In this special technology white paper, Why Machine Intelligence is the Key to Solving the Data Integration Problem for the IIoT, you’ll uncover the reasons why machine intelligence is the key to solving the data integration challenge for the IIoT. The heaviest lift for an industrial enterprise is data integration, the Achilles’ heel of the Industrial Internet of Things (IIoT). This is blocking progress on the transformations and ROI that companies originally envisioned.
Developments have been stymied by challenges in handling the complexity, diversity, volume, and velocity of data as well as in the disparity of data characteristics such as quality, completeness and timeliness. Companies are now recognizing the heavy-lift involved in supporting Big Data strategies that can handle the data that is generated by information systems, operational systems and the extensive networks of old and new sensors. To compound these issues, business leaders are expecting data to be captured, analyzed and used in a near real-time to optimize business processes, drive efficiency and improve profitability. However, integrating this vast amount of dissimilar data into a unified data strategy can be overwhelming for even the largest organizations.
The paper explores ways to solve the data integration challenge by requiring a new way of thinking in terms of traditional data architectures that need to be re-imagined to support the rapid proliferation of data from an exponentially expanding set of data types. The paper also details a new solution from Bit Stew Systems – The MIx Core integration solution which is segmented into the following technology layers:
- System Connectors
- Byte Sequencing & Marking
- Composite Information Patterns
- Semantic Model Mapping
- Intelligence, Analytics and Knowledge
Consider how a Big Data solution might analyze, query and report data received from IIoT sensors to streamline operations when that data will have significant gaps and reading errors, cleansing and normalization issues, synchronization and sequencing problems and inherent industrial noise affecting resolution and quality. Manual integration is far too tedious and costly to deal with IIoT Big Data on a continuous basis and intelligent automation is the key for successful automated integration. The white paper includes a number of compelling case studies as well as the following high level topics that address IIoT data integration challenges:
- Challenges with IIoT Data Integration
- An Intelligent Solution with Mix
- Intelligent Semantic Modeling
- Small Teams Can Solve Big Industrial Data Integration Problems
- Use Cases for Data Integration in Industrial Environments
The Why Machine Intelligence is the Key to Solving the Data Integration Problem for the IIoT white paper is available for download in PDF from the insideBIGDATA White Paper Library, courtesy of Bit Stew Systems.
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