Christophe Blefari

FEBRUARY 24, 2023

Data engineering team moving data manually ( credits ) Dear readers, I hope you had a great week. Each time I look back and I see the amount of Fridays I've spent reading and writing I'm still surprised. For the last 2 newsletters I've tried to ask your for paying support. From number of people who really paid I can see that I failed to either word it correctly, either to propose a newsletter where you see the value of paying for it.

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Kafka Data Lake Data Storage Data 130

U-Next

FEBRUARY 24, 2023

What’s cooler than having thousands of followers on Instagram? It’s the teeny tiny blue tick next to your name that establishes the fact that you as an individual/product/service is popular as well as reliable. The Instagram ‘Blue Tick’ which is a symbol of celebrity, popularity, and influence on the platform has now been made available to all.

Government 98

Government Designing Building IT 98

Towards Data Science

FEBRUARY 24, 2023

The Chaos Data-Engineering Manifesto Another lesson we can learn from software engineers: break stuff to make it more reliable. Photo by Soheb Zaidi on Unsplash It’s midnight in the dim and cluttered office of The New York Times currently serving as the “situation room.” A powerful surge of traffic is inevitable. During every major election, the wave would crest and crash against our overwhelmed systems before receding, allowing us to assess the damage.

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Data Engineering Data Engineer Engineering Software Engineer 97

KDnuggets

FEBRUARY 24, 2023

Learn about three levels of data science to make the quantum leap to the next level.

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Data Science Data 133

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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.

Database

Engineering at Meta

FEBRUARY 24, 2023

While VR headsets have been with us for at least a decade, AR hardware barely exists today; indeed, the very components that will comprise the hardware scarcely exist, making it a truly zero-to-one innovation challenge. Meta’s Head of AR Glasses Hardware, Caitlin Kalinowski is helping to lead that charge. Kalinowski hails from Portsmouth, NH and studied mechanical engineering at Stanford University.

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Engineering Designing Technology IT 90

KDnuggets

FEBRUARY 24, 2023

This article will discuss SQL visualization, its role in augmenting the modern-day data engineer, and five categories of SQL visualization tools.

SQL 99

SQL Data Engineering Data Engineer Engineering 99

Engineering at Meta

FEBRUARY 24, 2023

While VR headsets have been with us for at least a decade, AR hardware barely exists today; indeed, the very components that will comprise the hardware scarcely exist, making it a truly zero-to-one innovation challenge. Meta’s Head of AR Glasses Hardware, Caitlin Kalinowski is helping to lead that charge. Kalinowski hails from Portsmouth, NH and studied mechanical engineering at Stanford University.

Engineering 68

Engineering Designing Technology IT 68

Hevo

FEBRUARY 24, 2023

Marketing analytics metrics are essential for gaining access to insightful data that may boost sales, profitability, and brand recognition. The right analytics tools can help locate new markets, audience segments, and potential growth regions. However, with the vast amount of data available, it can be challenging to make sense of it all.

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Accessible Accessibility IT Data 52

ArcGIS

FEBRUARY 24, 2023

With a substantial interest in radar, Esri has released a series of capabilities and tools to work with Synthetic Aperture Radar (SAR).

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Deep Learning 52

Hevo

FEBRUARY 24, 2023

Marketing analytics is essential to understand the marketing impact and predict marketing trends to drive sales. Various marketing analytics processes are used by businesses to improve marketing strategies and the overall performance of an organization.

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Process Data 52

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.

Certification

ArcGIS

FEBRUARY 24, 2023

The ArcGIS Business Analyst Pro team started the year off big with the February 2023 release! Read all about it!

Business Analyst 52

Business Analyst IT 52

Lyft Engineering

FEBRUARY 24, 2023

by Alex Chin and Tony Qin Photo by Lisheng Chang on Unsplash The health of Lyft’s marketplace depends on how riders and drivers are distributed across space and time. Within the complex rideshare space, it is not easy to define typical marketplace concepts like “market efficiency” and “supply-demand balance”. A simple question such as “Do we have enough drivers right now?

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Transportation Utilities Systems Algorithm 98

Rockset

FEBRUARY 24, 2023

Introduction Let’s get this out of the way at the beginning: understanding effective streaming data architectures is hard, and understanding how to make use of streaming data for analytics is really hard. Kafka or Kinesis ? Stream processing or an OLAP database? Open source or fully managed? This blog series will help demystify streaming data, and more specifically, provide engineering leaders a guide for incorporating streaming data into their analytics pipelines.

Kafka 52

Kafka AWS Amazon Web Services Programming Language 52

Towards Data Science

FEBRUARY 24, 2023

Build clean nested data models for use in data engineering pipelines Photo by Didssph on Unsplash Introduction Pydantic is an incredibly powerful library for data modeling and validation that should become a standard part of your data pipelines. Part of what makes them so powerful is they can easily accommodate nested data files like JSON. For a quick refresher, Pydantic is a Python library that lets you define a data model in a Pythonic way, and use that model to validate data inputs, mainly t

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Data Python Data Pipeline Data Engineering 83

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Data Science