Remove Data Architecture Remove Data Warehouse Remove Structured Data Remove Testing
article thumbnail

Create a modern data platform using the Data Build Tool (dbt) in the AWS Cloud

AWS Big Data

A modern data platform entails maintaining data across multiple layers, targeting diverse platform capabilities like high performance, ease of development, cost-effectiveness, and DataOps features such as CI/CD, lineage, and unit testing. It’s raw, unprocessed data straight from the source. usr/local/airflow/.local/bin/dbt

article thumbnail

Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Insiders

Sign Up for our Newsletter

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

article thumbnail

The hidden history of Db2

IBM Big Data Hub

In today’s world of complex data architectures and emerging technologies, databases can sometimes be undervalued and unrecognized. Nedbank builds a scalable data warehouse architecture . Endless data but your queries aren’t fast enough. Vektis improves healthcare quality through data .

article thumbnail

How GamesKraft uses Amazon Redshift data sharing to support growing analytics workloads

AWS Big Data

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

article thumbnail

Data platform trinity: Competitive or complementary?

IBM Big Data Hub

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. This storage architecture is inflexible and inefficient.

article thumbnail

Implement slowly changing dimensions in a data lake using AWS Glue and Delta

AWS Big Data

In a data warehouse, a dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. Test SCD Type 2 implementation With the infrastructure in place, you’re ready to test out the overall solution design and query historical records from the employee dataset.

article thumbnail

How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.