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Top 12 Data Engineering Project Ideas [With Source Code]

Knowledge Hut

Use Stack Overflow Data for Analytic Purposes Project Overview: What if you had access to all or most of the public repos on GitHub? As part of similar research, Felipe Hoffa analysed gigabytes of data spread over many publications from Google's BigQuery data collection. Which queries do you have?

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Types of Data Analytics

U-Next

Data Analytics Illustration. Organizations may alter their company and environment electronically via the use of Data Analytics, rendering them more creative and forward in their judgment call. Diagnostic Analytics offers in-depth perceptions of a specific issue. Predictive Analytics.

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Making smart cities safer with data

Cloudera

These digital tools will allow them to: Effectively aggregate data from various systems and organizations to support multi-functional analytic applications. Cost-effectively ingest, store and utilize data from all IoT devices. Enable comprehensive data security, compliance, and governance for all of the data collected.

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How Big Data Analysis helped increase Walmarts Sales turnover?

ProjectPro

Walmart acquired a small startup Inkiru based in Palo Alto, California to boost its big data capabilites. Inkiru's predictive technology platform pulls data from diverse sources and helps Walmart improve personalization through data analytics. How Walmart uses Big Data? Walmart has a broad big data ecosystem.

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100+ Big Data Interview Questions and Answers 2023

ProjectPro

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. It ensures that the data collected from cloud sources or local databases is complete and accurate.

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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.

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Addressing the Three Scalability Challenges in Modern Data Platforms

Cloudera

In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads. CRM platforms). benchmarking study conducted by independent 3rd party ).