Remove Data Architecture Remove Data Warehouse 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

Modernizing the Data Warehouse: Challenges and Benefits

BI-Survey

But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? The following insights came from a global BARC survey into the current status of data warehouse modernization. They are opting for cloud data services more frequently.

Insiders

Sign Up for our Newsletter

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

article thumbnail

Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

AWS Big Data

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis. Create dbt models in dbt Cloud.

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. The past decades of enterprise data platform architectures can be summarized in 69 words. DDD divides a system or model into smaller subsystems called domains.

article thumbnail

The future of data: A 5-pillar approach to modern data management

CIO Business Intelligence

Digital transformation started creating a digital presence of everything we do in our lives, and artificial intelligence (AI) and machine learning (ML) advancements in the past decade dramatically altered the data landscape. The choice of vendors should align with the broader cloud or on-premises strategy.

article thumbnail

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

AWS Big Data

This enables you to extract insights from your data without the complexity of managing infrastructure. dbt has emerged as a leading framework, allowing data teams to transform and manage data pipelines effectively. You can review code changes directly on the platform, facilitating efficient teamwork.

article thumbnail

Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

These strategies, such as investing in AI-powered cleansing tools and adopting federated governance models, not only address the current data quality challenges but also pave the way for improved decision-making, operational efficiency and customer satisfaction. When financial data is inconsistent, reporting becomes unreliable.