Filter Swapping (part 1)
In this two-part blog I'm going to look at use cases involving a feature of PYLON called filter swapping which allows you to change the CSDL code of an interaction filter without stopping your recording.
If you're new to the PYLON platform take a look at our PYLON 101 and Get Started guides.
Use Case: Countries
Suppose you want to monitor a brand in your own country initially and then gradually expand your geographical coverage to include other countries....
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Planning Your Migration from API v1.2 to v1.3
Today we released version 1.7 of PYLON for Facebook Topic Data. This release introduces version 1.3 of the DataSift API. For PYLON customers this means significant improvement to features but also code changes to move to the new API. In this post we'll take a look at the changes and cover points you'll need to consider when making the move.
Note that version 1.2 of the API will be available for a while yet. Check out the API changelog for full details of planned API deprecations....
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Announcing PYLON 1.7 - Introducing Interaction Filter Swapping
Today we released version 1.7 of PYLON for Facebook Topic Data. This release includes some key features that will make it easier for you to build production solutions with PYLON.
Introducing interaction filter swapping
Until now recordings and indexes have been tied to the CSDL you defined for your filter. When you compiled your CSDL you received a hash, which in turn was used as the identifier for the index in which recorded data was stored. This meant that if you wanted to update the CSDL...
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Using Facebook Topic Data to Refine an Advertising Campaign
You might have seen our recent blog post where we discussed how an agency used Facebook topic data to carry out audience research and refine an upcoming ad campaign. In this post we'll take a look at how the research was carried using our platform.
Using Facebook topic data to understand an audience
It naturally follows that the better you can understand your audience, the better you can plan your ad campaign, and therefore the more impact your campaign will have.
In this instance...
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Nested Analysis Queries in PYLON
In this blog I'm going to introduce nested analysis queries in PYLON. These are queries that allow you to delve more than one level deep. The example I'll use will analyze authors by gender and then divide them further into age demographic ranges.
PYLON is DataSift's privacy first technology that allows you to look at Facebook data on an aggregate level without visibility of the details of individual people. Think of it like this: you can hear what a crowd is saying without zooming...
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