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Big Data as a Service (BDaaS): A Comprehensive Overview

Pickl AI

Summary: Big Data as a Service (BDaaS) offers organisations scalable, cost-effective solutions for managing and analysing vast data volumes. By outsourcing Big Data functionalities, businesses can focus on deriving insights, improving decision-making, and driving innovation while overcoming infrastructure complexities.

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A Comprehensive Overview of Data Engineering Pipeline Tools

Marktechpost

ELT Pipelines: Typically used for big data, these pipelines extract data, load it into data warehouses or lakes, and then transform it. It is suitable for distributed and scalable large-scale data processing, providing quick big-data query and analysis capabilities.

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Introduction to Apache NiFi and Its Architecture

Pickl AI

Summary: Apache NiFi is a powerful open-source data ingestion platform design to automate data flow management between systems. Its architecture includes FlowFiles, repositories, and processors, enabling efficient data processing and transformation. What is Apache NiFi?

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A Beginner’s Guide to Data Warehousing

Unite.AI

In this digital economy, data is paramount. Today, all sectors, from private enterprises to public entities, use big data to make critical business decisions. However, the data ecosystem faces numerous challenges regarding large data volume, variety, and velocity. Enter data warehousing!

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Popular Data Transformation Tools: Importance and Best Practices

Pickl AI

Introduction Data transformation plays a crucial role in data processing by ensuring that raw data is properly structured and optimised for analysis. Data transformation tools simplify this process by automating data manipulation, making it more efficient and reducing errors.

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Data architecture strategy for data quality

IBM Journey to AI blog

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

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10 Best Data Engineering Books [Beginners to Advanced]

Pickl AI

The key sectors where Data Engineering has a major contribution include IT, Internet/eCommerce, and Banking & Insurance. Salary of a Data Engineer ranges between ₹ 3.1 Data Storage: Storing the collected data in various storage systems, such as relational databases, NoSQL databases, data lakes, or data warehouses.