Se ha denunciado esta presentación.
Utilizamos tu perfil de LinkedIn y tus datos de actividad para personalizar los anuncios y mostrarte publicidad más relevante. Puedes cambiar tus preferencias de publicidad en cualquier momento.

BIME Analytics Maps: Efficiently visualize data on beautiful maps

668 visualizaciones

Publicado el

BIME Analytics Maps: Efficiently visualize data on beautiful maps

We believe the new improved BIME Map visualization is both the easiest and most beautiful way to do spatial analysis available today. The cloud makes it easy. Here is why…

Ease and speed of geocode data coming
from very different data sources

An important part of spatial analysis is extracting the location from text value. Most of the geographic information is not available in perfect longitude and latitude form but in text columns in databases, online services or Excel files.

BIME will take care of converting text value to longitude and latitude and if the data point is something BIME has already seen it will return the position at an incredible speed.

Light maps:
High contrast with default colors. Contains minimal informations in terms of streets, road names. This tile really leaves room for your data to shine.

Street maps
Beautiful colors. Street and city names detailed.

Dark maps:
A black theme of the light version. If your dashboard leans toward the dark side.

Pencil maps
A very beautiful theme that retains high contrast with data points. It works extremely well when you zoom in on an area with a high density of population.

Satellite maps:
Very precise topographic and road information.

Clustering

A lot of data maps out there suffer from occlusion of points. With the new BIME, map points that are too close are automatically merged. Have a look below by sliding the separation between the old way and new way.

This approach offers a lot of advantages
VISUALIZATION
Much nicer and cleaner picture of data with fewer data points.

PERFORMANCE
Better performance as the rendering doesn't have to draw thousands of points on the map.

LEVEL OF DETAILS
Details on demand.
Zooming is very easy by clicking on zones of interest.

Multivariate spatial analysis
You can encode several numeric values through text, color and size encoding. The new BIME map also gives you the ability to analyze several categories at once via pie chart representation.

Heatmap
A heatmap is a visualization used to depict the intensity of data at geographical points. When the Heatmap Layer is enabled, a colored overlay will appear on top of the map. By default, areas of higher intensity will be colored yellow, and areas of lower intensity will appear purple.

Maps are another fundamental visualization as they maximise the cognitive ability of the analyst to understand data through space. They are both very easy to use as thanks to default settings such as clustering, and a wealth of customization options allow you to create beautiful custom maps.

About BIME: BIME delivers a simple-to-use yet powerful data analysis and dashboarding cloud platform accessible everywhere that enables modern organizations to explore, understand and communicate data with style. Its UI combines the visual simplicity and elegance of the best consumer apps with powerful features

Publicado en: Empresariales
  • Sé el primero en comentar

BIME Analytics Maps: Efficiently visualize data on beautiful maps

  1. 1. Efficíently vísualize data on beautiful maps
  2. 2. We believe the new improved BIME Map visualizatíon is both the easiest and most beautiful way to do spatial analysis available today. The cloud makes it easy. Here is why. .. bime III
  3. 3. Ease and speed of geocode data coming from very different data sources 'Half : at on fiom ien vaiue lost of I ongimcíé and amucé- fow? Du( n on Ene (les An "HIZDHSHI ; part of s me eograo tex: ccriumns n : i Hi "E S . rama to mg 140e {md Iaitutle if'. een : ewn me DOSVLCW al sv" BIME w take : are of coiweruzwg : m s vwntr “g BIME has a: speed bime III
  4. 4. Choose the right map background Rendering mode Circles Base Iayer Dark L' ht Radius 'g Dark Merge overlapplng points Pencu opacüy Streets Terrain Satellite bime
  5. 5. High contrast with default colors. Contains minimal informations in terms of streets. road names. This tile really leaves room for your data to shine. i i i bime all
  6. 6. I l9lOl9 ? UNS/ W Il 393039 3ON3AV I 39H03D ! FINE/ W w t: goes” s w* g , ~ i «ü . é g c e5 e 9g 90 90 t} e é* Q. y. u» Q * v. ;- , a W 7 j à 5 'v, $3 w Püga 42- 50 e” 40,715” $9 a ~ va a s 4 4 I. uhm Qo 9-: sp, ~s z 4 < Z ':7 55 2 i 2 < ã a «z 2 it ' , . . s ` ”` 4 Q Champs-Elysees - Clemençeau . .arw/ ER à v , imax bime
  7. 7. ' f, .:. li críií-lilgíeíiií bime
  8. 8. a A very beautiful theme that retains high contrast with data points. lt works extremely well when you zoom in "~ on an area with a high density of population. _ " . ` 7 * o . _` o 4k l ~ x
  9. 9. 5.353,. , Danmark Lietuva -Gdansk Republic . Manthesrer - Hamburg of Ireland Unned . -Berlin Kingdom Nederland Polska rwarszawa -London Belgique - Deutschland Be| giê~ Belgien -Frankfurlam Main 9'? ” Luxembourg (ako 'flew! ' 73'” Slovensko Wien- France ósterreich Emmy*** llechlenxteín_ _ . _ ' swizsariana» ' ' Magyammag Genéve' ` " 3- 'sioveniia . '_ Hrvatska Rama" EeorpaA aosna . Bucure$li . Monaco san Mmm i Herzegovina cpsnla Satellite Bilbao- V Andorra Italia “m” igo- , -. - ' 5"" Penyãnwu o* ` - Barcelona Roma Gora Maxeuonma _l N i' Sh i eria' Espana 'W' q p , ?ortugal (
  10. 10. Clustering -: di. @o O ; *'~'l'l: : l: .«. "`. r s : u: "lj, ll _« , %,. .,. Slidlngi'>: :¢jL: i', ,: '. '
  11. 11. This approach offers a lot of advantages VISUALIZATION PERFORMANCE LEVEL OF DETAILS Much nicer and cleaner p cture of : lata Better perfollhance as the rehcleung Deta s on demand Zooming ls very easy wvth fewer : lata COlfiiS doesnt *lave to (ilaw thousands of po nts by cllck 'lg oll zones oi llitelest on the nla: ) bime: l:
  12. 12. Multivariate spatial analysis You : an elcocle 'evelel l`Lll7`ê'lC val-ties "7l`GLlgi1Z"<I` color and *c eltcocllng *he wew BlME l`l`: `:D alss give; you . ne lty to analyze 3': eral catego' es at olue u' a ole mart leolesentat on Dirlci 'll ! lv zhg"
  13. 13. Heatmap bime. .I
  14. 14. Maps are another fundamental visualizatíon as they maximise the cognitive ability of the analyst to understand data through space. They are both very easy to use as thanks to default settings such as clustering, and a wealth of customization options allow you to create beautiful custom maps. bime III
  15. 15. ~ it 7;1`: 'l x 'i y. 'd ~~~, .,-, -,~ . «- a. . ilw3i~4~ 'i' 7 r ~'*`x v' . lm: @tinura-EFIêlnilãiííãíêlteãlêini 'gvr i. , a _| _ir_l iiüíiííílà--l ll

×