TDAN

JUNE 16, 2020

When companies embark on a journey of becoming data-driven, usually, this goes hand in and with using new technologies and concepts such as AI and data lakes or Hadoop and IoT. Suddenly, the data warehouse team and their software are not the only ones anymore that turn data […].

Data Warehouse 52

Data Warehouse Data-driven Data Lake IoT 52

CIO Business Intelligence

NOVEMBER 29, 2022

A sea of complexity For years, data ecosystems have gotten more complex due to discrete (and not necessarily strategic) data-platform decisions aimed at addressing new projects, use cases, or initiatives. Layering technology on the overall data architecture introduces more complexity.

Data Architecture 103

Data Architecture Data Integration IoT Strategy 103

Cloudera

DECEMBER 19, 2018

Growth factors and business priority are ever changing. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Natural language analytics and streaming data analytics are emerging technologies that will impact the market.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. This storage architecture is inflexible and inefficient.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Alation

APRIL 14, 2022

Similar to a data warehouse schema, this prep tool automates the development of the recipe to match. Integrating data from your own ERP and CRM systems may be a chore, but for today’s data-aware applications, the fabric of data is multi-colored. On-premises business intelligence and databases.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

O'Reilly on Data

SEPTEMBER 11, 2019

Our call for speakers for Strata NY 2019 solicited contributions on the themes of data science and ML; data engineering and architecture; streaming and the Internet of Things (IoT); business analytics and data visualization; and automation, security, and data privacy. Stream” itself was No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20