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Data-driven actioncams – Garmin Virb XE review and roadtest

Data-driven actioncams – Garmin Virb XE review and roadtest

  |   Blog

Data to Value’s Director James Phare takes Garmin’s latest data-driven actioncam for a test ride on his commute to the office.




Thanks to a rise in the use of smartphones, falling sensor prices, and growing data literacy the fitness tracking and wearables market continues to rapidly grow with 70m units shipped in 2014 according to Gartner. New hardware such as smart glasses, watches and bracelets, new software apps and new sports use cases continue to emerge. As someone who enjoys extreme sports and data in equal quantities I find this a genuinely exciting time and look forward to seeing what the Internet of Things (IoT) can bring to this sector.


One area where technology has matured quite a bit recently is the actioncam market where GoPro’s traditional dominance is now being challenged by competitors. Many have chosen to go down the analytics and sensors route by loading their compact cameras with internal sensors and Bluetooth or wifi connectivity to external sensors. Garmin are one of the leaders in this space thanks to their successful Virb series of water, dust and snow proof actioncams. These have proven popular in a wide range of sports including snowsports, sailing and cycling to name a few. The latest model busting with features, the Virb XE, recently hit the shelves and we couldn’t wait to test it out.


Initial impressions of the device are that it will be very familiar to GoPro users in terms of dimensions and usability. It features a micro SD card, rechargeable batteries and will shoot high definition video at up to 1440p30 and 12 megapixel photos. It also has a number of other latest generation actioncam features such as wifi connectivity to line up shots.


Virb XE actioncam


What’s different about the Virb XE however is it’s sensor and data logging capabilities, branded G-Metrix by Garmin.  Included as standard in the Virb are GPS, G-force and orientation / gyro sensors.  This enables the capture of a number of datapoints that can help sports enthusiasts to understand what was going on in a particular photo or video. The Virb XE can also be connected to a range of compatible sensors such as heart-rate sensors, cadence sensors for cycling, remotes and watches. This data can then be seamlessly over layed onto video footage using the Virb Edit software (pictured below) and enriched with analytics, graphs, maps and other widgets. For someone that has worked with Data Visualisation and Business intelligence tools for years this ability to overlay useful data over my sports videos is fantastic. For those wishing to get the data into third party software there are also some helpful GPX and FIT file export options.


Virb Edit cycling video


To test out the cam I strapped it to the handlebars of my roadbike for my morning commute into the office and connected my garmin heart rate sensor.  I was impressed with the results, not only was the footage quality excellent the sensor data has also proven to be very complete and accurate. For my morning commute I’m not that bothered about finding insights to improve performance, however for improving general fitness awareness I can see how it could be useful. For me the Virb really comes into its own for sports where it has traditionally been difficult to capture metrics for meaningful performance improvements such as sailing. I can see the cam being a really useful training age for improving techniques and setup over the autumn and winter months.


Virb Edit Studio software

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time is running out

Applying data exploration & discovery techniques to BCBS 239

  |   Blog

Time is fast running out for G-SIBS (and indeed D-SIBS) to demonstrate compliance with the principles of BCBS 239.  Many surveys have been conducted by firms such as EY, McKinsey and Deloitte – none of which paint a particularly pretty picture in terms of readiness. Most suggest that the majority of banks will only be able to demonstrate compliance with between 25% and 60% of the listed principles by the January 2016 deadline. Why is this?


At a recent industry event discussing barriers to compliance one of the top issues that participants highlighted was difficulty understanding what data and metadata the G-SIBS and D-SIBS possess within their systems, shared drives and documentation. It seems that for datasets that are relatively well understood many have made great strides towards improving governance, architectural and sourcing issues. For those datasets that are less understood and defined using artefacts such as data models, dictionaries and other documentation however progress has been much more limited.


‘Risk data’ by its very nature often opaque – typically featuring many aggregations, data flows, summaries, data inputs and different flavours of complex underlying calculations. So far this opacity has been addressed by many G-SIBS using largely traditional methods such as workshops and stakeholder interviews.  These often generate reams of documentation requiring numerous peer reviews. Unfortunately however the devil really is in the data and too often this approach has only analysed the underlying schemas, content and calculations buried within applications too late in the process. Clearly if banks are to speed up progress in the time remaining more automated techniques need to be leveraged.



Applying the latest Data Exploration & Discovery techniques


network links

Fortunately many automated techniques already exist to rapidly discover and understand the characteristics, lineage, relationships and linkages buried in disparate and complex datasets that can be applied to BCBS 239 requirements. In fact Data Exploration and Discovery techniques are often now considered an essential starting point for most Business Intelligence and Data Science projects, regulatory data is still a relatively untapped opportunity however. Typically the discovery process works by applying different algorithms to a dataset in order to harvest metadata characteristics such as formats, standards, uniqueness and completeness.  In many tools more advanced key and relationship discovery capabilities also exist enabling users to discover mappings, transformations and the true lineage of individual data points.  Essential requirements for understanding where your risk data outputs originated. This valuable metadata can then be integrated and enriched with traditional sources such as data models, dictionaries, workshop notes and stakeholder interviews to create a detailed understanding of a bank’s risk architecture, data, processes and governance. All essential for BCBS239 compliance.


So for those lagging behind perhaps it’s time to find out how these proven techniques can help your bank hit the 2016 deadlines?  Contact us for more information.

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Regulatory roundtable event

Regulatory data management roundtable

  |   Events

We were thrilled to host a breakfast event with software partners Experian Data Quality where we shared ideas and insights with regulatory data practitioners. The roundtable expert group discussed the main regulatory challenges such as culture, technology and semantics in financial services organisations.


We established that senior decision makers in financial firms need to start viewing regulatory drivers as an opportunity for a fundamental paradigm shift in how data is managed rather than figuring out the cheapest, quick fix. Moreover, the IT infrastructure, of many financial firms, is ridged and dated making it more difficult to implement necessary changes. Many firms also appear to be struggling to understand what data they have and which regulations this data is subject to.


Data Prototyping and Data Discovery were discussed as two potential solutions to a number of regulatory data management challenges. When paired with Lean Information Management we have found these techniques to rapidly accelerate your regulatory data initiatives.


Subscribe to our mailing list to keep abreast of upcoming events.

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