6 strategic imperatives for your next data strategy

In the architecture, engineering and construction (AEC) industry, for example, these scenarios might include geospatial data like aerial imagery offered directly via an ecommerce-enabled website, drone-based photogrammetry of roadways and bridges with AI-enabled defect analysis, like Manam, traffic congestion data visualized via a GIS platform, like Urban SDK, or EV charging data provided by a live digital twin.

The focus here should be on considering all ways your customers currently consume data as well as new ways they might want to achieve better results. For example, although the recent I-95 bridge collapse in Philadelphia was an unforeseeable event, legacy bridge management systems can likely benefit from being augmented with AI-defect analysis, or even upgraded or replaced with live digital twin platforms for a past, present, and future model.    

Utilize automation, data analytics, and AI/ML

Many of today’s modern data platforms go beyond the traditional relational database, data warehouse, and data mart to provide built-in support for automation and AI/ML. There are also no-code data engineering and AI/ML platforms so regular business users, as well as data engineers, scientists and DevOps staff, can rapidly develop, deploy, and derive business value.

By placing these platforms at the core of your data architecture, your organization can get a springboard into automation, analytics and AI/ML projects while rounding it out with additional partners and investments to complete your ecosystem.

Integrate various data sources

Integrating data sources is another strategy to provide added insights for clients, and can be achieved via 2D environments such as analytics dashboards and GIS, or 3D environments like digital twins with XR capabilities for visualization, such as Magic Leap and Apple Vision Pro.

Look for opportunities to combine your own data with third-party data, including open data, where applicable, for added value and for tools that support data ingestion, transformation, and integration to feed into a variety of analysis tools including GIS and digital twins.

About Author

AndyC

Andy Curtis is an award-winning security consultant, researcher and public speaker. He has been working in the computer security industry since the early 1990s, having been employed by state and federal government, leading healthcare and banking providers across three continents. He has given talks about computer security for some of the world’s largest companies, worked with law enforcement agencies on investigations into hacking groups, and is a regular voice on TV and radio explaining IT security threats.

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