AppsFlyer provides users with centralized and accurate ROI tracking for each of their marketing campaigns and advertising sources. This includes both traditional advertising sources - like TV and social media - as well as harder-to-measure sources like in-app advertisements. It then sends all of this data to one consolidated dashboard to be viewed and analyzed.
About Amazon Kinesis
Amazon Kinesis is a powerful analytics solution that overcomes the batch-processing challenges of Hadoop — and similar solutions — which don't allow real-time precision in decision-making because they can't rapidly process high volumes of streaming data. With its ability to process hundreds of terabytes of streaming data per hour, Kinesis allows you to develop apps that rely on real-time data to fuel AI analytics, machine learning insights, and other applications. Kineses enables instant responses by eliminating the delay associated with batch processing.
Popular Use Cases
Bring all your AppsFlyer data to Amazon Redshift
Load your AppsFlyer data to Google BigQuery
ETL all your AppsFlyer data to Snowflake
Move your AppsFlyer data to MySQL
Bring all your Amazon Kinesis data to Amazon Redshift
Load your Amazon Kinesis data to Google BigQuery
ETL all your Amazon Kinesis data to Snowflake
Move your Amazon Kinesis data to MySQL
AppsFlyer's End Points
AppsFlyer Data Locker
Configure a large, daily export of raw data - including organic installs, impressions, uninstalls and in-app events - which is sent to a dedicated AWS bucket. Then, access that exported data whenever you need to and integrate it with other data sources for an even broader variety of insights and metrics.
AppsFlyer Reports and Exporting
Appsflyer reports fall into four categories: performance, re-targeting, fraud prevention, and raw data reports. You can export any of these reports to get an array of useful data, including the number of installations in a date range, the number of lost leads that were successfully retargeted, and the number of in-app events that occurred in a set period. This allows you to gauge your true ROI as accurately as possible.
Amazon Kinesis's End Points
Amazon Kinesis Video Streams
Amazon Kineses Video Streams allow you to safely ingest streaming video data from millions of linked devices into AWS for machine learning, analytical, and other processing purposes. The platform then encrypts, stores, and indexes the video data so you can access video with simple APIs, play live video streams, and offer on-demand playback. When incorporating this technology with Amazon Rekognition Video, TensorFlow, ApacheMxNet, and OpenCV, Amazon Kineses Video Streams makes it possible to build video analytics and computer vision processes into your applications.
Amazon Kinesis Data Streams
By capturing, processing, and storing data streams, Amazon Kinesis offers a real-time data streaming solution to ingest large amounts of information from hundreds of thousands — even millions — of sources at the gigabytes-per-second scale. The massive scalability of this solution lets you capture and produce immediate analytics on data pertaining to financial transactions, database event streams, location tracking data, clickstreams, social media activity, and more. Since the availability of streaming data happens in milliseconds, the platform enables real-time analytics of this information for instant detection of anomalies, dynamic price adjustments, precise dashboard metrics, and more.
Amazon Kinesis Data Firehose
Amazon Kinesis Data Firehose provides a simple and durable way to pull your streaming data into data warehouses, data lakes, and analytics solutions. Due to its compatibility with Splunk, Amazon Redshift, Amazon S3, and Amazon Elasticsearch Service, Kinesis Data Firehose empowers real-time data analytics for the dashboarding and BI tools you've come to trust. Fully managed and automatically scaling, you can use Firehose to encrypt, batch, transform, and compress your information before ingestion to boost security and save on disk space.
Amazon Kinesis Data Analytics
Amazon Kinesis Data Analytics helps users without programming knowledge to analyze data streams with SQL or Java. For team members who know SQL, an SQL editor and templates are available for creating streaming applications or querying streaming data. Meanwhile, those with Java knowledge can develop more nuanced streaming applications that perform real-time data transformations and analytical processes.