Apps Run The World Apps Purchases

Customer	Industry	Empl.	Revenue	Country	Vendor	Application	Category	When	VAR/SI	Insight Source
The New York Times Company	Media	5800	$2.3B	United States	SAS Institute	SAS Enterprise Miner	Analytics and BI	2018	n/a	In 2018, The New York Times Company implemented SAS Enterprise Miner as a central component of its Analytics and BI environment. The deployment was provisioned across Windows, UNIX and Linux environments to support the publisher's analytics and business intelligence workflows used by statisticians, business analysts and reporting teams. SAS Enterprise Miner was implemented alongside a broad SAS stack including Base SAS, SAS Enterprise Guide, SAS Data Integration Studio, Text Miner, SAS Management Console, SAS Visual Analytics and SAS Forecast Studio to support predictive modeling, text mining, data preparation and reporting. Configuration emphasized model building, SAS macro libraries for reusable transformation logic, PROC SQL based data manipulation and SAS/ODS output generation for HTML, RTF and PDF reporting. Integrations included native connectivity to Oracle Server, Microsoft SQL Server and MS Access via SAS/Access and PROC CONNECT, with capability to import and export CSV, Excel and XML files for downstream consumption. Data Integration Studio was used to design and schedule DI jobs for extract, transform and load processing and to populate data mart structures consumed by SAS Information Map Studio and reporting layers. Governance was aligned to a formal SDLC methodology with deployment and support administered through SAS Management Console and Information Map Studio, scheduled job flows and change control for macro libraries and DI jobs. Operational practices included proactive issue identification, vendor coordination and solution research, preserving consistency of analytic results across environments while supporting model development, scoring and enterprise reporting.
Voice and Script International (VSI) Group	Media	520	$98M	United Kingdom	Microsoft	Microsoft Power BI	Analytics and BI	2019	n/a
	Media	700	$300M	United Kingdom	SplashBI	SplashBI	Analytics and BI	2013	n/a
	Media	7300	$3.1B	United States	Oracle	Oracle Transactional Business Intelligence (OTBI)	Analytics and BI	2017	n/a
	Media	7300	$3.1B	United States	Oracle	Oracle BI Publisher	Analytics and BI	2017	n/a
	Media	5680	$9.0B	United States	Oracle	Oracle BI Publisher	Analytics and BI	2018	n/a
	Media	5680	$9.0B	United States	Alteryx	Alteryx One Platform	Analytics and BI	2020	PwC
	Media	4000	$2.8B	United States	Apache Software	Apache Spark	Analytics and BI	2018	n/a
	Media	160	$30M	United States	Chartbeat	Chartbeat	Analytics and BI	2021	n/a
	Media	21273	$7.2B	United Kingdom	Chartbeat	Chartbeat	Analytics and BI	2014	n/a

Logo

Customer

Industry

Empl.

Revenue

Country

Vendor

Application

Category

When

VAR/SI

Insight

Insight Source

The New York Times Company

Media

5800

$2.3B

United States

SAS Institute

SAS Enterprise Miner

Analytics and BI

2018

n/a

In 2018, The New York Times Company implemented SAS Enterprise Miner as a central component of its Analytics and BI environment. The deployment was provisioned across Windows, UNIX and Linux environments to support the publisher's analytics and business intelligence workflows used by statisticians, business analysts and reporting teams. SAS Enterprise Miner was implemented alongside a broad SAS stack including Base SAS, SAS Enterprise Guide, SAS Data Integration Studio, Text Miner, SAS Management Console, SAS Visual Analytics and SAS Forecast Studio to support predictive modeling, text mining, data preparation and reporting. Configuration emphasized model building, SAS macro libraries for reusable transformation logic, PROC SQL based data manipulation and SAS/ODS output generation for HTML, RTF and PDF reporting. Integrations included native connectivity to Oracle Server, Microsoft SQL Server and MS Access via SAS/Access and PROC CONNECT, with capability to import and export CSV, Excel and XML files for downstream consumption. Data Integration Studio was used to design and schedule DI jobs for extract, transform and load processing and to populate data mart structures consumed by SAS Information Map Studio and reporting layers. Governance was aligned to a formal SDLC methodology with deployment and support administered through SAS Management Console and Information Map Studio, scheduled job flows and change control for macro libraries and DI jobs. Operational practices included proactive issue identification, vendor coordination and solution research, preserving consistency of analytic results across environments while supporting model development, scoring and enterprise reporting.