--- title: Data Cleaning Got a New Name: Context Engineering description: 'Context engineering' is the AI-era rebrand of data cleaning, data dictionaries, business analysis, and data governance — work that has existed for decades.... canonical: https://daily.dev/posts/data-cleaning-got-a-new-name-context-engineering-h9gs0lpci twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Data Cleaning Got a New Name: Context Engineering | daily.dev og:description: 'Context engineering' is the AI-era rebrand of data cleaning, data dictionaries, business analysis, and data governance — work that has existed for decades.... og:url: https://daily.dev/posts/data-cleaning-got-a-new-name-context-engineering-h9gs0lpci og:image: https://api.daily.dev/og/posts/H9gs0lPci.png og:image:alt: Data Cleaning Got a New Name: Context Engineering og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Data Cleaning Got a New Name: Context Engineering **[Medium](https://daily.dev/sources/medium_js)** · 3 min read · 0 upvotes · 0 comments ## Summary 'Context engineering' is the AI-era rebrand of data cleaning, data dictionaries, business analysis, and data governance — work that has existed for decades. The core argument is that while the terminology is new, the underlying tasks are identical. The rebrand is pragmatically useful because it finally attracts budget and stakeholder attention that data quality work has historically been denied. AI cannot replace this work because the hard decisions require business context that lives in people's heads, not in the data itself. Practical advice is given for both operators and data engineers on how to formalize and fund this work. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### Can AI fully automate data cleaning for AI projects without human input? No, AI can only handle the mechanical parts of data cleaning, such as normalizing date formats, spotting obvious typos, or flagging unusual rows. It cannot make judgment calls that require business context, like determining whether two similarly named customer records are duplicates, whether an outlier is a real data point or an export bug, or whether refunded orders should count as revenue. _Anyone weighing how much to trust AI with data prep can follow context engineering discussions like this on daily.dev._ ### What is the difference between data cleaning and context engineering? There is no real difference in substance; context engineering is described as the same underlying work rebranded with a trendier name that attracts funding. It covers four tasks: cleaning data, documenting what the data means (a data dictionary), defining business rules, and keeping definitions current as the business evolves (data governance). _Teams debating whether to invest in context engineering versus traditional data cleaning can track the terminology shift on daily.dev._ ## Similar posts on daily.dev - [Why context engineering will define the next era of enterprise AI](https://daily.dev/posts/why-context-engineering-will-define-the-next-era-of-enterprise-ai-zyxxtfsqd) · InfoWorld · 2 upvotes · 1 comments - [What is Context Engineering?](https://daily.dev/posts/what-is-context-engineering--fzdcu7uy1) · Decube · 125 upvotes · 11 comments - [Context Engineering: A Definitive Guide](https://daily.dev/posts/context-engineering-a-definitive-guide-wbko2k9kr) · SingleStore · 15 upvotes · 0 comments - [Context Engineering: The Foundation for Reliable AI Agents](https://daily.dev/posts/context-engineering-the-foundation-for-reliable-ai-agents-kkiepi3co) · The New Stack · 1 upvotes · 0 comments - [Context Engineering Is Governance](https://daily.dev/posts/context-engineering-is-governance-x9tctpnv9) · API Evangelist · 0 upvotes · 0 comments --- Tags: [#ai](https://daily.dev/tags/ai), [#data-analysis](https://daily.dev/tags/data-analysis), [#big-data](https://daily.dev/tags/big-data), [#data-quality](https://daily.dev/tags/data-quality), [#context-engineering](https://daily.dev/tags/context-engineering) [View this post on daily.dev](https://daily.dev/posts/data-cleaning-got-a-new-name-context-engineering-h9gs0lpci) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Data Cleaning Got a New Name: Context Engineering","url":"https://daily.dev/posts/data-cleaning-got-a-new-name-context-engineering-h9gs0lpci","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/data-cleaning-got-a-new-name-context-engineering-h9gs0lpci"},"datePublished":"2026-07-21T18:59:40.318Z","dateModified":"2026-09-14T09:09:42.753Z","description":"'Context engineering' is the AI-era rebrand of data cleaning, data dictionaries, business analysis, and data governance — work that has existed for decades....","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/b4e5be609c8b033ed131e12af85695c6?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/b4e5be609c8b033ed131e12af85695c6?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Medium","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Medium","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/medium","url":"https://daily.dev/sources/medium_js"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/data-cleaning-got-a-new-name-context-engineering-h9gs0lpci","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"ai,data-analysis,big-data,data-quality,context-engineering","timeRequired":"PT3M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Medium","item":"https://daily.dev/sources/medium_js"},{"@type":"ListItem","position":3,"name":"Data Cleaning Got a New Name: Context Engineering"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/data-cleaning-got-a-new-name-context-engineering-h9gs0lpci#faq","mainEntity":[{"@type":"Question","name":"Can AI fully automate data cleaning for AI projects without human input?","acceptedAnswer":{"@type":"Answer","text":"No, AI can only handle the mechanical parts of data cleaning, such as normalizing date formats, spotting obvious typos, or flagging unusual rows. It cannot make judgment calls that require business context, like determining whether two similarly named customer records are duplicates, whether an outlier is a real data point or an export bug, or whether refunded orders should count as revenue. Anyone weighing how much to trust AI with data prep can follow context engineering discussions like this on daily.dev."}},{"@type":"Question","name":"What is the difference between data cleaning and context engineering?","acceptedAnswer":{"@type":"Answer","text":"There is no real difference in substance; context engineering is described as the same underlying work rebranded with a trendier name that attracts funding. It covers four tasks: cleaning data, documenting what the data means (a data dictionary), defining business rules, and keeping definitions current as the business evolves (data governance). 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