The data lake has become accepted as an important component of a modern data architecture, enabling a wider variety of data to be accessed by users. Yet, challenges persist. Recently, John O'Brien, ...

Traditional architecture and technologies and newer big data approaches each offer advantages. In a session at Data Summit 2019, titled “Designing a Data Architecture for Modern Business Intelligence ...

Consider a dataset extracted from a windmill within an open data architecture. A team of data scientists analyzes the dataset and uses machine learning (ML) tools to perform predictive analytics. At ...

The data consumers can rely on a single standardized set of data, provided through both streams and tables, to power their operations, analytics, and everything in between. We create the headless ...

To gain business value from data, enterprises need to get their data architecture right – and the right business leadership and culture is critical to that.

Centralizing your data, they argue, makes it easier to apply machine learning and other advanced analytics to get more useful information out of your data. But this strategy is faulty. Centralized ...

To succeed, organizations must design adaptable data architecture that seamlessly integrates, enables collaboration and delivers complementary analytics solutions.

Cloud-based data lakes are the biggest repositories of data today, but they’re not the only place where data lives. By following the precepts of the data mesh architecture, Starburst aims to unify ...

A basic serverless architecture built on 1) infinitely scalable object storage; 2) ETL operations, crawlers, and data catalogs; and 3) an analytics compute engine such as Amazon Athena can work as ...

Dr. Prakriteswar Santikary, chief data officer at ERT, spoke at Data Architecture Summit 2018 Conference last month about data lake architecture his team developed at their clinical research organizat ...