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What is dataPARC Historian?

Harness the complete capabilities of your organization's time-series data through the dataPARC Historian. This innovative solution enhances data management by ensuring seamless and secure data movement throughout your enterprise. Its architecture is designed for straightforward integration with AI, machine learning, and cloud technologies, which fosters creative adaptability and richer insights. With rapid data retrieval, sophisticated manufacturing intelligence, and the ability to scale, the dataPARC Historian emerges as the premier option for companies aiming to excel in their operations. It transcends mere data storage; it is about converting data into actionable insights with remarkable speed and accuracy. The dataPARC Historian is distinguished as more than just a data storage solution. It equips organizations with the flexibility to leverage time-series data more effectively, ensuring that decisions are well-informed and impactful, supported by a platform celebrated for its reliability and user-friendliness. Additionally, its ability to adapt to changing business needs makes it an invaluable asset for future growth and innovation.

What is Robyn?

Robyn is an advanced, open-source tool for Marketing Mix Modeling (MMM) developed by the Marketing Science team at Meta with a focus on experimental applications. Its primary goal is to support advertisers and analysts in creating comprehensive, data-driven models that evaluate the influence of different marketing channels on key business outcomes, such as sales and conversions, while maintaining user privacy through the use of aggregated data. Rather than relying on the tracking of individual users, Robyn leverages historical time-series data by combining marketing spend or reach metrics—including advertisements, promotions, and organic outreach—with performance metrics to assess incremental effects, saturation levels, and carry-over dynamics. The tool employs a blend of traditional statistical methods and innovative machine learning techniques; it utilizes ridge regression to address multicollinearity in complex models, executes time-series decomposition to separate trends from seasonal variations, and applies a multi-objective evolutionary algorithm for optimization purposes. This cutting-edge methodology empowers businesses to achieve a deeper understanding of their marketing performance, enabling them to make data-driven decisions founded on solid analysis. As organizations increasingly prioritize data-driven strategies, tools like Robyn will play a crucial role in enhancing marketing effectiveness and driving growth.

Media

Media

Integrations Supported

AVEVA PI System
App Orchid
Braincube
FactoryTalk Optix
Ignition SCADA
Ndustrial Contxt
Opralog
PARCview
PI Vision
PreCognize
RtDUET
Seeq
TrendMiner
Uptake
Visual KPI

Integrations Supported

Facebook
Facebook Ads
Instagram Ads
Meta Ads
Meta Pixel

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

SaaS
Windows
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

dataPARC

Date Founded

1997

Company Location

United States

Company Website

www.dataparc.com

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

facebookexperimental.github.io/Robyn/

Categories and Features

Data Analysis

Not specified

Data Historians

Not specified

Data Visualization

Not specified

Industrial Automation

Not specified

Industrial IoT

Not specified

IoT Analytics

Not specified

Manufacturing

Not specified

OEE

Not specified

Root Cause Analysis

Not specified

Categories and Features

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