I'm currently using the Bing Maps API to display a map of a city along with traffic data (such as incident report and traffic flow).
I need to be able to pass a complete list of street segments and intersections of a given area to an AI application to work with. However, all this data, along with the corresponding traffic data I need seems to be bound to the actual map of the API (ie. It can only be displayed and not worked with). Is there any way to extract this information and insert it into a custom made data structure? If not, is there some other map API that is capable of doing this? (although I would prefer work with Bing Maps if possible)
The traffic data can only be used within the Bing Maps controls. This data cannot be extracted from Bing Maps and stored elsewhere. Try taking a look at the HERE Traffic API's: https://developer.here.com/rest-apis/documentation/traffic
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Basically I've a use-case that I need to fetch multiple longitude and latitudes on multiple zip codes. So that I can avoid multiple requests to the Google servers and can reduce costs as well as make my code more efficient.
Request for single request look like below:
https://maps.googleapis.com/maps/api/geocode/json?address=10001&sensor=false&key=<some_key>
And this works fine for the single request. But I want to know if there is some method using which multiple geolocation data can be fetched?
I am validating the data from Eloqua insights with the data I pulled using Eloqua API. There are some differences in the metrics.So, are there any issues when pulling the data using API vs .csv file using Eloqua Insights?
Absolutely, besides undocumented data discrepancies that might exist, Insights can aggregate, calculate, and expose various hidden relations between data in Eloqua that is not accessible by an API export definition.
Think of the api as the raw data with the ability to pick and choose fields and apply a general filter on those, but Insights/OBIEE as a way to calculate that data, create those relationships across tables of raw data, and then present it in a consumable manner to the end user. A user has little use with a 1 gigabyte csv of individual unsubscribes for the past year, but present that in several graphs on a dashboard with running totals, averages, and timeseries, and it suddenly becomes actionable.
I need to get data from one query using 13 dimensions and 13 metrics. Because of the limitation, I can't do that. Q: is it possible to get raw data or how can you combine data from multiple queries with different dimensions?
If you are using Google Analytics Standard, then there is no way to fetch 13 dimensions in a single query. But if you have Google Analytics 360 aka Premium version then you can link your GA 360 account to BigQuery and then you can fetch such data using sql from BigQuery.
Having said that, there is a way for standard as well but its feasibility depends the kind of data you would want to fetch. You can use segment features if possible by creating a segment based on some of the dimensions and rest dimensions ( 5 maximum) can be put in custom report. For example if you want to fetch data such as sessions, transactions, bounce rate, time spent and other metrics on the basis of Gender type: Male, Device: desktop, Country: India, Age: 25-34, Browser: Chrome, and other dimensions are generic with no filters such as source, medium, event action, landing page and etc. Then, you can create a segment based on dimensions which sort of have filter criteria as per your requirement and use other dimensions which don't have filter criteria in custom report.But remember, the feasibility of this solution depends on your requirement.
I am in a bit of dilemma.. in the database if have lots of posts which all have a longitude and latitude attribute.
What I am currently doing is observing the whole post group, and then doing the validation on the device. Which will become very heavy if there are more than 1000 or more posts.
if (location (latitude + longitude)).distance(currentUser.location) < 5000
Is there a way to do the validation directly on the database? And keep in mind that the currentUser.location is relative to the device, so I always would need to construct the location from the post and compare it to the current location of the user.
Any help would be much appreciated.
It's possible if you would use something like geohashes. Then you could filter your locations based on their geohash indexes. Or you can also achieve that by creating your data structure based on geohashes. But there's no need for this since there are libraries which do that.
I've created a library for geo queries, check it out.
Or there's also a good library from firebase itself.
I am planning to build a location-aware app with the Ionic framework. It basically comes down to showing a Google map with the location of the user and markers in his neighbourhood. I will only show markers on the visible part of the map.
This excellent tutorial of Josh Morony uses a PHP script on the database. It limits the number of markers returned to the app based on a distance calculation between the user location and all markers stored in a mysql database.
However, I would like to use a Firebase database for my app. This question already points out that server-side calculations are not possible with Firebase.
Would it harm the performance of my app if I would return all markers stored in Firebase and calculate the distance on the client side? I would then limit the markers shown based on those calculations.
Or is it better to limit the number of markers returned after server-side calculations and then load the Google Map Markers?