All Research Sponsored By:HighByte
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Gousto Case Study
This case study explores how Gousto, an online meal-kit manufacturer, used HighByte Intelligence Hub to streamline data infrastructure and improve operational efficiency. By democratizing data and building a scalable unified namespace, Gousto achieved mechanical availability and sustainability. Access the case study to learn more.
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Fireside Chat with ABI Research
As DataOps continues to evolve, so does the technology you need to keep up. This was the case for Gousto, an online, subscription meal service and delivery company, who began struggling with a lack of operational efficiency and strived to achieve success throughout their Industry 4.0 journey. Tune into the webinar to learn more.
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Catalent Case Study
Catalent, a leading CDMO, used HighByte Intelligence Hub to integrate bioreactor and lab data across 50+ sites, enabling data contextualization and publishing for analytics, remote monitoring, and customer insights. This saved hundreds of hours and created a scalable data architecture. Discover more in the full case study.
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Siemens Gamesa Case Study
Siemens Gamesa, a leader in renewable energy, utilized HighByte Intelligence Hub to merge systems and establish a unified data model. This led to better alignment, real-time monitoring, and a base for enterprise data architecture. Discover how HighByte aided Siemens Gamesa in reaching Industry 4.0 objectives in the full case study.
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HighByte Intelligence Hub version 3.2: A complete UNS and data engineering toolset
In this white paper, you’ll discover a software solution designed to provide organizations will all the necessary components to build and manage a Unified Namespace (UNS). Read on to learn how you can maximize the value and accessibility of your industrial data.
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The power of payloads in your unified namespace
Although most industrial companies have been able to load their data in their Unified Namespace (UNS), many are finding that they are unable to use it effectively. In this white paper, you’ll discover how you can unlock the necessary capabilities to contextualize your data and maximize the value of your UNS. Read on to learn more.
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Abstraction puts the ‘unified’ in Unified Namespace
The Unified Namespace (UNS) architecture has become a favorite in the manufacturing industry for its ability to provide data access to users across an organization – but it’s not enough on its own. Read on to understand why an abstraction layer is key for unlocking the potential of your UNS and empowering your organization with data.
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Solution Brief
Manufacturers and industrial organizations can produce more than a terabyte of data every day, but without the right tools and processes to refine that data, they are sitting on an abundant asset that cannot be leveraged in a meaningful way. Read on to understand how you can unlock the potential of industrial data for your organization.
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Think Big, Start Small, Scale Fast: The Data Engineering Workbook
In this interactive workbook, you’ll discover 10 steps accompanied by some brief questions that are designed to help industrial leaders learn how they can leverage data engineering strategies to get the most out of their data. Read on to learn how you can unlock hidden business value.
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DataOps: The Missing Link in Your Industrial Data Architecture
How can your business simplify data contextualization to maximize the value of your technology investments? By leveraging DataOps to define standard models and establish and manage integrations, operational teams can provide data to the systems and business users who are requesting it in a more efficient and managed way. Read on to learn more.
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ABI Insight: Modern Industrial Data Architecture Strategies and Best Practices For Life Sciences 4.0
Industrial DataOps is the dominant framework for mastering 4.0 data transformation projects, and it is key for leveraging solutions that can deliver data to users for a real-time view of the enterprise. Read on to learn about a solution that can help manage data in a common format that is ready to consume, contextualize, and scale for the customer.
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Bringing sustainability to your industrial data architecture
While industrial processes are a big contributor to a company’s CO2 emissions, data processing and storage is also an important part of the sustainability equation. Read on to learn how manufacturers can support their sustainability goals while potentially increasing production and why DataOps is crucial for success.
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HighByte Blog: Contextualized Data Where it Matters
There are several obstacles that IT teams must overcome in order to make IoT data usable for the organization. Access this blog post to learn why industrial DataOps is key for organizations that are looking to maximize the ROI of their digital investments and deliver contextualized data where it matters.
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How to apply lean manufacturing to data management
The volume, velocity and variety of raw industrial data are ever increasing, making it difficult to work with. Fortunately, manufacturers already have the framework they need to streamline data production and preparation. Read on to learn how you can enable your organization with lean data.
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The State of DataOps
For many reasons, the complexity of today’s data ecosystem hinders the democratization of data and analytics. This e-book by ESG provides insights on how to improve the quality, delivery and management of data/analytics at scale using DataOps. Explore this e-book to learn key findings and use the report to compare your performance to your peers.
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How IT Can Effectively Build and Scale Operational Data Pipelines
Integrating and contextualizing operational data has proven to be difficult when it comes to technical execution. This brief by IDC provides insights on the challenges and opportunities facing the CIO as they strive to bridge operational technology (OT) and the line of business. Read on to learn how you can empower your IT and LoB.
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Making The Case: Why You Should Be Using A Dedicated Layer For Data Modeling
While it’s great to recognize the role that data modeling plays in Industry 4.0 success, it’s another thing to understand how you can actually achieve a data infrastructure that can really scale. This blog post explores just that. Read on to learn how a dedicated abstraction layer for data modeling can help you meet your Industry 4.0 goals.
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Data Modeling Guidebook
Digital transformation is providing an unprecedented amount of predictive insights, but making the best use of this data can be daunting. Check out HighByte’s e-book to gain a better understanding of how data modeling works, what it looks like, how it works with existing standards, and to gather tips on how to establish a data modeling strategy.
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DataOps for manufacturing: A 4-stage maturity model
As companies look to scale up advanced data projects as part of their Industry 4.0 initiatives, they’re quickly running into difficulties due to legacy data infrastructures. Explore this blog post to discover a 4-stage maturity model for DataOps in manufacturing and learn how this discipline can help overcome data snafus for manufacturers.
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IIoT Health Check: 6 Signs You Need Industrial DataOps
In many industrial environments, it’s unfortunately common for hundreds of PLCs and machine controllers on disparate machines to generate operational data that is unintelligible to the data scientists who must make sense of it. By implementing Industrial DataOps, you can standardize disparate datasets and improve analytics. Read on to learn more.
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How to Select Your Integration Architecture
Integration architectures fall in two camps: direct application programming interface (API) connections (application-to-application) or integration hubs (DataOps solutions). Read this blog to explore both options and learn how to select the perfect integration architecture for your needs.
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How Industrial DataOps is shaping Industry 4.0
The change sweeping the manufacturing industry right now is so thorough that some are calling it “The 4th Industrial Revolution.” And with this change comes problems—namely the issue of unusable data. But with the right DataOps approach, you can start to make sense of these remarkably complex sets of data. Read on to learn more.
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An Intro to Industrial Data Modeling
Data modeling can help companies standardize information, enable interoperability, show intent, and more. But setting out to achieve data standardization at scale can be overwhelming. Explore this blog post to learn more about what data modeling looks like and discover how HighByte can help your teams develop successful models.
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Seven Steps to Making Your Industrial Data Fit for Purpose
A modern industrial facility can easily produce a terabyte of data each day; unfortunately, not all of this data is usable or useful in its original form. This 7-step guide will help you process your industrial data and transform it into a useable, valuable source of insight. Read on to learn more about Industrial IoT data and its proper use.
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Four practical use cases for Industrial DataOps
Most manufacturing companies know how leveraging industrial data can improve production, but they remain challenged as to how to scale-up to the enterprise level. Read how these four use cases reveal the ways Industrial DataOps can integrate your role-based operational systems with your business IT systems as well as those of outside vendors.