, what the neighborhood looks like, does it feel like their home?

 

What is the best data visualization technology?

The most common Data Visualization software which is excellent for maps is the combination of Mapbox and Deck.gl.

What is Mapbox

Mapbox is a solid provider of the best online maps for websites and applications. First of all, It helps developers to create smooth, fast, on the other hand, its a real-time map. It includes more than 130 multi validated sources for a world map. Map APIs get 5 billion requests per day. A dozen templates are available for you to choose.

Data visualization example for real estate. What is data visualization? Real estate mapbox.

What is Deck.gl


This is a data visualization tool. Many web applications, like Uber, are based on it. Above all, Deck.gl is created with React JavaScript library. 

Deck.gl data visualizatiom

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The article is written by Gayaene Melkumyan

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Earlier this summer at Locate, we announced our partnership with Uber’s data visualization team to integrate deck.gl with Mapbox. Our mission is to build incredible developer tools that help us understand and explore our world. Today we’re launching an integration between Uber’s data visualization library, deck.gl, and Mapbox GL JS. This means developers can add more types of data to their maps — with less code and higher performance.

At Great Department, we have a solid experience in creating amazing maps and data visualization (mapbox + deck.gl.

Let`s speak about Your Next Project

For those new to visualizing data with deck.gl and Mapbox, deck.gl is an open source geospatial analysis toolbox built on top of Mapbox GL JS that makes understanding location data simple. This toolbox is used to visualize massive datasets without compromising performance, from mapping hundreds of millions of trips as a ridesharing company to analyzing network models and cellular coverage as a telecommunications company. Together, we’ve made it easy for developers to add any of the beautiful data visualization layer types in deck.gl to a Mapbox map.

 
Add deck.gl 3D hexbins to visualize the density of road incidents — try the live demo.

This integration is powered by a new feature in Mapbox GL JS v0.50: Custom Layers. Custom Layers works with popular WebGL rendering libraries like deck.gl and three.js for adding 3D models, data visualization layers, and animated scenes. This enables developers to render a WebGL scene directly into the Mapbox GL context as a layer, giving full control over what’s brought into the map — whether that’s a 3D CAD rendering, a SpaceX rocket launch simulation, or a GLTF solid model.

Here are a few visualizations enabled by Custom Layers that we’re most excited about.

Deck.gl data visualizations

Before Custom Layers, visualizations with origin-to-destination great-arc circles were difficult to create. Deck.gl arc layers make this easy.

The visualization below shows US migration patterns between cities. Mouse over each city to visualize the volume of people moving to other areas of the US. Blue lines indicate net migration into a city, while red lines indicate net migration out. Not only can users clearly see city labels above their data, but developers can create this visual by adding a deck.gl layer at runtime.

 
Add origin-to-destination great-arc circles to a map. Try the demo.

To add arc layers to your Mapbox map, follow the example from deck.gl’s Mapbox layer docs:

Deck.gl has many more advanced data visualization layers you can add to a Mapbox map, including point clouds, contours, and more, enabling you to build the best visualization for your location data.

3D models

Developers have long requested full support for 3D models in Mapbox GL JS. With Custom Layers, it’s easy to add 3D models to a Mapbox map with three.js.

Andrew Harvey of Alantgeo created a basic example of how to load a GLTF 3D model and render it under a label layer. Prior to Custom Layers, developers had to manually work with coordinate matrix projections to synchronize two WebGL canvases for the map and the 3D model. Now, developers can control exactly where the model is placed in the scene, and Mapbox handles the synchronization of the model with the map while the user pans and zooms.

 
Add a three.js GLTF solid model to a Mapbox map as a Custom Layer. Try the demo.

What’s next

deck.gl data visualizations and three.js 3D models are just the beginning of what’s possible with Custom Layers. To get started with deck.gl and Mapbox, head to the deck.gl + Mapbox docs. And to start building with Custom Layers in GL JS, check out our developer example and documentation.

Want to have amazing mapbox and deck.gl data visualization? WRITE US NOW and we will help You create amazing maps.


Article by https://blog.mapbox.com/launching-custom-layers-with-uber-2a235841a125


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