InfoQ HomepageData Analytics Content on InfoQ
- Posted by Neha Pawar on Aug 16, 2023
Speed of Apache Pinot at the Cost of Cloud Object Storage with Tiered Storage
Neha Pawar discusses how to query data on the cloud directly with sub-seconds latencies, diving into data fetch and optimization strategies, challenges faced and learnings.
on Aug 16, 2023%2fpresentations%2fapache-pinot-cloud%2fen%2fmediumimage%2fneha-pawar-medium-1691576131033.jpg&f=jpg&w=240)
Icon43:39 - Posted by Blanca Garcia-Gil on Jun 21, 2021
Evolving Analytics in the Data Platform
Blanca Garcia-Gil discusses the BBC’s analytics platform architecture, the failure modes they designed for, and the investigation of the new unknowns and how they automated them away.
on Jun 21, 2021%2fpresentations%2fbbc-analytics-platform%2fen%2fmediumimage%2fblanca_garcia_gil-m-1623962460893.jpg&f=jpg&w=240)
Icon38:12 - Posted by Gareth Rogers on Jul 30, 2019
Putting the Spark in Functional Fashion Tech Analytics
Gareth Rogers shows how his team used Clojure to provide a solid platform to connect and manage an AWS hosted analytics pipeline and the pitfalls they encountered on the way.
on Jul 30, 2019%2fpresentations%2fmetail-aws-pipeline%2fen%2fmediumimage%2fgareth_rogers_big_data_m-1564649609944.jpeg&f=jpg&w=240)
Icon35:50 - Posted by Deepak Chandramouli on Jun 13, 2018
Gimel: PayPal’s Analytics Data Platform
Deepak Chandramouli introduces and demos Gimel, a unified analytics data platform which provides access to any storage through a single unified data API and SQL.
on Jun 13, 2018%2fpresentations%2fgimel-paypal%2fen%2fmediumimage%2fDeebig-1528941201064.JPG&f=jpg&w=240)
Icon49:00 - Posted by Yujing Wu on Nov 18, 2017
A Cloud-centric Ecosystem Approach to Ease IoT Development
Yujing Wu discusses two use cases of a cloud-based IoT ecosystem that enables IoT device communication across silos and interoperability across different vendors.
on Nov 18, 2017%2fpresentations%2fiot-cloud-ecosystem%2fen%2fmediumimage%2fYubig-1511138614300.JPG&f=jpg&w=240)
Icon35:26 - Posted by Mahish Singh on Sep 08, 2017
Enabling High Performance Real-time Analytics for IoT Environments
Mahish Singh discusses how to use methodologies during design, development, deployment and operation for delivery of analytics platforms which offer real-time SLAs.
on Sep 08, 2017%2fpresentations%2freal-time-analytics-iot%2fen%2fmediumimage%2fManbig.JPG&f=jpg&w=240)
Icon38:11 - Posted by Yi Pan on Mar 30, 2017
Scaling up Near Real-Time Analytics @Uber &LinkedIn
Chinmay Soman and Yi Pan discuss how Uber and LinkedIn use Apache Samza, Calcite and Pinot along with the analytics platform AthenaX to transform data to make it available for querying in minutes.
on Mar 30, 2017%2fpresentations%2fuber-linkedin-analytics%2fen%2fmediumimage%2fChibig.JPG&f=jpg&w=240)
Icon46:03 - Posted by Danny Yuan on Mar 25, 2017
Stream Processing & Analytics with Flink @Uber
Danny Yuan discusses how Uber builds its next generation of stream processing system to support real-time analytics as well as complex event processing.
on Mar 25, 2017%2fpresentations%2fuber-flink-stream%2fen%2fmediumimage%2fDanbig.JPG&f=jpg&w=240)
Icon47:47 - Posted by Doug Daniels on Feb 17, 2017
Elastic Data Analytics Platform @Datadog
Doug Daniels discusses the cloud-based platform they have built at DataDog and how it differs from a traditional datacenter-based analytics stack, pros and cons and the tooling built.
on Feb 17, 2017%2fpresentations%2fdatadog-cloud%2fen%2fmediumimage%2fDobig.JPG&f=jpg&w=240)
Icon43:06 - Posted by Oleg Zhurakousky on Jan 29, 2017
Streaming Live Data and the Hadoop Ecosystem
Oleg Zhurakousky discusses the Hadoop ecosystem – Hadoop, HDFS, Yarn-, and how projects such as Hive, Atlas, NiFi interact and integrate to support the variety of data used for analytics.
on Jan 29, 2017%2fpresentations%2fstreaming-hadoop%2fen%2fmediumimage%2fOlebig.JPG&f=jpg&w=240)
Icon33:53 - Posted by Nikhil Garg on Jan 22, 2017
Scaling Counting Infrastructure @Quora
Chun-Ho Hung and Nikhil Garg discuss Quanta, Quora's counting system powering their high-volume near-real-time analytics, describing the architecture, design goals, constraints, and choices made.
on Jan 22, 2017%2fpresentations%2fquora-analytics%2fen%2fmediumimage%2fRobbig.JPG&f=jpg&w=240)
Icon50:21 - Posted by Ali Jalali on Oct 16, 2016
Developing a Machine Learning Based Predictive Analytics Engine for Big Data Analytics
Ali Jalali presents how to develop a machine learning predictive analytics engine for big data analytics.
on Oct 16, 2016%2fpresentations%2fml-predictive-analytics-engine%2fen%2fmediumimage%2fAlibig.JPG&f=jpg&w=240)
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