ABOUT SEEQ CORPORATION

Seeq® is an advanced analytics solution for process manufacturing data that enables organizations to rapidly investigate and share insights from data in historians, IIoT platforms, and database web services—as well as contextual data in manufacturing and business systems. Seeq’s extensive support for time series data and its inherent challenges enables organizations to derive more value from data already collected by accelerating analytics, publishing, and decision making. With diagnostic, monitoring, and predictive analytics powered by innovations in big data and machine learning technologies, Seeq’s advanced analytics solutions help organizations turn data into insights to drive process improvement and increase profitability. 

 
5 Questions To Ask Before Selecting A Process Data Analytics Solution   Leveraging Predictive Analytics: A Case Study   Devon Energy Uses Real-Time Data And Advanced Analytics To Make Better Decisions

5 Questions To Ask Before Selecting A Process Data Analytics Solution

 

Leveraging Predictive Analytics: A Case Study

 

Devon Energy Uses Real-Time Data And Advanced Analytics To Make Better Decisions

FEATURED PRODUCTS

Seeq Workbench Seeq Workbench

Workbench is Seeq’s application for engineers engaged in diagnostic, descriptive, and predictive analytics with process manufacturing data.

Seeq Organizer Seeq Organizer

Organizer is Seeq’s application for engineers and managers to assemble and distribute Seeq analyses as reports, dashboards, and web pages.

CONTACT INFORMATION

Seeq Corporation

1301 2nd Avenue Suite 2850

Seattle, WA 98101

UNITED STATES

Phone: 206-801-9339

Contact: Jennifer Bentzel

SEEQ SOCIAL MEDIA

        

FEATURED ARTICLES

  • Gas Processing Data Analysis From Afar
    Gas Processing Data Analysis From Afar

    Unmanned well sites in remote locations present operational challenges. Data must not only be collected, but it also must be monitored to uncover any discrepancies, and ideally predict any problems before they occur. Advanced analytics software, coupled with a sophisticated data collection system, can address these issues, and also provide additional benefits.

  • Adding Value With Analytics
    Adding Value With Analytics

    The oil and gas industry, like many others, is collecting and storing ever larger volumes of data. Although, there is value in this data, it is often difficult to unearth using conventional analysis tolls such as spreadsheets. To address this issue, new data analytics software platforms are being introduced specifically to deal with time-series data.

  • 5 Questions To Ask Before Selecting A Process Data Analytics Solution
    5 Questions To Ask Before Selecting A Process Data Analytics Solution

    The data generation and collection strategies at the center of manufacturing processes have evolved dramatically, especially in recent years. Process manufacturers now collect and store huge volumes of data throughout their operations, both on and off premise, across multiple geographic locations, in an increasing number of separate data silos. In this paper, we propose five questions we believe every process manufacturing buyer should ask when evaluating a data analytics solution.

  • Leveraging Predictive Analytics: A Case Study
    Leveraging Predictive Analytics: A Case Study

    Often the first notification of a spill comes from a member of the public, hours and sometimes days after the first spill. This can intensify public health and environmental impacts and the cost of clean-up efforts. Following a sewer spill at an environmentally significant site at Midway Point in August 2017, TasWater sought a way to reduce the likelihood and impact of spill events occurring in the future.

  • Devon Energy Uses Real-Time Data And Advanced Analytics To Make Better Decisions
    Devon Energy Uses Real-Time Data And Advanced Analytics To Make Better Decisions

    Like many other energy companies, Devon Energy, a leading independent oil and natural gas exploration and production company in North America, generates huge volumes of data. The company’s SCADA system monitors 6.5 million data points from multiple sites, with more than 10,000 updates per second. 

  • Optimize Process Unit Results With Advanced Analytics For Condition-Based Monitoring
    Optimize Process Unit Results With Advanced Analytics For Condition-Based Monitoring

    Businesses rely on process units meeting or exceeding their operational plans. To ensure that operational plans are achieved, it is important that equipment operates as designed (i.e., delivers the required performance) and continues to operate in an optimum manner (i.e., remains reliable, in a good condition). The most common causes of missing operational plan targets are equipment failure, which results in unplanned downtime, and low quality or yields from production processes.

  • Industrial IoT-Enabled Remote Monitoring Improves OEM Service Performance
    Industrial IoT-Enabled Remote Monitoring Improves OEM Service Performance

    The prime reason most industrial plants still have internal, on-site maintenance staffs is to reduce repair times and unplanned downtime, which negatively impact revenue, customer satisfaction, cost, and other key business metrics. In most plants today, contracting with the equipment manufacturer for maintenance usually results in unacceptably long periods of downtime for critical equipment while waiting for a technician to arrive – particularly with the typical two passes required for inspection and repair.

  • Leveraging IIoT Technologies To Reduce Unplanned Downtime
    Leveraging IIoT Technologies To Reduce Unplanned Downtime

    At ARC Advisory Group’s 20th Annual Industry Forum in Orlando, Florida, Shawn Anderson, Senior Research Specialist for Fisher Valves, a division of Emerson Process Management, gave a presentation on how the company is leveraging the Industrial Internet of Things (IIoT) to help end users reduce valve-related unplanned downtime.