The data integration challenge is leaving many industrial enterprises feeling like they are drowning in data. This article by Alex Clark, Chief Software Architect at Bit Stew, shares insights on the heavy-lift involved in supporting your data management strategy.
This Blog originally appeared on April 13, 2016 on Bit Stew Systems' “Bit View” Blog Site.
The Internet of Things (IoT) is the network connection of physical objects, or “things” across existing communication infrastructures. The IIoT is the same thing but on an industrial level where the value, volume, variety, velocity and veracity of data is more critical. The challenges are compounded by the complexity and scale of data being ingested in industrial environments. Although the challenges are greater, the opportunities the IIoT presents are more prevalent. The technologies behind the IIoT have brought significant advancements to industries such as manufacturing, oil & gas, aviation, energy, and others.
Are you Prepared for the Data Tsunami?
Gartner forecasts that 6.4 billion connected things will be in use worldwide in 2016, and the number of connected devices will reach 20.8 billion by 2020. Newly connected devices are coming online within networks at an alarming rate, and most of the effort has been focused exclusively on data generation. Developments have been hindered by challenges in handling the data as well as in the disparity of data characteristics such as quality, completeness and timeliness. Another issue is that industrial organizations often have multiple, siloed legacy systems producing data in different formats and protocols, which do not communicate with each other. Integrating this vast amount of dissimilar data into a unified data strategy is proving to be overwhelming.
Data Integration – The Achilles’ Heel of the IIoT
Data integration has become the Achilles’ Heel of the IIoT and is blocking progress on the transformations and ROI that companies had hoped for. Data integration can account for more than 80% of project costs and are the primary factor in lengthy delays, and cancelled or failed projects. In fact, Garter reports that 50% of projects will exceed budget, or fail to deliver expected benefits due to inadequate data integration tools and architecture. Industrial customers are concerned about these major challenges, complexities, costs and delays in integrating the diverse technologies, devices and proprietary solutions.
Recognizing the Common Mistakes
Implementing an IIoT architecture can be a daunting task. Industrial enterprises often prematurely make investments in open source architecture, business intelligence tools, analytics products, or ETL processes for their data. These traditional tools are not necessarily designed for the IIoT. Solving the data integration challenge requires a new way of thinking and approach.
The only way for an industrial organization to come around the curve and efficiently capitalize on the exponentially growing data in industrial environments is through a software solution that is purpose-built for the Industrial Internet. Bit Stew’s MIx Core™ platform applies a schema first approach that allows industrial enterprises to integrate data rapidly by removing the heavy lift of data wrangling. Another key to Bit Stew’s data integration capability is that Mlx Core automates the data modeling and mapping of data from billions of endpoints enabling you to intelligently manage your data in wristwatch time.
Other IIoT Resources from Alex Clark and Bit Stew Systems:
- VIDEO: Solving the Data Integration Challenge with a Purpose-Built IIoT Platform
- WHITE PAPER: Data is Power for Oil and Gas, But is Data Enough for the Digital Oil Field?
- WHITE PAPER: Purpose-Built Data Architecture for the Industrial Internet