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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project. And, out of these professions, this blog will discuss the data engineering job role.

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Differences Between Business Intelligence vs Data Science

Knowledge Hut

Data Usage It stores the data in a sorted manner for future use. It uses data from the past and present to make decisions related to future growth. Data Type Data science deals with both structured and unstructured data. Business Intelligence only deals with structured data.

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Spark vs Hive - What's the Difference

ProjectPro

Apache Hive and Apache Spark are the two popular Big Data tools available for complex data processing. To effectively utilize the Big Data tools, it is essential to understand the features and capabilities of the tools. Spark SQL, for instance, enables structured data processing with SQL.

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Deciphering the Data Enigma: Big Data vs Small Data

Knowledge Hut

Big Data Training online courses will help you build a robust skill-set working with the most powerful big data tools and technologies. Big Data vs Small Data: Velocity Big Data is often characterized by high data velocity, requiring real-time or near real-time data ingestion and processing.

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20 Solved End-to-End Big Data Projects with Source Code

ProjectPro

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies.

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Top 16 Data Science Job Roles To Pursue in 2024

Knowledge Hut

According to the World Economic Forum, the amount of data generated per day will reach 463 exabytes (1 exabyte = 10 9 gigabytes) globally by the year 2025. Thus, almost every organization has access to large volumes of rich data and needs “experts” who can generate insights from this rich data.

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Top ETL Use Cases for BI and Analytics:Real-World Examples

ProjectPro

However, the vast volume of data will overwhelm you if you start looking at historical trends. The time-consuming method of data collection and transformation can be eliminated using ETL. You can analyze and optimize your investment strategy using high-quality structured data. PREVIOUS NEXT <

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