Insights Hub (formerly MindSphere) is the industrial IoT application suite that empowers you to generate actionable insights from assets and operational data, driving manufacturing excellence by improving operational efficiency and quality.
Insights Hub is part of Industrial Operations X. With Industrial Operations X, we are expanding the Siemens Xcelerator vision to include our portfolio of industrial operations software and industrial IoT. The Industrial Operations X portfolio helps our customers and industries to accelerate their production processes, making them adaptive, people-centric and holistically integrated. With this new approach to operations and smart manufacturing, we are confident you will be better equipped to face the ever-changing industry demands, business models and workforces.
There are three ways to log in to Insights Hub for the first time:
Your username and password depend on the identity provider (IDP) you use. There are several options for Identity Provider Access. Our Standard IDP provider is Webkey. Other federated IDP-authorized providers include Mendix ID and Siemens ID. If your Environment Admin uses the Custom IDP feature, log in with your familiar access window provided by your IDP Provider.
Normally, you create a Webkey during the Start for Free registration process, and this can carry over to a paid account.
In commercial Insights Hub deployments, the welcome email guides you through the Webkey creation process. If you already own a Webkey account because you are using it for other Siemens Software, use your existing Webkey to access Insights Hub.
Insights Hub public versions are available on Azure and AWS. We also offer a private version which is cloud dedicated (VPC: virtual private cloud) and privately administered (LPC: local private cloud).
Summary of the differences between LPC and VPC
Insights Hub for Private Cloud (LPC): Companies must have their own data center and their own infrastructure services. They will need to install RedHat OpenShift or Rancher on top of their infrastructure.
Insights Hub Cloud dedicated (VPC): Companies put Insights Hub on an already existing hyperscaler account like AWS or Azure.
Yes. You can also deploy Insights Hub in your Azure and AWS account or your own datacenter with our Insights Hub for Private Cloud (LPC: local private cloud).
Currently the public version of Insights Hub runs on AWS and Azure.
Only your organization knows this. Users and their roles are only visible to the admin in your organization.
Yes. Choose the Insights Hub for Private Cloud (LPC: local private cloud) or the Insights Hub Cloud Dedicated (VPC: virtual private cloud) to ensure data policies meet the requirements of the respective country. Additionally, make sure that the infrastructure provider offers the required services. Please talk to our sales and operations team to verify this.
If neither option works for you, please contact our sales team and they will work with you to find a solution.
All data is stored on AWS servers in Germany.
If you host your application using the Insights Hub hosting environment, based on Cloud Foundry, choose from the following languages: Java, Node.js, .Net Core, Python, PHP, Go, Ruby, staticfile, binary and Mendix. If you host the app in another infrastructure, you are free to choose the programming language.
Yes, you can use your own IDE.
Host your applications either on the Insights Hub Cloud Foundry application runtime or on your own infrastructure.
Manage your Insights Hub applications with Insights Hub Developer Cockpit, Operator Cockpit and Cloud Foundry CLI (command line interface).
No, Insights Hub focuses on multi-tenant capable applications, which means that the application runs only in your production environment and is only provisioned to your customers through the Insights Hub developer/operator functionality.
Yes, Insights Hub and Industrial IoT Web Components offer exactly that.
Yes, you can use non-Siemens hardware and software that support standard communication protocols and develop a connectivity solution to send data to Insights Hub (Using MQTT, MindConnect API, MindConnect LIB and so on).
Besides these possibilities, many Siemens hardware devices and software can already connect easily to Insights Hub, using MindConnect Elements.
Yes. Develop your hardware with our MindConnect Lib SDK with C Programming (see here) or the MindConnect API with any programming language you choose. Use an SDK of your choice and connect to Insights Hub with MindConnect MQTT, or use the MindConnect Software Agent (MCSA).
Yes. Use your existing hardware and software using the Insights Hub Connectivity LIB SDK (see here) to create a gateway.
You can also use the connectivity solution Insights Hub Software Agent in your hardware to connect and send data to Insights Hub (see here). It is available for Windows and also as a dockerized version.
Yes. Use S7, OPC UA and MQTT protocols for bidirectional communication between Insights Hub and your on-site devices/machines using our MindConnect elements, such as MindConnect Nano and MindConnect IoT 2040. You can also use MindConnect MQTT for bidirectional communication using your hardware of choice.
All communication to and from Insights Hub is secured with TLS v1.2.
MindConnect Software Agent, MindConnect Nano and MindConnect IoT 2040 easily connect a Siemens programmable logic controller (PLC) to Insights Hub. There are some PLCs, such as S7-1500 and S7-1200 that can be connected directly to Insights Hub.
This highly depends on the PLCs and is evaluated on a case-by-case basis.
Different kinds of data can be stored: timeseries data in our timeseries database, unstructured data in an integrated data lake, files in our file storage. Other data, such as log files and events can also be stored in Insights Hub.
There are different ingest possibilities for hardware and software solutions; for example, an IoT database or Integrated Data Lake.
Yes. Using MindConnect Integration, bring data from both cloud and on-premise based systems into Insights Hub for further contextualization, visualization and advanced analytics.
Yes. With Data Contextualization ( formerly known as Semantic Data Interconnect (SDI)), it is possible to correlate data in an integrated data lake and timeseries data from machines providing context to your data.
Store any kind of data including structured, semi-structured and unstructured data in the integrated data lake.
Yes. Share your S3 resources with our Integrated Data Lake.
Yes. Bring data from AWS/Azure storage services into Insights Hub for contextualization, visualization and advanced analytics.
Yes. MindConnect Integration has a feature called recipes (configured integration flows) that can be reused for different instances of source and destination systems configured in a recipe.
Yes. MindConnect Integration reads files from your FTP server and then transfers them into Insights Hub for contextualization, visualization and advanced analytics.
Yes. MindConnect Integration allows the scheduling of integration workflows.
Yes. MindConnect Integration allows detailed monitoring of integration workflows giving details on their status.
Data Contextualization (formeraly Semantic Data Interconnect (SDI)) is a framework that enables users to provide a context to IoT, OT and IT data by establishing a semantic relationship between different sources.
A semantic layer is an abstraction of the technical implementation layer. It provides citizen data practitioners with an easy way to understand the data without worrying about the technical complexity and implementation of the underlying data source. The semantic layer presents the underlying data model using familiar domain definitions (dimensions, measures, hierarchies) and easy-to-understand terms.
Yes. Semantic Data Interconnect (SDI) allows you to query contextualized data and use the query response for further analysis.
Yes. Query responses from Data Contextualization (formeraly Semantic Data Interconnect (SDI)) are available over REST interface and also available as files in the Integrated Data Lake.
Yes. Multiple capabilities in Insights Hub, such as system integration, transformation, orchestration and contextualization, provide users with intuitive ways to design, execute and monitor data workflows. For example, Visual Flow Creator offers a graphical workflow editor that uses drag-and-drop to connect a collection of preconfigured and local nodes to perform a range of functions.
Yes. With Insights Hub Monitor and Visual Flow Creator, it is possible to define and save KPIs on timeseries data in Insights Hub.
Currently, there is no possibility of connecting on-premise data lakes with the Insights Hub Integrated Data Lake. However, it is possible to transfer data between Insights Hub and on-premise data lakes.
The Integrated Data Lake supports uploading up to 5GB on AWS tenants and up to 256MB for Azure tenants.
Yes. Import your timeseries data into the Integrated Data Lake using the timeseries import feature.