Alation

FEBRUARY 20, 2020

With the year coming to a close, many look back at the headlines that made major waves in technology and big data – from Spark to Hadoop to trends in data science – the list could go on and on. 2016 will be the year of the “logical data warehouse.” In 2016, these will increasingly be deployed to query multiple data sources.

Data Warehouse 52

Data Warehouse Hadoop Data Science ETL 52

Alation

FEBRUARY 13, 2020

Earlier this month in London, more than 1,600 data and analytics leaders and professionals gathered for the Gartner Data & Analytics Summit. Zaidi’s vision for the value of machine learning data catalogs closely resembles the data cataloging vision presented by our Cofounder Aaron Kalb at Strata + Hadoop World 2016.

Machine Learning 52

Machine Learning Machine Learning Analytics Analytics 52

phData

NOVEMBER 8, 2024

These systems are built on open standards and offer immense analytical and transactional processing flexibility. However, this feature becomes an absolute must-have if you are operating your analytics on top of your data lake or lakehouse. It provided ACID transactions and built-in support for real-time analytics.

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

Smart Data Collective

NOVEMBER 29, 2019

Some of the changes include the following: Big data can be used to identify new link building opportunities through complicated Hadoop data-mining tools. Predictive analytics tools can be used to identify future changes in Google’s algorithms. In 2016, Inc. Lots of courses are being offered on SEO these days.

Big Data 67

Big Data Big Data Data Mining Data Mining 67