Project Related Topics 
The Pragmatic Engineer
JUNE 1, 2023
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.
Start Data Engineering
JUNE 14, 2024
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.
Christophe Blefari
OCTOBER 19, 2023
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.
Analytics Vidhya
SEPTEMBER 20, 2023
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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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.
Start Data Engineering
MAY 11, 2022
Introduction 2. Objective 3. Prerequisite 4.2 AWS Infrastructure costs 4.3 Data lake structure 5. Code walkthrough 5.1 Loading user purchase data into the data warehouse 5.2 Loading classified movie review data into the data warehouse 5.3 Generating user behavior metric 5.4. Checking results 6. Tear down infra 7. Design considerations 8.
KDnuggets
JANUARY 23, 2024
Here are data repositories that will up your data science game and improve your data projects.
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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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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.
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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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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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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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?
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Every data-driven project calls for a review of your data architecture—and that includes embedded analytics. Before you add new dashboards and reports to your application, you need to evaluate your data architecture with analytics in mind.
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Great dashboards lead to richer user experiences and significant return on investment (ROI), while poorly designed dashboards distract users, suppress adoption, and can even tarnish your project or brand.
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