Remove Data Analytics Remove Data Processing Remove Data Warehouse Remove Modeling
article thumbnail

Power analytics as a service capabilities using Amazon Redshift

AWS Big Data

Analytics as a service (AaaS) is a business model that uses the cloud to deliver analytic capabilities on a subscription basis. This model provides organizations with a cost-effective, scalable, and flexible solution for building analytics. times better price-performance than other cloud data warehouses.

article thumbnail

Implement data warehousing solution using dbt on Amazon Redshift

AWS Big Data

For more information, refer SQL models. Seeds – These are CSV files in your dbt project (typically in your seeds directory), which dbt can load into your data warehouse using the dbt seed command. In an optimal environment, we store the credentials in AWS Secrets Manager and retrieve them.

Insiders

Sign Up for our Newsletter

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

article thumbnail

Design a data mesh pattern for Amazon EMR-based data lakes using AWS Lake Formation with Hive metastore federation

AWS Big Data

One of the key challenges in modern big data management is facilitating efficient data sharing and access control across multiple EMR clusters. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated. The producer account will host the EMR cluster and S3 buckets.

article thumbnail

Setting up and Getting Started with Cloudera’s New SQL AI Assistant

Cloudera

As described in our recent blog post , an SQL AI Assistant has been integrated into Hue with the capability to leverage the power of large language models (LLMs) for a number of SQL tasks. This is a real game-changer for data analysts on all levels and will make SQL development faster, easier, and less error-prone.

article thumbnail

Take Your SQL Skills To The Next Level With These Popular SQL Books

datapine

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

article thumbnail

Architectural Patterns for real-time analytics using Amazon Kinesis Data Streams, Part 2: AI Applications

AWS Big Data

Select the best recipe matching your use case after importing your datasets into a dataset group using Amazon Simple Storage Service (Amazon S3), and then create a solution to train a model by creating a solution version. First, it persists all streamed interactions so they will be incorporated into future retrainings of your model.

IoT 90
article thumbnail

How Macmillan Publishers authored success using IBM Cognos Analytics

IBM Big Data Hub

It’s no wonder then that Macmillan needs sophisticated business intelligence (BI) and data analytics. This data is leveraged by departments throughout the organization and is essential to their business operations. As business processes grew more complex, the data transparency and visibility suffered.