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Big Data Analytics: How It Works, Tools, and Real-Life Applications

AltexSoft

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

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Big Data Timeline- Series of Big Data Evolution

ProjectPro

"Big data is at the foundation of all of the megatrends that are happening today, from social to mobile to the cloud to gaming."- ”- Atul Butte, Stanford With the big data hype all around, it is the fuel of the 21 st century that is driving all that we do. .”- said Chris Lynch, the ex CEO of Vertica.

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Google Cloud vs AWS- Which is Better: A Comparison

Knowledge Hut

Amazon Web Services (AWS) A subsidiary of Amazon.com, this cloud computing service was launched in 2006. Big data, computing, storage, web, databases, AI and ML are just a few of the services offered by AWS and GCP. If you are looking for a platform that offers Big data solutions effectively, then GCP is a good option.

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How LinkedIn uses Hadoop to leverage Big Data Analytics?

ProjectPro

Table of Contents LinkedIn Hadoop and Big Data Analytics The Big Data Ecosystem at LinkedIn LinkedIn Big Data Products 1) People You May Know 2) Skill Endorsements 3) Jobs You May Be Interested In 4) News Feed Updates Wondering how LinkedIn keeps up with your job preferences, your connection suggestions and stories you prefer to read?

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15+ AWS Projects Ideas for Beginners to Practice in 2023

ProjectPro

Orchestrate Redshift ETL using AWS Glue and Step Functions AWS Projects for Portfolio 17. Sentiment Analysis on Real-time Twitter Data 23. AWS Athena Big Data Project for Querying COVID-19 Data 25. Build an AWS ETL Data Pipeline in Python on YouTube Data 26. Serverless Image Recognition Engine 13.

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Google BigQuery: A Game-Changing Data Warehousing Solution

ProjectPro

The three essential functions of combining Google Analytics and BigQuery include- 1) Data Manipulation BigQuery allows for data manipulation and transformation, such as filtering, joins, and aggregations, which helps to prepare the data for analysis and visualization. While a field name is optional, the type must be specified.

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AWS vs Azure-Who is the big winner in the cloud war?

ProjectPro

For big data, EBS storage is incredibly fast. Big data poses challenges for standard storage, demanding the use of premium storage. For big data, much more advanced cloud infrastructure is required. Although Azure's services are less developed for big data, they are improving.

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