Integrate Slack with Amazon Kinesis
Use the Slack integration to get vital information about your organization, your team, and their habits or productivity.
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 Slack data to Amazon Redshift
Load your Slack data to Google BigQuery
ETL all your Slack data to Snowflake
Move your Slack 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
Integrate Slack With Amazon Kinesis Today
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Slack's End Points
Gather and set information on members of your Slack team: get a user’s identity, find a user with email addresses, set user profile pictures, and more.
Get info on your team's Slack channels, create or archive channels, invite users, set the topic and purpose, or mark a channel as read. Use this information to track and improve company communication.
Interface with all kinds of conversations, including public conversations, private channels, and direct messages.
Get info on files uploaded, upload new files, and control things like file sharing, filters, and file information.
Slack Group and User Group
Get info on your team's private channels, or groups, and on your team's user groups.
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.