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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...
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2 Top Python Libraries to Create ML model

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To Create a Model of Machine Learning in Python, you need TWO libraries. One is 'NUMPY' and the other one is 'PANDAS'.
Libraries You Need to Create ML Model

2 Top Libraries You Need


To Build a model of Machine learning you need the right kind of data. So, use the data for your project should be refined. Else, it will not produce correct results. The prime steps are Data Analysis and Data Preprocessing.

  1. NUMPY - It has the capabilities of Calculations.
  2. PANDAS- It has the capabilities of Data processing.

How Install Python Machine Learning Libraries 

import NumPy as np # linear algebra
import pandas as PD # data processing, CSV file I/O (e.g. PD.read_csv)


How to Check NumPy/Pandas installed

After '.' you need to give double underscore on both sides of the version. 

how to check numpy or pandas version


How Many Types of Data You Need

You need two types of data. One is data to build a model and the other one is data you need to test the model.
  1. Raw data
  2. Evaluate-data


How to Build a Model Flowchart

I have given a flowchart to build a model along with sample data.

Comments

  1. Alfred AvinaFebruary 4, 2020 at 6:13 PM

    Big data solutions developer should understand the need of Data, and they should work to build more appropriate services to meet the requirements of their clients.


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