Remove Data Lake Remove Data Warehouse Remove Interactive Remove Modeling
article thumbnail

Build an Amazon Redshift data warehouse using an Amazon DynamoDB single-table design

AWS Big Data

In traditional databases, we would model such applications using a normalized data model (entity-relation diagram). These types of queries are suited for a data warehouse. Amazon Redshift is fully managed, scalable, cloud data warehouse. To house our data, we need to define a data model.

article thumbnail

Data Modeling 301 for the cloud: data lake and NoSQL data modeling and design

erwin

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Data Modeling.

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

Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 103
article thumbnail

5 things on our data and AI radar for 2021

O'Reilly on Data

The data that powers ML applications is as important as code, making version control difficult; outputs are probabilistic rather than deterministic, making testing difficult; training a model is processor intensive and time consuming, making rapid build/deploy cycles difficult. A Wave of Cloud-Native, Distributed Data Frameworks.

Data Lake 296
article thumbnail

Data Modeling 201 for the cloud: designing databases for data warehouses

erwin

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Figure 1: Pricing for a 4 TB data warehouse in AWS.

article thumbnail

Enable business users to analyze large datasets in your data lake with Amazon QuickSight

AWS Big Data

Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. As part of their solution, they are using Amazon QuickSight to unlock insights from their data.

article thumbnail

Simplify operational data processing in data lakes using AWS Glue and Apache Hudi

AWS Big Data

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.