#data_processing_cycle результаты поиска
How CI/CD pipelines work (explained in 2 mins or less): A CI/CD pipeline is an automated workflow that facilitates continuous integration (CI) and continuous delivery or deployment (CD) by managing code building, testing, and release processes. It integrates the various stages…
A breakdown of 𝗗𝗮𝘁𝗮 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 𝗶𝗻 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 👇 And yes, it can also be used for LLM based systems! It is critical to ensure Data Quality and Integrity upstream of ML Training and Inference Pipelines, trying to do that in the…
Database stuff I’d study if I wanted to understand scaling deeply: Bookmark this. B+ Trees LSM Trees Write-Ahead Logging Two-Phase Commit Three-Phase Commit Read Replicas Leader-Follower Replication Partitioning Query Caching Secondary Indexes Vector Indexes (FAISS, HNSW)…
Data pipelines let you collect, process, and use huge amounts of data efficiently. But building and maintaining these pipelines can be tricky with API rate limits, changing data schemas, etc. In this in-depth course, you'll learn about data ingestion & normalization, data…
𝗛𝗼𝘄 𝘁𝗼 𝗦𝗼𝗹𝘃𝗲 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀 - 𝗧𝗵𝗲 𝗥𝗲𝗮𝗹 𝗣𝗿𝗼𝗰𝗲𝘀𝘀. Most people think data analysis is just running code and making charts. It’s not. It’s a structured problem-solving process. Here’s the framework that actually works. 🧵…
This week in my data engineering journey, I finally understood how data moves... from simple transactions to powerful business insights. Let’s talk about RDBMS, Data Warehouses, Data Lakes, and NoSQL 🧵
Data Science Roles & How They Interact 📊 🌐 Data Engineer: Core Skills: ETL, Data Warehousing, Hadoop/Spark, Coding (Java/Scala), Database Management Collaborates with Analysts and Stakeholders. 💡 🧩 Data Analyst: Core Skills: Analysis, Programming (Python/R), Comment, Cv
Data Pipelines Overview. The method to download the GIF is available at the end. Data pipelines are a fundamental component of managing and processing data efficiently within modern systems. These pipelines typically encompass 5 predominant phases: Collect, Ingest, Store,…
Data in Practice: Hands-on Analysis Program 📅 Starts November 15, 2025 📷 impriindia.com/event/data-in-…
The Evolving Roles for #DataScientists in the Age of Intelligent Automation: codata.org/blog/2025/10/3… #AI #DataScience #ML #MachineLearning
The life cycle of a Data Analysis Project by Northeastern University. Always follow these steps.
Data pipelines will put you in the top 1% of the market. If you could only learn one skill for the next decade, I can't think of anything more critical than learning to move and process data at scale. I like to tell people I'm a Machine Learning Engineer, but in reality, 90% of…
You send a query to @SentientAGI. Everything finishes in just a few seconds. But behind the scenes, here’s what really happens: User → Agent Router → Specialized Agents → GRID → ROMA → Output Layer 🟢 1️⃣ Router: Analyzes the query and determines which agents should…
✂️ Let's break down the 6️⃣steps of #DataScience in this #GCPSketchnote 1️⃣ Data Engineering 2️⃣ Data Analysis 3️⃣ Model Development 4️⃣ ML Engineering 5️⃣ Insights Activation 6️⃣ Orchestration Now, let's see each of these in this thread 👇 1/8
𝗪𝗵𝗮𝘁 𝗶𝘀 𝗗𝗮𝘁𝗮 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴? It refers to collecting, manipulating, and analyzing data to extract useful insights or information. It involves 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗿𝗮𝘄 𝗱𝗮𝘁𝗮 𝗶𝗻𝘁𝗼 𝗺𝗲𝗮𝗻𝗶𝗻𝗴𝗳𝘂𝗹 𝗮𝗻𝗱 𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲…
A breakdown of 𝗗𝗮𝘁𝗮 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 𝗶𝗻 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 👇 And yes, it can also be used for LLM based systems! It is critical to ensure Data Quality and Integrity upstream of ML Training and Inference Pipelines, trying to do that in the…
A breakdown of 𝗗𝗮𝘁𝗮 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 𝗶𝗻 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 👇 And yes, it can also be used for LLM based systems! It is critical to ensure Data Quality and Integrity upstream of ML Training and Inference Pipelines, trying to do that in the…
Key to understanding 𝗟𝗮𝗿𝗴𝗲 𝗦𝗰𝗮𝗹𝗲 𝗗𝗮𝘁𝗮 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 is the ability to 𝗗𝗲𝗰𝗼𝗺𝗽𝗼𝘀𝗲 𝘁𝗵𝗲𝗺 𝗶𝗻𝘁𝗼 𝘀𝗺𝗮𝗹𝗹𝗲𝗿 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹 𝗽𝗶𝗲𝗰𝗲𝘀. Why decompose? ✅ Different Tech Stack in different Layers. ✅ Each Layer can be scaled separately. ✅…
The #Data_Processing_Cycle is a series of steps carried out to extract #information from raw data. Although each step must be taken in order, the order is cyclic. The #output and #storage stage can lead to the repeat of the data collection stage.
The #Data_Processing_Cycle is a series of steps carried out to extract #information from raw data. Although each step must be taken in order, the order is cyclic. The #output and #storage stage can lead to the repeat of the data collection stage.
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