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Five Ways to Run Analytics on MongoDB – Their Pros and Cons

Rockset

MongoDB is a top database choice for application development. Developers choose this database because of its flexible data model and its inherent scalability as a NoSQL database. MongoDB wasn’t originally developed with an eye on high performance for analytics. Third, there are no relational joins available in MongoDB.

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Case Study: Is Your NoSQL Data Hindering Real-Time Analytics? Savvy Solved It with Rockset.

Rockset

All interactions are streamed in the form of semi-structured events into Firebase’s NoSQL cloud database, where the data, which includes a large number of nested objects and arrays, is ingested. We ended up deploying a real-time analytics platform, Rockset , on top of MongoDB. It feels like magic!

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Python for Data Engineering

Ascend.io

Use Case: Transforming monthly sales data to weekly averages import dask.dataframe as dd data = dd.read_csv('large_dataset.csv') mean_values = data.groupby('category').mean().compute() compute() Data Storage Python extends its mastery to data storage, boasting smooth integrations with both SQL and NoSQL databases.

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14 Best Database Certifications in 2023 to Boost Your Career

Knowledge Hut

Over the past decade, the IT world transformed with a data revolution. The rise of big data and NoSQL changed the game. Systems evolved from simple to complex, and we had to split how we find data from where we store it. Skills acquired : Relational database concepts Retrieving data using the SQL SELECT statement.

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Most important Data Engineering Concepts and Tools for Data Scientists

DareData

For data scientists, these skills are extremely helpful when it comes to manage and build more optimized data transformation processes, helping models achieve better speed and relability when set in production. Examples of NoSQL databases include MongoDB or Cassandra.

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The Good and the Bad of Apache Kafka Streaming Platform

AltexSoft

This enables systems using Kafka to aggregate data from many sources and to make it consistent. Instead of interfering with each other, Kafka consumers create groups and split data among themselves. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift.

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Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

Flume functions well in streaming data sources which are generated continuously in hadoop environment such as log files from multiple servers whereas Apache Sqoop is designed to work well with any kind of relational database system that has JDBC connectivity. Sqoop is not event-driven.