Data integration and management¶
Create context from cloud and on-premise sources¶
Solid business intelligence is vital. Add to a unified data-fueled view of your organization by placing your machine data into context. Here are the tools to ingest, manage, und seamlessly integrate data from any source - in the cloud or on premises; systems or applications; finance, planning, IT, or shop floor.
How you ingest data into your data lake¶
APIs extract data from your source and load it into your data lake. You can use any HTTP API with OpenAPI definitions or message-driven API with AsyncAPI specs for your data integration solution.
As a cross-platform C software development kit and API library, MindConnect LIB brings together functionalities that help your apps and APIs connect, exchange data, and feed your data lake.
MindConnect Integration comprises both a library of ready-to-use connectors and a low-code graphical DIY tool for building connectors. Ready-to-go connectors cover systems, from PLCs and SCADA to ERP as well as service platforms like Salesforce.
A single file or bulk data, with a clean, quick, and clutterfree user interface you can drop data into your lake whenever and wherever it's ready to go.
Pulling time series data from connected assets¶
Data from assets can also be ingested using our wide range of MindConnect connectivity offerings. Based on the use case these asset centric data could also be used together with the Data from other sources like described above.
How you store and manage your data¶
Your data lake¶
Capable of handling large data pools, the data lake is a repository where you store your data, structured and unstructured, in its native format. Schemata and data requirements remain undefined until you query the data.
Your data lake natively integrates with Insights Hub analytics and visualization tools. A built-for-convenience user interface, the integrated data lake application, helps you administer it while APIs provide automated processes with direct access to the data.
Your Time Series data¶
With a comprehensive set of funtionalities, the IoT Time Series Service helps you create, read, update, and delete time series data gathered by your assets. You can import and store time series data in your data lake for advanced analyses and queries.
How to make the most of your ingested data¶
1. Processing and contextualization¶
is a NodeRed-based visual designer for data orchestration flows that comes with rich integration capabilities.
helps you place integrated OT, IT and ET data into context by establishing semantic relationships between disparate sources.
2. Analytics¶
is a powerful industry solution to predict and optimize quality results based on the production process data.
3. Visualization¶
is a browser-based solution that utilizes Tableau® to create customized, advanced data visualizations, dashboards and reports from data sets.
Use this out-of-the-box application to jump right into monitoring, visualizing and managing production lines and machines. With its flexibility and rich capabilities, Insights Hub Monitor is easy to expand and scale.
Get the support you need¶
FAQs
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.
You can store any kind of data including structured, semi-structured and unstructured data in the Integrated Data Lake.
Ask questions and share ideas with Siemens customers who use Industrial IoT.
Browse the knowledge base to find answers or get in touch with product support. Sign in with your Insights Hub / Siemens ID credentials.
Accelerate your skills¶
Shape your own learning journey with Siemens comprehensive resources on how to integrate data and use it.