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Add Pop-ups to your CARTO Builder Maps

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When working with dynamic maps they often contain an interactivity layer on top of the data, which allows you to click on different geospatial features to get more details about them like: how many products are sold in a particular store, how many people live at a specific location, and what is the core demographic of this region. CARTO Builder’s pop-up feature helps deliver these data insights as meaningful information.

Pop-ups in Builder are what we called “infowindows” –components that show you data about a particular feature– in the Editor.

To create pop-ups in CARTO Builder you just need to go to a layer, click on the pop-up tab, and select the data—and the style for your pop-ups—that you’d like to use either when clicking on a feature or when hovering over them.

Hover pop-ups are typically used to show very straightforward metadata, while pop-ups that open by clicking are intended to explain metadata about the features in detail. We’ve curated some beautiful styles in Builder that will help you with most of your data, and you can always go and edit the HTML of the pop-ups yourself.

Happy data analyzing!


Creating Animated Maps with CARTO Builder

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Temporal data representation is a great way to communicate information with both style and analysis. With Torque.js, data can be aggregated either in time or space.

CARTO has invented a completely new way of aggregating geospatial data for both time and space and this functionality is something that you can continue to use in CARTO Builder.

As you browse the different aggregation methods, you will notice that there is one method that will let you aggregate your data by time. This causes your data to become animated. You can animate your data based on a date type or numeric column. Also, an addition that we’ve included in CARTO Builder is a histogram chart, which substitutes for the old Torque scrub bar. Now you can see the distribution of your data over time, filter between two dates, or just animate it like in the good old times.

Time aggregations are very useful to find, show, and understand temporal trends such as seeing how the world reacts to a particular topic, or how your business expands in new locations.

Happy data analyzing!

Empowering the Democratic Process through Location Intelligence

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The power of the people starts at the hyper-local level and technology is driving new expectations on how media and campaigns view citizen participation. In today’s political climate, citizen engagement is more influential than ever and much of the interaction is taking place in the digital world. Our friend and partner, Alteryx a leader in self-service data analytics, developed a solution with CARTO to visualize data, down to the neighborhood-level, to help predict behaviors and focus campaigns.

The Decision 2016 Presidential Election application, which incorporates SurveyMonkey’s election tracking data and other data sources like the American Community Survey, can forecast the U.S. presidential election at the local level with the ability to segment further while considering demographics including age, education, income, and race.

The application, which uses our CARTO.js library to create dynamic maps updated based on user input, allows for a unique drill-down to the the census tract analysis of presidential preference. The tens of thousands of records from SurveyMonkey are combined with other data to develop a uniquely-focused, proprietary model designed to accurately forecast electoral preferences at the very granular Census Block Group level for the 2016 U.S. presidential election. With over 74,000 census tract possibilities, Alteryx was able to create an application that creates custom maps to visualize all of those possibilities.

Alteryx election app workflow

When combined with location intelligence, political parties can create incredibly robust profiles to identify and serve more relevant messaging to likely supporters. All of this enables political parties to construct real-time voter profiles at scale, creating efficiency while moving them closer to their ultimate goal: getting people to the polls. In fact, on Election Day, supporters can be re-targeted with messaging showing the nearest voting locations, hopefully giving them the motivation to get out there and vote. Win or lose, each party is gaining valuable insights that are applicable to future success.

Put CARTO technology at the heart of your successful elections and campaigns. In a rapidly changing world, take advantage of modern maps to effectively serve the public and meet expectations. From operations and public outreach to redistricting and campaigning, location intelligence can empower your organization to create and deploy useful geospatial applications to navigate this election season. Visualize relationships, patterns, and trends to deeply understand your constituency and electoral process.

  • As technology partners, CARTO and Alteryx have teamed up to provide an engaging, intuitive experience for visually analyzing and interacting with Alteryx workflow outputs on a beautiful, dynamic CARTO map. Learn more about CARTO’s Alteryx Connector and how to maximize analysis and extract the most from location intelligence.

Explore with Widgets in CARTO Builder

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CARTO Builder is becoming the easiest tool to predict and discover insights behind your location data. Making decisions using data-driven maps means more than just visualizing points or polygons. After plotting data in your maps, the real analysis begins as you employ widgets to visualize information in different ways and calculate aggregated values for particular areas.

Widgets are an integral part of CARTO Builder’s experience and workflow. Not only do widgets filter data but they also update the styling of that data and initiate analysis. At their core, widgets allow users to question their data further and discover answers more readily with modules that can visualize, aggregate, and filter data. These intuitive modules can be used in many different ways by either clicking on the widgets tab, or by clicking on the different columns that appear under the data tab on each one of your layers. The widget results will reflect the data you see in the current bounding box view.

Users can customize their apps with CARTO Builder to filter data through:

  • Formula Widgets calculate aggregated values from numeric columns in AVG, MAX, MIN, SUM, and COUNT - support for text columns is on it’s way!
  • Histogram Widgets can examine numerical values within a given range distributed across your data map.
  • Category Widgets allow users to ask different context-based questions of a dataset.
  • The Time Series Widget allows you to set a temporal parameter upon your data to display across time.

Another very powerful feature of the Widgets is the auto-style button - which you can identify by the drop icon in the top right of the Widget. Select auto-style to apply a new temporary color ramp to the widget data. This is useful for better visualizing the widget results. As you continue to filter your data by using widgets, the color scheme applied during the auto-styling will be maintained as the map recalculates and renders based on the parameters you set with the widgets.

Adding widgets to your maps opens up the possibility for exploring your data in a new way, in addition to providing insights that facilitate predictive analysis. The user experience is characterized by a unique, new level of engagement and interactivity with the data while continuing to function quickly and efficiently.

Now, finding the highest value in an area, for example, when looking at filtered data, is only a few clicks away!

Let us know what you come up with. We would love to see it!

CARTO’s New York Summer and Fall Interns

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We are very happy to share with you the news that we have added several experienced individuals to the CARTO family, to fuel our growth as the leading location intelligence platform.

Mehak

Mehak Sachdeva

CARTO Education Intern

Mehak is one of our new interns and was previously interning at the New York City Economic Development Corporation. Prior to that, she was a Graduate Teaching Assistant for Advanced GIS in the Urban Planning Department at Columbia University.

“As an urban enthusiast, what excites me the most about working at CARTO is the collaboration between technology and research to spatially locate and understand problems to help solve them for a better world.”

She’ll be working with our Data Research team to create new and innovative ways to train and educate our users!


Michelle

Michelle Ho

Data Research Intern

We are also excited to welcome Michelle Ho to the team. She’ll be interning with our Data Research team and comes to us from the New York County District Attorney’s Office where she was a Technology Analyst.

“I’m excited to bring data to life with the CARTO Data Observatory.”


 
   Peter 

Peter Murray

Content Marketing Intern

Peter is our newest intern on our Marketing team where he’ll be specializing in social media content and strategy. He’ll be creating exciting content that will engage and influence our present community while attracting a broader audience. He’ll also be working on our blog. He is currently completing his PHD in English at Fordham.

“Joining CARTO provides me the opportunity to learn new writing styles and genres appropriate for web content, as well as teaching me new ways in which to understand the relation between writing and research through data analysis and visualization.”


 
   Christy 

Christy Sunquist

Sales Operations Intern

We would also like to welcome Christy, who is interning with our Sales team. Christy has years of operations experience with Charity:Water, helping develop relationships to get clean, drinkable water in the hands of as many people as possible.

“I love how CARTO is making location intelligence accessible to the masses and I’m excited about the potential the product has to empower small businesses and governments around the globe.”

Welcome Mehak, Michelle, Peter, and Christy! We’re excited to have all of them in our Brooklyn office! VAMOS!

Welcome to the CARTO team!

BTW, we’re hiring! Find all our open job positions at carto.com/jobs.

Reimagining Political Campaigns with our Election Mapping Webinar

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How can media outlets provide viewers and subscribers with more context on the 2016 U.S. Presidential election? CARTO knows the value of context, and you will too after watching our Election Mapping Webinar.

Context comes in many forms, however, and with our Election Mapping Webinar you will learn how CARTO Builder adds value to content with geographical context. Interactive data visualizations, such as the Google Trends visualization representing Google searches of each candidate over an eleven week period, allow users to locate nationally each candidate’s impact. During our webinar we will introduce you to CARTO features that allow you to create your own election maps.

Providing an Overview

Visualizations, such as the Daily Mail’s map of top searched political party leaders during the 2015 UK election season, convey a visual overview of a dataset’s raw material. Instead of tables and charts full of numerical figures and statistics, the Daily Mail’s data visualization employs a category map depicting the most searched for politician in each city and town throughout the UK.

Users interested in mapping rates, percentages, and proportions from normalized data would want to employ a choropleth map. Choropleth maps often use a color palette, with lighter and darker hues, to signal differences.

Zoom and Filter

Choropleth maps are popular for an overview, but because they do not account for the characteristics of an aerial surface (bodies of water, mountain ranges, etc.) users are often left with a false sense of aerial distribution. To ensure a more accurate representation of your data accounting for geographical specificities users can begin to “zoom and filter” with a dasymetric map.

VillaWeb, a newspaper in Barcelona, used a dasymetric map to visualize municipal elections results in 2015. Like a choropleth map, VillaWeb’s interactive map represents percentage rates for each party throughout the city with a color palette. Unlike a choropleth map, this dasymetric map acknowledges Barcelona’s non-residential areas (parks, bodies of water, etc.).

We know determining when to use a choropleth map versus a dasymetric map is tricky so we are sharing our recent Election Mapping Webinar with you today!

Details on Demand

Well-seasoned geospatial explorers examining both percentage rates and raw data will want to use a dot density map. The Chicago Sun Times visualized the 2015 mayoral runoff election results with a dot density map. Each dot, is a proportional symbol that attaches data to a specific geographical location, shows individual voters as well as the volume of voters of each candidate precinct by precinct. Users demanding even more details can click on any given dot to discover demographic information for each voter provided by the Chicago Election Board.

Our Election Mapping Webinar teaches users of any level new ways to engage in elections, which may help provide context to the 2016 US Presidential election by shifting away from journalist-centered news to data journalism.

Happy Election Mapping!

Charting New Terrain in eCommerce with Pitney Bowes

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CARTO is excited to announce a new partnership with Pitney Bowes, a global technology company powering billions of transactions – both physical and digital – across the connected and borderlessworld of commerce.

Pitney Bowes (PBI), like CARTO, understands that location intelligence is a crucial component of commerce within a globalized economy. In their 2016 Global Online Shopping Study, for instance, PB found that 66% of online shoppers crossed international borders while completing their retail transaction. “The world is shopping—everywhere—as new consumer behaviors and trends have emerged,” Lila Snyder, PB’s Global eCommerce President, stated in regards to the 2016 survey results.

CARTO’s self-service design enables our partners, like Pitney Bowes, to integrate data visualization features within their internal systems. Currently, we have begun providing internal teams with basemap templates, specifically raster and vector maps , in an effort to add location value to their data.

Whereas a raster map provides a snapshot of a designated geographical location, a vector map allows partners to link their own data alongside zoomable attributes (points, lines, polygons, and texts) providing a more informed assessment of a given location. The map included here, for instance, is from PB’s Street map, a vector map with zooming capabilities capable providing both a side-by-side glimpse of a regional overview and a street-by-street view of lower Manhattan.

This type of data visualization allows Pitney Bowes to start charting trends in different dimensions while also extending reach to other commerce solutions providers and developer-customers.

Pitney Bowes will demonstrate how to easily integrate Location Intelligence in applications, from mobile to IoT, during their ‘Learn to GeoEnrich apps, processes, and workflows’ webinar, Tuesday, October 18, 2016 at 2PM EST. Please register here.

We are thrilled to be assisting PB in these early endeavors, and look forward to future collaborations that will combine our forces to add data layers to PB’s current basemaps and more.

Watch this space for more CARTO and Pitney Bowes joint ventures!

Adding Version Control to your CARTO Builder Maps

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The version control feature was integrated into the Share and Publish functions in CARTO Builder. Previously, when sharing or publishing a map, the published map automatically reflected the changes and edits as they were being made, and many users liked the ease at which their maps could be updated and viewed publicly without having to do anything extra. However, for maps that are constantly evolving, this created some issues for user’s workflow.

For those unavoidable times when you start experimenting with different colors and elements, we added one step to the publishing process that will allow you to experiment with your visualization without interrupting the public-facing version of the map.

Now CARTO Builder maintains two versions of every map. One version we can call the “development” version, which –as in the Editor– is being autosaved, and is only accessible by the owner of the map. The second is the public version. This is the version the public will see via the link to the map or the application and/or website where the map is published. You decide when your latest edits are ready to be seen by the public.

After making your edits and the time comes to UPDATE the public version of your maps, you will just need to click on the SHARE button, and then the UPDATE button in the new window, just below the name of the map. From this moment on the changes you made will be visible to public viewers!

Don’t worry though, the data will be refreshed automatically, so creating real-time maps is still completely possible.

We’re still gauging interest among the CARTO community about having full version control of your maps. So every version you work on can be saved independently (and then restored). How does that sound?

Let us know what you think! For any Builder related questions please reach out to builder-support@carto.com.

Happy data mapping!


Mapping the historical biodiversity of the Solomon Islands with the American Museum of Natural History

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At CARTO we take pride in empowering the next generation of researchers and data-lovers to create projects that push the boundaries of how we understand our world. Recently, we shared our technology with Hannan Abid and Julian Moulton, two students transcribing, cleaning, and digitizing data at the American Museum of Natural History related to the historic species collection expeditions conducted in the Solomon Islands. Check out how Hannan and Julian used CARTO in their project!


Historical Biodiversity of the Solomon Islands

Hannan Abid & Julian Moulton

Introduction

The Pacific Ocean covers over 30% of the Earth’s surface, which is more than all the landmasses combined. Scattered in this vast region are thousands of islands and archipelagos that at the beginning of the 20th century were virtually unknown to scientists. In order to document the biodiversity of this area, and particularly of the region’s bird life, the American Museum of Natural History (AMNH) launched the Whitney South Sea Expedition (WSSE). During the expedition, which lasted from 1920 to 1935, some 40,000 bird specimens were collected from over 600 islands, and dozens of new species and subspecies were discovered and described (Figure 1). The majority of these specimens are housed today in the Department of Ornithology at the AMNH. These specimens are critical to our understanding of the region’s biodiversity, but few of them were cataloged with an accurate georeference as most specimen records included only a general locality such as the island name. This missing information hampers the use of these specimens for modern scientific research.

Fortunately the participants in the WSSE maintained detailed field journals, which are deposited in the AMNH archives. Using these unpublished journals, the logbook from The France (named after the expedition’s ship), specimen labels, and handwritten catalogs we matched individual specimens to precise geographic locations along the expedition’s route while referencing maps, gazetteers, and online sources. By discovering the collecting locality for each specimen, we hoped to depict visually early 20th century avian diversity.

CARTO
Figure 1. Lorikeet study skins from the Solomon Islands.

The Solomon Islands

Because of time limitations, we focused our study on specimens collected within the Solomon Islands. The Solomon Islands consist of six major islands and over 900 smaller islands that lie to the east of New Guinea in the region known as Melanesia (Fig. 1). Although the island of Bougainville is geographically part of the Solomon Islands, politically it is part of Papua New Guinea, and thus excluded from this study. The Solomon archipelago has played a vital role in studies in evolutionary biology, notably Ernst Mayr and Jared Diamond’s The Birds of Northern Melanesia. In recent years, the AMNH has renewed interest in the Melanesian islands and several AMNH expeditions have resampled the islands.

CARTO
Figure 2. Map showing position of Solomon Islands in Southwest Pacific Ocean.

Methods

Our objectives were to update specimen collecting information in the AMNH database, and to create a map that visualized the route of the Whitney South Sea Expedition through the Solomon Islands. The AMNH database was generated by transcribing specimen data from handwritten ledgers. These ledgers were based on data transcribed from the original specimen labels, which were written by the collectors in the field. Because this data was transcribed several times, from handwritten documents, errors were sometimes introduced into our sample. Additionally, the lack of standardized geographic names (alternate spellings, abbreviated references, etc.) meant that a given locality could be accounted for several different ways. Similarly, taxonomic names also were not standardized, and sometimes were completely missing. Figure 3 below describes the steps that were taken to generate the current database for specimens collected on the WSSE.

CARTO
Figure 3. Flow diagram for specimen data.

The first step in our data clean up was standardizing the legacy geographic data. We extracted around 8,000 locality records from the AMNH database. This data contained 809 unique values, but many proved redundant as a result of the previously mentioned lack of standardization. The AMNH database contains multiple hierarchical locality fields, such as country, island, political subdivision, and precise locality, and during data entry it was not always obvious in which field a particular value should be entered, and consequently many were misassigned. We cleaned, standardized, and parsed this data down to 154 unique locality records.

These new records gave us general information about the locations visited by the WSSE. Although this information was a useful start, our project required specific locality records that could be georeferenced. A database containing such data did not exist at the time so we decided to create one. We read through the unpublished field journals of the crewmembers of the WSSE and the logbook of The France. From these sources we were able to extract specific geographic and temporal data (Fig. 2), which we compiled in a spreadsheet with rows for date, and columns for the various crewmembers notes on geography. This enabled us to associate dates with specific localities that were visited by the WSSE.

CARTO
Figure 4. Example of detailed geographic information in WSSE journals.

Using the updated locality records and the temporal and spatial information extracted from the archival materials we assigned latitudinal and longitudinal coordinates to each specimen. These updates not only improved our understanding of certain specimen’s locality, but also provided detailed information related to the WSSE’s route. After fixing some outdated taxonomic information, our dataset was complete and ready to be visualized.

Results

The purpose of our study was to render previously unusable data from a biologically significant area available for scientific research. We parsed and standardized 809 redundant locality records into 154; we extracted an additional 114 precise localities from the WSSE field journals, and we cleaned and georeferenced 8,172 records of avian specimens. With the help of colleagues from CARTO, we generated two maps visualizing these results. The first map, for instance, illustrates the specific localities at which 8,172 specimens from the WSSE were collected (Fig. 5). CARTO also allowed us to visualize the complete itinerary of the Whitney South Sea Expedition through the Solomon Islands.

CARTO
Figure 5. Map of Solomon Islands collecting localities from WSSE.

Conclusion

Our research in the WSSE archives allowed us to assign georeferences to over 8,000 specimens, and with this data create digital maps illustrating the avian diversity of the Solomon Islands during 1927 to 1930. This data will be uploaded to the AMNH database and made available via online sources such as VertNet as well. Our work can be used for future studies including species distribution modeling, environmental impact, and climate change. Although a large number of WSSE specimens were georeferenced in our study, there exist many more in need of similar work throughout the South Pacific.

Acknowledgements

We thank Javier de la Torre and Santiago Giraldo at CARTO for their help with mapping, and Tom Trombone for providing raw data. We extend our thanks to Mark Weckel, Nuala Caomhanach and the rest of the SRMP team. Paul Sweet has also been an amazing mentor and guide throughout this project. Finally, we dedicate our work to the crew of the WSSE, especially Rollo Beck (Fig. 4), for providing us with the rich details of their travels.

CARTO
Figure 6. Rollo H. Beck skinning a Tropicbird aboard The France.

The outcome of the work is quite beautiful and revelatory. At CARTO, we helped them create an explorable version of the species collected using the CARTO Builder.

Happy Data Mapping!

Fon uses CARTO to scale millions of data points for better network service

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Location intelligence is a compelling method to measure technology usage in major metropolitan cities. Fon Wireless Ltd. (Fon), a leading worldwide WiFi provider that operates a system of dual access wireless networks and more than 19 million crowdsourced hotspots, fused geographic analysis and multiple data sources to discover where access points are placed and network density.

Using CARTO’s location and data analysis platform, Fon created a portal that spatially represents millions of stakeholders and their interests to network connectivity.

Fon was able to focus on the creation of customizable data-driven visualizations that update data and maps in real-time. Now Fon, as well as its clients and partners, can see WiFi service offerings and compare what works and doesn’t for better, faster decisions.

Discover how Fon used CARTO to visualize millions of data points and add transparency to their network offerings.

Download

CARTO’s location intelligence enriches cities, telcos, and service providers with deep insights from geographical and customer data. To learn more about how CARTO helped Fon visualize and analyze millions of data points for better customer services through the power of location intelligence and data analysis, read our case study today.

We really hope to continue to see more successful user experiences in this and other industries!

CARTO Expands Operations to Washington, D.C.

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CARTO began in Madrid, Spain in 2012, and has since expanded internationally with offices currently operating in Brooklyn, New York, Tartu, Estonia, and London, UK. We can now add Washington, D.C. to our ever-expanding list as CARTO goes to Washington.

Ben Mathew, our Senior Vice President of North American Sales, has found our D.C. initiative a home within Refraction, a curated office community providing rental space to startup companies, and especially tech startups companies. CARTO team members working from our D.C. office will benefit from Refraction’s many amenities, which include complimentary health-conscious meals as well as access to the on-site fitness center.

Refraction is located in Reston Town Center, a trendy area in Northern Virginia (NoVA), and is surrounded by great restaurants and entertainment venues.

Expanding operations to Washington, D.C. also means expanding our team! We are looking to grow this new branch and will be expanding hiring efforts for our D.C. office.

See you in D.C.!

Widgets Make Numeric Data Manageable and Meaningful for Everyone

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Communicating numeric data as meaningful information to an audience without a background in data science can be difficult. But CARTO Builder’s Dashboard Widgets help make numeric data valuable for everyone.

When working with numeric data, a data type comprised of columns and rows of numbers representing measurable values and/or observations, Dashboard Widgets help non-specialists visually navigate a dataset within a geographically specific context. CARTO Builder’s User Interface includes Dashboard Widgets, an application of interactive visual filters allowing map viewers to target select subsets of data for further exploration. Available widgets in dashboard include category, histogram, formula, and time-series, and as each widget interacts with a numeric dataset the map visualization responds. These responses exemplify Dashboard Widget’s dynamic behavior, which is what facilitates a map viewer’s deeper engagement with numeric data, but without making any modifications to the original dataset.

In terms of numeric data, viewers will find category and formula widgets helpful. Category widgets visually filter aggregated data columns defined within a numeric dataset. This widget has two behaviors that help viewers navigate more easily charts of numeric data: first, the unlock/lock behavior highlights a single category of the dataset for a more narrow examination; second, the search categories behavior allows viewers to search for patterns across multiple categories within the dataset.

Whereas category widgets work with numeric data columns, formula widgets filter data based upon defined elements within each row. Formula widgets are particularly helpful with analyses, too, as only formula widgets can define interactions between widgets and the original data. Additionally, viewers have the option of including supplemental text that appears underneath the formula widgets as well.

There’s plenty more to say about Builder’s Dashboard Widgets, but we would rather hear from you! How have widgets helped you manage numeric datasets?

Happy Filtering!

Locating CARTO Events for November 2016

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The upcoming month presents an opportunity for reflection and giving thanks. Our November conferences, likewise, will reflect improvements made to CARTO’s Location Intelligence platform, and you’ll be thankful not to have missed these informative sessions.

Wherecamp Berlin

November 4th-5th

Jaak Laineste, Head of CARTO’s Mobile team, will be present at WhereCamp GeoIT Navigation Conference in Berlin, Germany. Laineste’s talk, titled “Creating Accessible Insight: Adventures in Open Source Location Technology with CartoDB,” is scheduled for Friday, November 4th starting at 10:20am.

Open Data Science Conference

November 4th-6th

This year’s Open Data Science Conference West will run six concurrent conferences over three days in Santa Clara, California. Tyler Bird, our Community Development Strategist, is scheduled to participate within the Open Visualization Conference on Saturday, November 5th. Tyler’s presentation, titled “Multi-Dimensional Mapping,” starts at 3:45pm, and will explore data analysis and design in web mapping applications.

SenchaCon 2016

November 7th-9th

CARTO is excited to announce Michael Giddens, a CARTO partner, will be speaking at SenchaCon 2016. Michael holds 17 years of experience as a solutions architect and long-term veteran of Ext JS. He has developed and worked with numerous companies creating unique applications, which have impacted industry and the scientific communities alike. Michael is currently director of Crestone Digital, LLC, which specializes in geospatial web applications and big data projects.

Michael will discuss how to integrate geospatial maps and big data using CARTO-Ext JS components. These new components allow developers to visualize, filter dynamically, create time-lapse animations, and explore large location datasets at unprecedented scales. This presentation is scheduled for Wednesday, November 9th starting at 11:10AM at the Aria Resort & Casino in Las Vegas, Nevada, an apt location given this year’s theme, “Winning the Modern Web.”

Smart Cities Expo World Congress 2016

November 15-17th

Andres Gallardo Albajar, from Mobi Lab, will be demonstrating how CARTO’s Location Intelligence platform aids in resiliency planning and smart city initiatives at this year’s Smart Cities Expo World Congress (SCEWC) in Barcelona, Spain. Be sure to stop by Mobi Lab’s booth to meet Andres, learn about CARTO Builder, and share tips and insights related to smart city programs.

We’ll remind you about these events (and more!) throughout the month, but we wanted you to start marking your calendar today!

LUCA and CARTO to work together bringing location to the next frontier of big data

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The ability to derive actionable insights from the analysis of big data is a huge component to success for any telecommunications company. Big data is typically defined as having an inordinate amount of velocity, volume, and variety of data, which more often than not contains a location element. Therefore, to perform a holistic analysis of Big Data requires location contextualization. Telefónica, a multinational telecommunications service provider, is now working with CARTO to do just that.

Telefónica is collaborating with CARTO to add location intelligence to the wealth of data that Telefónica has access to. CARTO will work with Telefónica to develop new and integrated products within their newly announced Big Data business, LUCA. LUCA will enable Telefónica’s corporate clients to understand and derive value from their data, encouraging its transparent and responsible use.

One of the first examples of the partnership is this dashboard showing international and national tourists attraction to Spain, which highlights tourism influx through visual-spatial representation (the more pronounced the point and line, the more tourists). The dashboard enables toggling between countries and temporal settings, which facilitates the descriptive analysis of nearly 90,000 records. Ultimately this data-driven analysis can lead to the simple prediction of when and where tourists are likely to come from in the future, providing valuable insights for businesses and public organizations.

CARTO and Telefónica have a rich history of working with Telefónica on other data-driven projects. For example, CARTO is used as an integrated intelligence layer to illuminate insights from Smart Steps’ aggregated behavioural data collected from anonymized mobile devices. The observation of behaviour based on billions of mobile interactions that occur daily enables analysis to be performed by transport operators, city planners, retailers, banking institutions, and marketers.

Telefónica’s development of the FIWARE connector for CARTO, has enabled many European Union cities to access CARTO’s visualization and analysis tools for sensor data, to promote the development of Smart Cities applications based on open standards and open source code.

In addition to this partnership and collaboration, CARTO is part of Open Future, which manages the portfolio of investments made by Telefónica.

“We are delighted to be working with CARTO to develop new capabilities together to offer to our customers that will enable them to become data-driven companies” said Philip Douty, LUCA Director of Alliances and Strategic Partnerships, “we strongly believe that through working with Alliance Partners such as CARTO we will enrich and broaden the LUCA portfolio and increase its appeal to our clients.”

“It is wonderful to have Telefónica as a loyal partner throughout the years,” says Miguel Arias, COO of CARTO. “From the very beginning, Telefónica has believed in our team and product with their initial investment through Kibo Ventures, an Amerigo ventures fund. In addition to having the continuous support and guidance of their corporate development team in finding new business opportunities within such a huge organization.”

Through this partnership and collaboration, even more new products will be developed and mutually commercialized. This is a great opportunity to expand the reach of CARTO’s technologies worldwide with incredible partners like Telefónica.

Happy big data mapping!

CARTO at UNICEF: Using Location Intelligence for better global health

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Last week CARTO had the honor of being invited by UNICEF’s Knowledge Management & Implementation Research Unit to discuss global health issues and showcase how CARTO’s technology can help improve vaccination rates for children across the world.

We were able to identify a geospatial challenge related to the use of data that Kenya, a country trying to improve vaccination coverage, currently faces: namely, how to leverage data while determining the best locations to open clinics capable of serving segments of the population. Typically, building and rebuilding weighted geospatial models entails burderns (temporal, finanical, and technical) that many organizations simply cannot afford. Yet, CARTO’s scalability and self-service design was the perfect fit to assist this timely project.

We wanted to quickly address these industry issues before demonstrating how CARTO Builder would meet and exceed these very challenges. Using 1-2 year old population data from Columbia University’s Earth Institute alongside data from the Kenya Open Data Initiative, which provided the location for each of the country’s current vaccination clinics, we built a predictive dashboard for modeling optimum vaccination clinic locations in Kenya live in less than 30 mintues. This dashboard not only ran comprehensive analysis (several times), but also recalculated clinic locations based on weighted population cluster density centroids. Take a look at the outcome:

CARTO prides itself on fostering ethical and responsible corporate cultures. Our roots in conservation science as well as our present and future resiliency initiatives, such as PREP, prepared us to meet and surpass the challenges presented by UNICEF. To learn more about CARTO Builder and how it can work for your organization or business, don’t hesitate to get in touch!

Happy Data Mapping!


Filter data by column value in CARTO Builder

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Working with data can sometimes be a daunting task. Luckily, CARTO Builder’s analysis interface makes it easier than ever to perform data transformation, such as filtering, like never before. Filtering a dataset by column value can be done in just a few simple steps directly from CARTO Builder’s layer list or by selecting “Analysis” from the layer view once a layer is selected.

In the “Add a new analysis” screen, you will notice a variety of methods for manipulating and analyzing data. By selecting “Transform” and then “Filter by column value,” we have added our first analysis node to the layer’s workflow. Filtering by column value works directly with the data to only render parameters specified by the user.

If you are working with numerical or date values, it is possible to select a range from the data and filter out the results within the range, or not, meeting the criteria in the query. For string data types, or columns containing letters, numbers, and/or symbols, the filter by column value analysis allows you to search isolate, and/or remove specific cell values.

To learn more about analysis in CARTO Builder, be sure to check out our Analyzing your data section of our documentation.

Happy Data Mapping!

Introduction to analysis nodes in CARTO Builder

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With the incredibly powerful analytical capabilities of CARTO Builder, managing analytical workflows has never been more important. This is why we’ve created fast, easy, and functional ways of creating and understanding analysis.

The layer list makes it easy to not only see the hierarchy of your layers, but also the workflows of analysis attached to each layer through analysis nodes located directly below each layer name. At any time, each of the analytical processes can be selected directly from the layer list and modified.

The “add new analysis” screen can be accessed in two ways. The first is by selecting the layer title and then selecting “analysis” from the layer view. This analysis panel allows you to add or modify any analysis while also providing a clear view of the analytical workflow through the analysis nodes at the top. The “add new analysis” screen can also be accessed directly from the layer list by selecting “add analysis.”

CARTO Builder makes it easy to build analysis on top of existing analysis and keep track of the changes. This allows for deep levels of drill-down exploration as users to create and clean data, transform it, then run more analysis on top of the results. The workflows can be easily seen through the sequential numerical labeling of each analysis node.

Managing these often complex analytical workflows has never been easier. To get started with analysis in CARTO Builder, be sure to check out our analyzing your data section of our documentation.

Happy Data Mapping!

Get the plan you need, for the uses you want

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CARTO values unique users and the distinct uses of our platform, Builder and Engine. As a whole, our product is comprised of Builder—a web interface to interact with data, perform analysis, create maps, and share them internally within organizations or the world—and CARTO Engine APIs, which provide the spatial infrastructure to power embeddable location applications. The special usage of Builder and Engine caught our attention. We noticed that our users were making use of the product, not so much as a complete package but, in a more interesting way.

Although some use cases involved the entire CARTO platform, more often than not, CARTO was being utilized either for Builder or Engine, respectively. Having a single pricing plan for both Builder and Engine simply seemed too narrow. We took a look at our pricing plans and came up with a solution that would provide the best fit and value for users. After examining how users make use of different aspects of the CARTO platform, we’ve determined that Builder, Engine, and Location Data Services quotas are three different products of CARTO.

CARTO Pricing

Builder plans

Users that want to use CARTO Builder for individual reasons can now subscribe to our Personal plan. The option to purchase Builder for collaborative use within an organization is still available with our Enterprise plans. However, subscribers can now determine how many users ( Builders ) within an organization need access to create maps and interact with data, as well as how many users ( Viewers ) can consume Builder location apps privately.

Engine plans

Our primary CARTO Engine users are developers that create custom applications for internal use. These developers interact with our APIs and use Builder, occasionally, to prototype maps. We augmented our price for Engine based on the number of developers that will program on Engine or the number of API Keys needed. We also know that resources are important, like the amount of cache data, CPU availability, or requests per second. We expect to speak with customers, case-by-case, related to resources, especially if a project is focused on commercialization.

Location Data Services quotas

A common need of both Builder and Engine are Location Data Services. LDS includes: geocoding, routing, isolines, data augmentation, and other services used when analyzing or building applications. CARTO is adding more definition to our LDS terms by providing specific quotas for each service. With each plan a certain amount of each of these services can be consumed while using CARTO. For a larger quota, we are always available to provide more upon request.

What does all this mean for my current subscription?

CARTO has put in a lot of work to ensure that current customers retain the same service as before. Additionally, users will get a rise in quotas and capacities, while functionalities only increase. We are that cool.

CARTO has a great community of non-profits, scientists, Ambassadors, students, journalists, and many non-traditional “Enterprise” users on our platform. We’ve set up a custom plan to ensure affordable access to our products. We are always happy to support and engage this special CARTO community.

Contact us with your questions!

Our new plans are a step forward in the way we describe our product and how we charge for its value. With these changes we hope to amplify the specificity of user needs and the individuality of our product. If you have any concerns or issues we’d love to hear from you to help with a solution.

Mastering layers in CARTO Builder

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When working with maps and analysis, it’s essential to have effective control over the data layer hierarchy and the analysis attached. In CARTO Builder, managing your layers and analytical workflows has never been easier thanks to our intuitive layer list and analysis nodes. When working with more than one dataset, the Builder’s layer list allows for complete control over the hierarchy of your visualization.

Right away you will notice that the data on the map is rendered in the same order as the layers in your list. Each dataset brought in is assigned a letter, beginning with “A,” in the order they were brought in.

When a layer is moved higher up, the visualization will dynamically adjust to represent the changes. Also in the layer list you will find the basemaps layer. While this layer can not be moved, selecting the basemaps layer allows you to select basemaps from a wide range of providers, or upload your own.

You will notice that some basemap layers place labels on top of your data. These basemaps allow you to sandwich your data between the basemap itself and the basemap labels element. This is also represented in CARTO Builder’s layer list, which gives complete visibility to all aspects of your visualization hierarchy.

Looking to learn more? Be sure to check out CARTO Learn for the latest and greatest on mastering CARTO Builder.

Happy Mapping!

Enhance your business intelligence with a Qlik

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Eighty percent of a business’s data contains a location component that is often overlooked. However, this trend is starting to change thanks to professionals using Qlik Sense to reimagine methods of data analysis with location intelligence.

Instead of understanding business intelligence tools as beefed up spreadsheets, companies like Qlik have excelled at raising the bar on data filtering and analysis. Qlik users can create widget dashboards that filter and automatically update datasets in response to new analyses. Qlik, like CARTO, encourages posing location-specific questions to existing data to pinpoint holistic answers that can be put into action immediately.

Given our shared interests, CARTO and Qlik have made it easier to reap the benefits from our platforms with a new extension. For Qlik users, the extension creates an “Open in CARTO” button in your Qlik workflow or branch that can be used to send contents of your hypercube to CARTO. Open datasets in Qlik Sense and visualize location apps with our new Builder. For CARTO users, the extension allows existing visualizations to be embedded in Qlik Sense whether or not the map’s dataset were imported from Qlik.

To install our new “Open in CARTO” extension follow these simple steps.

As a business user or analyst determining where to put a new store location or operations, you can do a lot of that analysis directly in Qlik. With the “Open in CARTO” extension, you can send that data to CARTO and continue to build your analysis. And for more cool Qlik connections check out our Qlik connector to enhance your business intelligence with time-series analysis.

Happy location data analysis!

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