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Data Engineering Projects

Start Data Engineering

Projects 3.1. Projects from least to most complex 3.2. Introduction 2. Run Data Pipelines 2.1. Run on codespaces 2.2. Run locally 3. Batch pipelines 3.3. Stream pipelines 3.4. Event-driven pipelines 3.5. LLM RAG pipelines 4. Conclusion 1.

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An educational side project

The Pragmatic Engineer

I’d like to share a story about an educational side project which could prove fruitful for a software engineer who’s seeking a new job. Juraj created a systems design explainer on how he built this project, and the technologies used: The systems design diagram for the Rides application The app uses: Node.js Persistence.

Education 363
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dbt multi-project collaboration

Christophe Blefari

cross-project dependencies ( credits ) Over the last few years, dbt has become a de facto standard enabling companies to collaborate easily on data transformations. Whatever the number, there will be a critical point at which a single project no longer scale. Cross-project references is a key enabler to data team decentralisation.

Project 264
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Top 20 Data Engineering Project Ideas [With Source Code]

Analytics Vidhya

Aspiring data engineers often seek real-world projects to gain hands-on experience and showcase their expertise. This article presents the top 20 data engineering project ideas with their source code. Whether you’re […] The post Top 20 Data Engineering Project Ideas [With Source Code] appeared first on Analytics Vidhya.

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Entity Resolution Checklist: What to Consider When Evaluating Options

It can be confusing to determine which features are most important for your project. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! Are you trying to decide which entity resolution capabilities you need? And sometimes key features are overlooked.

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7 Computer Vision Projects for All Levels

KDnuggets

Each project, from beginner tasks like Image Classification to advanced ones like Anomaly Detection, includes a link to the dataset and source code for easy access and implementation.

Project 135
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10 GitHub Repositories for Advanced Machine Learning Projects

KDnuggets

Where can you find projects dealing with advanced ML topics? GitHub is a perfect source with its many repositories. I’ve selected ten to talk about in this article.

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New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.

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5 Early Indicators Your Embedded Analytics Will Fail

In this White Paper, Logi Analytics has identified 5 tell-tale signs your project is moving from “nice to have” to “needed yesterday.". Many application teams leave embedded analytics to languish until something—an unhappy customer, plummeting revenue, a spike in customer churn—demands change. But by then, it may be too late.

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3 Challenges of Building Complex Dashboards with Open Source Components

Speaker: Ryan MacCarrigan, Founding Principal, LeanStudio

Watch this webinar with Ryan MacCarrigan, Founding Principal of LeanStudio, to learn about key considerations for launching your next analytics project. But what happens when you have a growing user base and additional feature requests?

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development!

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Why “Build or Buy?” Is the Wrong Question for Analytics

Every time an application team gets caught up in the “build vs buy” debate, it stalls projects and delays time to revenue. There is a third option. Partnering with an analytics development platform gives you the freedom to customize a solution without the risks and long-term costs of building your own.

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The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data and AI

Speaker: Aindra Misra, Sr. Staff Product Manager of Data & AI at BILL (Previously PM Lead at Twitter/X)

Anticipated future use cases as we project into 2024 and beyond. Examine real world use cases, both internal and external, where data analytics is applied, and understand its evolution with the introduction of Gen AI.

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How to Find and Test Assumptions in Product Development

You'll learn: Why every product leader goes into a new project with untested, hidden assumptions. Watch this webinar with Laura Klein, product manager and author of Build Better Products, to learn how to spot the unconscious assumptions which you’re basing decisions on and guidelines for validating (or invalidating) your ideas.

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The Essential Guide to Building Analytic Applications

What should product managers keep in mind when adding an analytics project to their roadmap? What are best practices when designing the UI and UX of embedded dashboards, reports, and analytics? What should software teams know about implementing security that works with the rest of their products?