Building the Pipes: Core Data Engineering Concepts Explained
The article discusses core concepts in data engineering, emphasizing its importance in modern businesses. It explains batch and streaming ingestion methods, highlighting their characteristics, pros, and cons. Additionally, it covers Change Data Capture (CDC) as an efficient way to manage data changes in real-time.
- ▪Data engineering involves designing systems for collecting, storing, and managing data for various business needs.
- ▪Batch ingestion processes data in large chunks at scheduled intervals, while streaming ingestion handles data continuously in real-time.
- ▪Change Data Capture (CDC) efficiently captures only the changes in a database, minimizing resource use and improving performance.
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| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/lawrence_murithi/building-the-pipes-core-data-engineering-concepts-explained-clk |
| Publication time | Wed, 27 May 2026 20:53:29 +0000 |
| Retrieval time | 2026-05-27T21:08:04.683Z |
| Last seen | 2026-05-27T21:08:04.683Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 5mMmcDCgq-qX |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3713327) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Lawrence Murithi Posted on May 27 Building the Pipes: Core Data Engineering Concepts Explained #dataengineering Introduction Data engineering is the practice of designing and building systems for collecting, storing, transforming, and managing data so it can be safely used for reporting, analytics, machine learning, and making business decisions. Think of it as the behind-the-scenes work that makes apps, websites, and businesses function. Every modern company depends on data.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
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