Lyft Engineering
JUNE 28, 2023
The Event Driven Decisions capability in particular turned out to be general enough as to be applicable to a wide range of use cases. At the time of writing, a Mapping team is working to utilize theEvent Driven Decisions product to rebuild Lyft’s Traffic infrastructure by aggregating data per geohash and applying a model.
LinkedIn Engineering
DECEMBER 19, 2023
Our RU framework ensures that our big data infrastructure, which consists of over 55,000 hosts and 20 clusters holding exabytes of data, is deployed and updated smoothly by minimizing downtime and avoiding performance degradation. This metadata includes the namespace, file permissions, and the mapping of data blocks to datanodes.
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ProjectPro
FEBRUARY 8, 2023
Application programming interfaces (APIs) are used to modify the retrieved data set for integration and to support users in keeping track of all the jobs. Users can schedule ETL jobs, and they can also choose the events that will trigger them. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog.
Cloudera
JUNE 29, 2023
Incorporate data from novel sources — social media feeds, alternative credit histories (utility and rental payments), geo-spatial systems, and IoT streams — into liquidity risk models. Apply predictive-analytic and ML techniques to this data to create more accurate profiles and proactively identify high-risk customers.
Lyft Engineering
SEPTEMBER 27, 2022
The very first version (see Figure 1) was designed to consume events, convert data to ML features, orchestrate model executions, and sync decision variables to their respective services. This pipeline ingests tens of millions of events per second and processes them into machine learning features.
Picnic Engineering
SEPTEMBER 8, 2022
Quick re-cap: the purpose of the internal pipeline is to deliver data from dozens of Picnic back-end services such as warehousing, machine learning models, customers and order status updates. The data is loaded into Snowflake, Picnic’s single source of truth Data Warehouse (DWH). Yet, some messages are destined for the DWH only.
Cloudera
NOVEMBER 13, 2020
The reality is that data warehousing contains a large variety of queries both small and large; there are many circumstances where Impala queries small amounts of data; when end users are iterating on a use case, filtering down to a specific time window, working with dimension tables, or pre-aggregated data.
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