Sat.Jul 11, 2020 - Fri.Jul 17, 2020

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Designing a "low-effort" ELT system, using stitch and dbt

Start Data Engineering

Intro A very common use case in data engineering is to build a ETL system for a data warehouse, to have data loaded in from multiple separate databases to enable data analysts/scientists to be able to run queries on this data, since the source databases are used by your applications and we do not want these analytic queries to affect our application performance and the source data is disconnected as shown below.

Systems 130
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Apache Kafka Native MQTT at Scale with Confluent Cloud and Waterstream

Confluent

With billions of Internet of Things (IoT) devices, achieving real-time interoperability has become a major challenge. Together, Confluent, Waterstream, and MQTT are accelerating Industry 4.0 with new Industrial IoT (IIoT) […].

Kafka 139
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Open Source Production Grade Data Integration With Meltano

Data Engineering Podcast

Summary The first stage of every data pipeline is extracting the information from source systems. There are a number of platforms for managing data integration, but there is a notable lack of a robust and easy to use open source option. The Meltano project is aiming to provide a solution to that situation. In this episode, project lead Douwe Maan shares the history of how Meltano got started, the motivation for the recent shift in focus, and how it is implemented.

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The Importance of Data in UX Design

Teradata

The days are gone when defining a user experience was limited to the choice of designers. Now data plays a more important role in the design process than ever before.

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Generative AI Deep Dive: Advancing from Proof of Concept to Production

Speaker: Maher Hanafi, VP of Engineering at Betterworks & Tony Karrer, CTO at Aggregage

Executive leaders and board members are pushing their teams to adopt Generative AI to gain a competitive edge, save money, and otherwise take advantage of the promise of this new era of artificial intelligence. There's no question that it is challenging to figure out where to focus and how to advance when it’s a new field that is evolving everyday. 💡 This new webinar featuring Maher Hanafi, CTO of Betterworks, will explore a practical framework to transform Generative AI prototypes into

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Empowering the Visual Effects Community with the NetFX Platform

Netflix Tech

The cloud-based platform allows vendors, artists and creators to connect and collaborate on visual effects (VFX) from anywhere in the… Continue reading on Netflix TechBlog ».

Cloud 74
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Top 5 Reasons to Attend Kafka Summit Virtually

Confluent

The first-ever virtual Kafka Summit 2020 kicks off next month in the comfort of your home office, couch, spare bedroom, living room, outbuilding, lanai, veranda, or in-home portico, featuring an […].

Kafka 137

More Trending

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Data.What? Whatever You Call It, Stay Away From a Data Mess!

Teradata

Data Warehouse, Data Lake, Data Mesh, Data.What? If you are confused by the proliferation of these IT terms, allow us to shed some light.

IT 69
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Inbox Zero is not a Lifestyle

Zalando Engineering

The following guidelines and tricks help me with task management, time management, planning & prioritization, reacting to ad-hoc situations, and the sense of not having accomplished anything during the day. There is some overlap with our Remote Work Guidelines 1. My meta-advice for applying anything from this article: start with one improvement, don’t try it all at once.

Process 40
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Track Transportation Assets in Real Time with Apache Kafka and Kafka Streams

Confluent

Apache Kafka® is a distributed commit log, commonly used as a multi-tenant data hub to connect diverse source systems and sink systems. Source systems can be systems or records, operational […].

Kafka 70
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Case Study: StoryFire - Scaling a Social Video Platform on MongoDB and Rockset

Rockset

StoryFire is a social platform for content creators to share and monetize their stories and videos. Using Rockset to index data from their transactional MongoDB system , StoryFire powers complex aggregation and join queries for their social and leaderboard features. By moving read-intensive services off MongoDB to Rockset, StoryFire is able to solve two hard challenges: performance and scale.

MongoDB 52
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Leading the Development of Profitable and Sustainable Products

Speaker: Jason Tanner

While growth of software-enabled solutions generates momentum, growth alone is not enough to ensure sustainability. The probability of success dramatically improves with early planning for profitability. A sustainable business model contains a system of interrelated choices made not once but over time. Join this webinar for an iterative approach to ensuring solution, economic and relationship sustainability.

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Forecasting COVID-19 Using Teradata Vantage

Teradata

Teradata data scientists utilized Teradata technologies to develop models to accurately project the number of COVID-19 confirmations and deaths. Learn more.

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Technology Choices at Zalando - Updating our Tech Radar Process

Zalando Engineering

Challenges with our Tech Radar The Zalando Tech Radar is modelled after the Thoughtworks Technology Radar and includes a ring-based scoring for a certain technology/framework along with supplementary information about pros, cons, restrictions, usage, and lessons learned at Zalando available as a knowledge base for our teams. Since publishing, the approach and visualization engine has been used by others and also showcased at conferences as an example of how tech companies manage their technology

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Empower Your Team With Effective Funnel Data Visualizations

Preset

Funnels are a very popular mental model for understanding data. Learn the pros and cons of different funnel data visualizations using Apache Superset.

Data 40
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Streaming Data Into Teradata Vantage using Amazon Kinesis Data Streams (KDS) and AWS Glue Streaming ETL

Teradata

Get step-by-step instructions to set up Teradata Vantage and author AWS Glue Streaming ETL jobs to stream data into Vantage from Amazon Kinesis and visualize the data.

AWS 52
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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?