Sat.May 09, 2020 - Fri.May 15, 2020

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Change Data Capture Using Debezium Kafka and Pg

Start Data Engineering

Change data capture is a software design pattern used to capture changes to data and take corresponding action based on that change. The change to data is usually one of read, update or delete. The corresponding action usually is supposed to occur in another system in response to the change that was made in the source system.

Kafka 246
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Drafting Your Data Pipelines

Team Data Science

With careful consideration and learning about your market, the choices you need to make become narrower and more clear. I can now begin drafting my data ingestion/ streaming pipeline without being overwhelmed. For A Quick Recap You can find the first blog post here, where I learned which tech is most in demand in Toronto: [link] And the second blog post is here where I learn which Toronto industries need data engineers the most: [link] The Pipeline Proposal I'll be creating several pipelines in

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Apache Kafka Needs No Keeper: Removing the Apache ZooKeeper Dependency

Confluent

Currently, Apache Kafka® uses Apache ZooKeeper™ to store its metadata. Data such as the location of partitions and the configuration of topics are stored outside of Kafka itself, in a […].

Kafka 145
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StreamNative Brings Streaming Data To The Cloud Native Landscape With Pulsar

Data Engineering Podcast

Summary There have been several generations of platforms for managing streaming data, each with their own strengths and weaknesses, and different areas of focus. Pulsar is one of the recent entrants which has quickly gained adoption and an impressive set of capabilities. In this episode Sijie Guo discusses his motivations for spending so much of his time and energy on contributing to the project and growing the community.

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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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COVID-19: The Perfect Storm

Teradata

The COVID-19 pandemic has brought with it a Perfect Storm of disruption that impacts all of us -- from our health to the economy to the supply chain. Read more.

IT 105
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Getting Started - Installing Apache Superset

Preset

Setting up Apache Superset for the first time can be difficult. Here's an easy way to accomplish the task!

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From Eager to Smarter in Apache Kafka Consumer Rebalances

Confluent

Everyone wants their infrastructure to be highly available, and ksqlDB is no different. But crucial properties like high availability don’t come without a thoughtful, rigorous design. We thought hard about […].

Kafka 111
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Announcing ksqlDB 0.9.0

Confluent

We’re pleased to announce the release of ksqlDB 0.9.0! This version includes support for multi-join statements, enhanced LIKE expressions, and a host of usability improvements. We’ll go through a few […].

Process 94
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How China is Using Advanced Analytics During the COVID-19 Pandemic

Teradata

Learn how advanced analytics are being used in China amidst the COVID-19 pandemic to help combat the spread of coronavirus now and in the future.

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Emulate Your Heroes with Data… and Vantage on AWS

Teradata

Teradata's top-ranked analytic software capabilities that market-leading companies have been using for years is available right now on Amazon Web Services (AWS). Learn more.

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Understanding User Needs and Satisfying Them

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.