Jesper Leth

In a business context, democratizing data means to make data (and derived analytics and insights) available to all layers of an organization and its business ecosystem, across departmental boundaries.

This is the third post in our 'Internet of Things' blog series. If you missed the first posts, you can find part one here and part two here.

Any organization wanting to be the next market game changer has to put innovation on the top of their agenda. Top leaders know that innovation is a way of thinking, not just a project, and therefore CIOs are tasked by the CEO to have a flexible and trusted infrastructure that supports innovation. According to Gartner’s Pace Layered Application Strategy: “(...)competing goals often lead to strategic misalignment”. A key concept to succeed is to have “Business and application organizations collaborating on innovations, ideation and experimentation”.

This is part two of our series on The Internet of Things. Click here to read part one.

We’ve said it before in earlier blogs but “…2016 is the year of Internet of Things (IoT)”. As Gartner also notes¹ “…IoT will be the most game-changing IT initiative since cloud computing in terms of new business opportunities, and its impact on IT.” 

Yet as the number of IoT-enabled devices increases, existing legacy systems might struggle to manage the volume and variety of new data being generated.

This is part one of our series on the Internet Of Things (IoT). Please find Part 2: The Data Goldmine here.

Traditional centralised databases will always have a role to play in analytics. However, the rise of the Internet of Things (IoT) suggests that we will soon live in a world that’s anything but centralised. Estimated to be worth somewhere between $3.9 trillion and $11.1 trillion by 2025 IoT technologies are giving physical products the sensor and online capability to report back on their own status as well as to communicate with other devices, all via the existing internet. As these IoT initiatives flourish, data management will move from the central data repository towards the edge of the network.