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10 Best Big Data Analytics Tools You Need To Know in 2023

FineReport

As the world becomes increasingly digitized, the amount of data being generated on a daily basis is growing at an unprecedented rate. This has led to the emergence of the field of Big Data, which refers to the collection, processing, and analysis of vast amounts of data. What is Big Data? What is Big Data?

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Data Brilliance at the Bay: Alation at Databricks Data + AI Summit 2023

Alation

That’s going to be the view at the highly anticipated gathering of the global data, analytics, and AI community — Databricks Data + AI Summit — when it makes its grand return to San Francisco from June 26–29. How does a lakehouse overlooking the Golden Gate Bridge sound? Join us at Summit!

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Introducing Amazon MWAA support for the Airflow REST API and web server auto scaling

AWS Big Data

Apache Airflow is a popular platform for enterprises looking to orchestrate complex data pipelines and workflows. In this post, we’re excited to introduce two new features that address common customer challenges and unlock new possibilities for building robust, scalable, and flexible data orchestration solutions using Amazon MWAA.

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Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

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Enable data analytics with Talend and Amazon Redshift Serverless

AWS Big Data

Today, in order to accelerate and scale data analytics, companies are looking for an approach to minimize infrastructure management and predict computing needs for different types of workloads, including spikes and ad hoc analytics. Prerequisites To complete the integration, you need a Redshift Serverless data warehouse.

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Join a streaming data source with CDC data for real-time serverless data analytics using AWS Glue, AWS DMS, and Amazon DynamoDB

AWS Big Data

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Traditional batch ingestion and processing pipelines that involve operations such as data cleaning and joining with reference data are straightforward to create and cost-efficient to maintain.

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The DataOps Vendor Landscape, 2021

DataKitchen

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Companies that implement DataOps find that they are able to reduce cycle times from weeks (or months) to days, virtually eliminate data errors, increase collaboration, and dramatically improve productivity.

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