Remove Data Processing Remove Data Warehouse Remove Events Remove Optimization
article thumbnail

How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse. In this post, we show how smava optimized their data platform by using Amazon Redshift Serverless and Amazon Redshift data sharing to overcome right-sizing challenges for unpredictable workloads and further improve price-performance.

article thumbnail

Power enterprise-grade Data Vaults with Amazon Redshift – Part 2

AWS Big Data

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Real-time streaming data top picks you cannot miss at AWS re:Invent 2023

AWS Big Data

Join us as we delve into the world of real-time streaming data at re:Invent 2023 and discover how you can use real-time streaming data to build new use cases, optimize existing projects and processes, and reimagine what’s possible. High-quality data is not just about accuracy; it’s also about timeliness.

article thumbnail

Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT

AWS Big Data

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. Amazon Redshift is straightforward to use with self-tuning and self-optimizing capabilities. Fault tolerance is built in. Create the S3 bucket and folder.

article thumbnail

Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

You can subscribe to data products that help enrich customer profiles, for example demographics data, advertising data, and financial markets data. Amazon Kinesis ingests streaming events in real time from point-of-sales systems, clickstream data from mobile apps and websites, and social media data.

article thumbnail

Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. Cold storage is optimized to store infrequently accessed or historical data.

Data Lake 112
article thumbnail

Deciphering The Seldom Discussed Differences Between Data Mining and Data Science

Smart Data Collective

Then artificial intelligence advances became more widely used, which made it possible to include optimization and informatics in analysis methods. This new approach has proven to be much more effective, so it is a skill set that people must master to become data scientists. Where to Use Data Science? Practical experience.