Remove Data Architecture Remove Data Lake Remove Modeling
article thumbnail

What is data architecture? A framework to manage data

CIO Business Intelligence

Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). An organizations data architecture is the purview of data architects.

article thumbnail

Modernize your legacy databases with AWS data lakes, Part 2: Build a data lake using AWS DMS data on Apache Iceberg

AWS Big Data

This is part two of a three-part series where we show how to build a data lake on AWS using a modern data architecture. This post shows how to load data from a legacy database (SQL Server) into a transactional data lake ( Apache Iceberg ) using AWS Glue. Delete the bucket.

Data Lake 101
Insiders

Sign Up for our Newsletter

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

article thumbnail

From data lakes to insights: dbt adapter for Amazon Athena now supported in dbt Cloud

AWS Big Data

The need for streamlined data transformations As organizations increasingly adopt cloud-based data lakes and warehouses, the demand for efficient data transformation tools has grown. This enables you to extract insights from your data without the complexity of managing infrastructure.

article thumbnail

What is a Data Mesh?

DataKitchen

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt.

article thumbnail

Eight Top DataOps Trends for 2022

DataKitchen

In 2022, data organizations will institute robust automated processes around their AI systems to make them more accountable to stakeholders. Model developers will test for AI bias as part of their pre-deployment testing. Continuous testing, monitoring and observability will prevent biased models from deploying or continuing to operate.

Testing 245
article thumbnail

Unleash deeper insights with Amazon Redshift data sharing for data lake tables

AWS Big Data

Over the years, this customer-centric approach has led to the introduction of groundbreaking features such as zero-ETL , data sharing , streaming ingestion , data lake integration , Amazon Redshift ML , Amazon Q generative SQL , and transactional data lake capabilities.

Data Lake 102
article thumbnail

The next generation of Amazon SageMaker: The center for all your data, analytics, and AI

AWS Big Data

They’re taking data they’ve historically used for analytics or business reporting and putting it to work in machine learning (ML) models and AI-powered applications. Amazon SageMaker Unified Studio (Preview) solves this challenge by providing an integrated authoring experience to use all your data and tools for analytics and AI.