Latest posts tagged with #RTASummit on Bluesky
On April 24-26, the real-time analytics community is gathering to discuss harnessing actionable insights from real-time data. Establish yourself as a leader in the space by sharing your real-time analytics journey at #RTASummit.
CFP closes Jan. 8th:
stree.ai/3Ze7d2u
Call for papers for #RTASummit 2023 is open! 📃
The real-time analytics category is defined by a community of people building things for diverse use cases using new technology. We would love for you to share your knowledge.
Submit your talk until Jan. 8:
stree.ai/3Y8HwzF
Almost 1700 registrations showed that interest in a real-time industry event like the #RTASummit exists - that's why we'll be back. On April 25-26, 2023, we'll be meeting in person in San Francisco to take things to the next level. CFP is now open:
stree.ai/3ErAhdb
It's a wrap 🎬 @tlberglund ended #RTASummit a few minutes ago and made sure to leave on a high note: The next Real-Time Analytics Summit will be held in person in San Francisco on April 25-26, 2023. You can already sign up to receive more information:
rtasummit.com
Our last talk of the day is coming from @redpandadata developer advocate @dunithd. He is talking about the challenges of building real-time user-facing dashboards with @ApachePinot
#RTASummit
Here is an excellent example of doing a migration from a legacy system of record to a real-time query path with @ApachePinot using the strangler pattern.
From Johan Adami at @stripe.
#RTASummit
"Your data now scales with the dimension cardinality. If you're one of the users that has an order of magnitude more data, that's okay."
Johan Adami on how @ApachePinot indexing scales real-time performance @Stripe.
#RTASummit
"We can consume many thousands of events per second but there is still a challenge. The challenge becomes the number of hops. @ApachePinot has a concept called 'exactly once ingestion' which is very important for our users."
Johan Adami on how @Stripe uses Pinot
#RTASummit
"Since we have a lot of internal users at @Uber coming up with new use cases, we need to be reliable so that we do not become the bottleneck for the business. We leverage @ApachePinot concepts like resource isolation to make this happen." @hungryankit
#RTASummit
"The freight team at @Uber came up with new use cases to educate carriers with on-the-job performance metrics. We helped them build a carrier scorecard app. @ApachePinot powers this at very low latency."
@UTulshigiri
#RTASummit
"Real-time customer feedback at @Uber lets you respond to the customers in real-time."
@UTulshigiri explains the power of real-time provided by @ApachePinot to maximize value.
#RTASummit
Reasons why StarTree Data Manager is the simplest way to use @ApachePinot:
The data modeling component is a game-changing feature which infers everything about your data and makes useful suggestions. @timsants @opanitch
#RTASummit
Currently, we have our very own @timsants and @opanitch talking about the StarTree Data Manager for getting your @ApachePinot data faster.
#RTASummit
"You should start to think about communication between your applications using streams. The standard microservice rules apply. Owners of a service (a stream) are the interface between other teams to consume." @esammer @Decodableco
#RTASummit
Here @esammer digs deep into how @Decodableco handles change data capture at scale.
"At @Decodableco we use the @debezium envelope format for change streams."
#RTASummit
"Real-time analytics is fundamentally about powering applications with the data behind the business." This is what @tlberglund leaves us with.
@karinwolok is now hosting the RTA Challenge. Come say hi:#ApachePinot #RTASummit
rtasummit2.com
"When you look around... When people say 'Modern Data Stack'... We see this. But the landscape is always changing. Change is not the problem. The problem is not seeing through it."
@tlberglund
#RTASummit
"When data suddenly got big, we needed a new data infrastructure to solve problems. Enter @hadoop. ETL became ELT (extract, load, and transform afterwards)"
@tlberglund
#RTASummit
What does the world look like for an organization after they've solved the data mesh problem? This diagram shows what the possibilities look like.
Excellent talk from @zhamakd and now on to @tlberglund and his keynote on the modern data stack.
#RTASummit
"These pipeline models are full of friction when going from data to value. The reality of existing data architectures is one of confused languages in an organization, slowing people down from delivering value." @zhamakd
#RTASummit
3 hours and 400+ live attendees later, #RTASummit is a wrap🎬
@tlberglund concluded the event and dropped some pretty big news along the way:
#RTASummit2 - The SQL
All new keynotes, and speakers but the same cinematic quality. Happening on Nov. 15th:
stree.ai/3RqJ0R3
It seems like JOINs are always breaking up the party when we try to make very fast, very scalable databases. Rong Rong and Siddharth Teotia are talking about how @apachepinot’s new multi-stage query engine enables general-purpose JOIN queries while still running fast. #RTASummit
Vaibhav Maheshwari (Staff Engineer, @LinkedIn) is talking about the components of @LinkedIn's Partition Metrics Provider Service (PMP) at #RTASummit. This includes @apachekafka @ApachePinot and #ApacheSamza
Just because you go down the road of Real-Time Analytics doesn’t mean you have to build your whole stack! @MantriM2 is talking about @startreedata ThirdEye, the community-licensed anomaly detection tool that runs on data in @apachepinot. #RTASummit
Currently, @mgrygles is giving a great introduction to event streaming and how @apache_pulsar can power the event-driven data layer that enables Real-Time Analytics. #rtasummit
Before and after architecture @Citi using @ApachePinot and @trinodb. Brought to you by Valentin Mahrwald (Lead of Data Platform @Citi) at #RTASummit.
app.hopin.com/events/real-ti…
Our very own @nehapawar18 and Xiaobing Li gave us a deep-dive into how tiered storage works in @startreedata Cloud.
All happening at #RTASummit
Luis Fernandez of @Etsy is talking at #rtasummit about exposing analytics to sellers. They started with memcached, MySQL, and cron jobs. Stats took hours to be visible to sellers. A new stack with @apachekafka and @ApachePinot got this down to seconds.
app.hopin.com/events/real-ti…
After two very insightful keynotes at #RTASummit, we now have our first speakers coming up. @nehapawar18 and Xiaobing Li are talking about Tiered Storage (East Theatre), and Luis Fernandez about @Etsy and its journey with @ApachePinot (West Theatre).
