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Top 12 Data Engineering Project Ideas [With Source Code]

Knowledge Hut

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. Source: Use Stack Overflow Data for Analytic Purposes 4.

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SQL and Complex Queries Are Needed for Real-Time Analytics

Rockset

Complex SQL queries have long been commonplace in business intelligence (BI). And when systems such as Hadoop and Hive arrived, it married complex queries with big data for the first time. Most analytical queries need this ability to join multiple data sources at query time.

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The Good and the Bad of Apache Spark Big Data Processing

AltexSoft

It has in-memory computing capabilities to deliver speed, a generalized execution model to support various applications, and Java, Scala, Python, and R APIs. Spark Streaming enhances the core engine of Apache Spark by providing near-real-time processing capabilities, which are essential for developing streaming analytics applications.

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Top 6 Big Data and Business Analytics Companies to Work For in 2023

ProjectPro

The company targets to deliver values to its customers through the free SaaS based analytics applications so that it can build credibility with the clients to encourage them to buy more. The products and services of Cloudera are changing the economics of big data analysis , BI, data processing and warehousing through Hadooponomics.

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Object-centric Process Mining on Data Mesh Architectures

Data Science Blog: Data Engineering

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. This aspect can be applied well to Process Mining, hand in hand with BI and AI.

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

ProjectPro

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Calculating the variations between date-column values, etc.

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Turning Streams Into Data Products

Cloudera

Use cases like fraud detection, network threat analysis, manufacturing intelligence, commerce optimization, real-time offers, instantaneous loan approvals, and more are now possible by moving the data processing components up the stream to address these real-time needs. .

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