Why Spatiotemporal Analytics Needs A New Type of Technology

We are surrounded by a vast and ever-increasing network of sensors and trackers, generating a constant stream of spatiotemporal data. From the movement of vehicles and GPS trackers, to smartphones and other mobile devices, the data is constantly changing as these objects traverse locations over time. However, when it comes to managing and analyzing these massive volumes of information, traditional data tools tend to fall short. A new type of technology is needed.

As data scales and accumulates from millions to billions of records, conventional data management tools degrade in performance. Tools that were not designed for this scale can become very expensive. In these scenarios, data teams begin to limit the scope of their reporting or in the the worst cases, wait hours or days for queries to run, which makes it difficult to extract trusted and timely insights for decision making.

Using advanced data science methodologies such as polygon searches or spatial joins with spatiotemporal data can also prove challenging. Technologies like H3 allow circumvention of some issues but require domain expertise and preprocessing with results remaining approximations.

Uncovering Actionable Insights

Amidst these challenges lies an opportunity. Spatiotemporal data holds valuable and undiscovered insights that have the power to transform operations.

To fully realize the benefits of this data trove and for businesses to become more data-driven, analysts need to quickly extract business insights and transform them into smart decisions. The ability to reduce latency between data to value is critical to maintain competitiveness in an ever-changing landscape.

Breaking Free from the 'Workaround or Trade-off' Mindset

It's only natural for data professionals to turn to their trusty tool kit of proven tools when tackling new projects. While these tools may be familiar and get projects off to a fast start, there are trade-offs which can cause challenges down the line. Tools that specialise in one area may lack capabilities in another and teams may find themselves bridging the gaps with costly, manual labour which takes a toll on productivity.

Delaying the exploration of new, more effective solutions can lead to protracted and painful projects, and feed an ongoing cycle of of temporary fixes. Data professionals may also miss out on opportunities for growth and innovation that limit their true potential.

Investing time into research and implementation of new, more effective tools improves collaboration, streamlines workflows and drives better results.

Purpose-Designed Technology

By leveraging purpose-designed technology, businesses can immediately overcome the limitations of existing tools and breeze through the typical challenges presented by processing and analysing spatiotemporal data.

The benefits go far beyond project efficiency. These innovative tools have the ability to unleash the true potential of both historic and streaming data to drive more accurate decision making and improve machine learning predictive models.

In Conclusion

As sensors and trackers become more prevalent in our evolving world, we can positively embrace the barrage of data with purpose designed technology.  Mastering the transformation of data into actionable strategies is essential but also rewarding as it creates a positive, lasting impression for the industry, employees, partners and customers. 

Contact us to find out how the Data Flow Index can deliver the missing technology pieces needed to unlock real time understanding and possibilities for your data.

Lisa Hutt

Chief Marketing Officer

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