Sat.May 20, 2023 - Fri.May 26, 2023

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7 Data Engineering Projects To Put On Your Resume

Seattle Data Guy

Starting new data engineering projects can be challenging. Data engineers can get stuck on finding the right data for their data engineering project or picking the right tools. And many of my Youtube followers agree as they confirmed in a recent poll that starting a new data engineering project was difficult. Here were the key… Read more The post 7 Data Engineering Projects To Put On Your Resume appeared first on Seattle Data Guy.

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Layoffs push down scores on Glassdoor: this is how companies respond

The Pragmatic Engineer

👋 Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover topics related to Big Tech and high-growth startups through the lens of engineering managers and senior engineers. In this issue, we cover one out of six topics from today’s subscriber-only The Scoop issue. To get full articles twice a week, subscribe here.

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What is Data Storage and How is it Used?

Analytics Vidhya

As modern companies rely on data, establishing dependable, effective solutions for maintaining that data is a top task for each organization. The complexity of information storage technologies increases exponentially with the growth of data. From physical hard drives to cloud computing, unravel the captivating world of data storage and recognize its ever-evolving role in our […] The post What is Data Storage and How is it Used?

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Keep Your Data Lake Fresh With Real Time Streams Using Estuary

Data Engineering Podcast

Summary Batch vs. streaming is a long running debate in the world of data integration and transformation. Proponents of the streaming paradigm argue that stream processing engines can easily handle batched workloads, but the reverse isn't true. The batch world has been the default for years because of the complexities of running a reliable streaming system at scale.

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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Data Modeling - The Unsung Hero of Data Engineering: Architecture Pattern, Tools and the Future (Part 3)

Simon Späti

Welcome to the third and final installment of our series “Data Modeling: The Unsung Hero of Data Engineering.” If you’ve journeyed with us from Part 1, where we dove into the importance and history of data modeling, or joined us in Part 2 to explore various approaches and techniques, I’m delighted you’ve stuck around. In this third part, we’ll delve into data architecture patterns and their influence on data modeling.

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What's new in Apache Spark 3.4.0 - Structured Streaming and correctness issue

Waitingforcode

Apache Spark is infamous for its correctness issue for chained stateful operations. Fortunately things get improved in each release. The most recent one, the 3.4.0, also got some important changes on that field!

IT 130

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Functional Python, Part III: The Ghost in the Machine

Tweag

Tweagers have an engineering mantra — Functional. Typed. Immutable. — that begets composable software which can be reasoned about and avails itself to static analysis. These are all “good things” for building robust software, which inevitably lead us to using languages such as Haskell, OCaml and Rust. However, it would be remiss of us to snub languages that don’t enforce the same disciplines, but are nonetheless popular choices in industry.

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Data Modeling - The Unsung Hero of Data Engineering: Architecture Pattern, Tools and the Future (Part 3)

Simon Späti

Welcome to the third and final installment of our series “Data Modeling: The Unsung Hero of Data Engineering.” If you’ve journeyed with us from Part 1, where we dove into the importance and history of data modeling, or joined us in Part 2 to explore various approaches and techniques, I’m delighted you’ve stuck around. In this third part, we’ll delve into data architecture patterns and their influence on data modeling.

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Data Freshness Explained: Making Data Consumers Wildly Happy

Monte Carlo

What is data freshness and why is it important? Data freshness, sometimes referred to as data timeliness, is the frequency in which data is updated for consumption. It is an important dimension of data quality and a pillar of data observability because recently refreshed data is more accurate, and thus more valuable. Since it is impractical and expensive to have all data refreshed on a near real-time basis, data engineers ingest and process most analytical data in batches with pipelines designed

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A Deep Dive into GPT Models: Evolution & Performance Comparison

KDnuggets

The blog focuses on GPT models, providing an in-depth understanding and analysis. It explains the three main components of GPT models: generative, pre-trained, and transformers.

IT 130
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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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Top 5 Marketing Trends from a Chief Marketing Officer

Precisely

Author’s note: this article about marketing trends has been adapted from an article originally published in The CMO. What are your goals in 2023, and which marketing trends can help you achieve them? In my role as Chief Marketing Officer (CMO) here at Precisely, an important part of what I do is to keep a finger on the pulse of the latest marketing innovations and strategize with my team around how we may be able to capitalize on industry trends to produce even bigger and better results.

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Representation online matters: practical end-to-end diversification in search and recommender…

Pinterest Engineering

Representation online matters: practical end-to-end diversification in search and recommender systems Bhawna Juneja | Senior Machine Learning Engineer; Pedro Silva | Senior Machine Learning Engineer; Shloka Desai | Machine Learning Engineer II; Ashudeep Singh | Machine Learning Engineer II; Nadia Fawaz | (former) Inclusive AI Tech Lead Introduction Pinterest is a platform designed to bring everyone the inspiration to create a life they love.

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From Data Engineering to Prompt Engineering

Towards Data Science

Solving data preparation tasks with ChatGPT Photo by Ricardo Gomez Angel on Unsplash Data engineering makes up a large part of the data science process. In CRISP-DM this process stage is called “data preparation”. It comprises tasks such as data ingestion, data transformation and data quality assurance. In our article we solve typical data engineering tasks using ChatGPT and Python.

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The Future of AI: Exploring the Next Generation of Generative Models

KDnuggets

What Generative AI is currently capable of and the current challenges it needs to overcome to explore the next wave of generative AI models?

IT 139
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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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Discover Your Data’s Depth: Applications of ArcGIS Bathymetry Webinar

ArcGIS

Discover the power of ArcGIS Bathymetry in our upcoming webinar on June 20th. Learn how this advanced tool can empower your organization.

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Announcing the Public Preview of Azure Databricks support for Azure confidential computing

databricks

We are excited to announce Azure Databricks support for Azure confidential computing (ACC) in preview! With this announcement, customers can run their Azure.

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Unleashing Your Potential: 5 Strategies to Identify Breakout Leadership Opportunities in Tech

DoorDash Engineering

Contrary to popular belief that the key to an exceptional career is the accumulation of skills and experience over time, I believe that taking advantage of breakout opportunities is a game-changer in your career. Characterized by their high-visibility or high-impact nature, these breakout opportunities can propel your career to new heights as you meet their demands for a unique combination of expertise, creativity, and leadership skill.

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Free ChatGPT Course: Use The OpenAI API to Code 5 Projects

KDnuggets

With all the buzz surrounding the ChatGPT. Are you eager to make the most out of it? Here is the FREE video course that offers a comprehensive education about OpenAI API through detailed explanations and hands-on projects.

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How to Drive Cost Savings, Efficiency Gains, and Sustainability Wins with MES

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

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A suite of sample geoprocessing tools for managing hyperlinks

ArcGIS

Learn more about a suite of sample data management tools to enable, add, remove or disable media hyperlinks to feature classes in geodatabases.

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Model Risk Management, a true accelerator to corporate AI

databricks

Special thanks to EY's Mario Schlener, Wissem Bouraoui and Tarek Elguebaly for their support throughout this journey and their contributions to this blog.

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How Michelin Cut Kafka Costs by 35% with Confluent Cloud

Confluent

Learn how Confluent Cloud helped Michelin streamline Apache Kafka® operations, reduce costs, and go to market 8-9 months faster.

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Data Engineering Landscape in the AI-Driven World

KDnuggets

Generative AI has just started to capture the imagination of data engineers, so the impact thus far has been just a fraction of what it will be a year or two from now.

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The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

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Porting ArcGIS Desktop Schematic Diagrams to ArcGIS Pro Network Diagrams

ArcGIS

Learn how to port schematic diagrams created with ArcGIS Schematics to network diagrams from utility or trace networks using ArcGIS Pro

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Driving a Large Language Model Revolution in Customer Service and Support

databricks

Want to build your own LLM-enabled bot? Download our end-to-end solution accelerator here. Business leaders are universally excited for the potential of large.

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Reverse Proxy Mastery: Deploying a Full-Stack Application with Multi-Container Docker and Nginx

Workfall

Reading Time: 6 minutes Sometimes, developing a full-stack application is not the end of the journey for a web developer. Let us take a case scenario whereby, you have a backend, a frontend, and also a database. For such a setup, we would like to make it easy to replicate our application in different environments let’s say development, staging, and production.

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What Are Foundation Models and How Do They Work?

KDnuggets

Foundation models represent a significant advancement in AI, enabling versatile and high-performing models that can be applied across various domains, such as NLP, computer vision, and multimodal tasks.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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ArcGIS and Apache Log4j Vulnerabilities

ArcGIS

Esri's updated statement regarding Log4j vulnerabilities (Log4Shell) and ArcGIS products

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The Executive’s Guide to Data, Analytics and AI Transformation, Part 5: Make informed build vs. buy decisions

databricks

A key piece of your data and AI transformation strategy will involve the decision around which components of the data ecosystem are built.

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One Big Cluster Stuck: Data Asset Standardization

Cloudera

Data asset standardization is the purposeful and carefully planned consolidation of redundant, contradictory reports, processes, and databases into enterprise standards. The proliferation of data assets can have the greatest adverse impact on environmental health; standardization has many health benefits: Reduces the likelihood that ill-constructed assets take down processes, nodes, and clusters Reduces contention and competition for compute and storage Reduces process and service failures and a

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WebLLM: Bring LLM Chatbots to the Browser

KDnuggets

Wouldn't it be cool if you can run LLMs and LLM chatbots natively in your browser? Let's learn more about the WebLLM project, an interesting step in this direction.

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The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.