Is the Internet of Things creating data hoarders?

A recent Gartner report predicts that the number of connected ‘things’ will reach 25 billion units by the year 2020[1]. The Internet of Things (IoT) holds great potential for business leaders, offering the possibility of viewing, analyzing and leveraging statistical information about unstructured, big data in an instant. According to Gartner[2], IoT will be the next critical focus for data/analytics services. In fact, it has already started to change the face of big data storageand analytics in 2014, and it is becoming a core investment strategy for organizations across all industries. In Asia Pacific, the IoT adoption is expected to grow to US$57.96 billion by 2020[3].

The IoT blends not only greater data volume, but also complexity and velocity to an already challenging data lifecycle. These new connected and embedded systems demand multiple service levels; and organizations will seek to process and analyze data in both real time and over the long term. The mountain of information these devices create is forcing companies to rethink how to securely capture, store and retrieve data to derive more value from it.

IT managers need therefore to rapidly make decisions about this ever increasing flow of data and to develop a holistic modern data management strategy. Hence, they need to consider the sources of data, the frequency of reporting, and how that data will be used, so that they can design policies to identify what to keep, where to keep it and for how long. While storage and cloud costs are decreasing, it is not happening fast enough to keep up with exponential data growth. The old fashioned strategy of “storing everything forever” is too rigid, slow and expensive. Besides, the new reality for IT managers is that every piece of data is not equal in value. To address this problem, companies are embracing modern data management strategies which include writing and executing automated policies that map back to demand from the business. These policies help make better business decisions, lower costs, evolve products and services and improve the user experience.

1)    Automate the organization and retention of data based on the content

Content-aware retention leverages intelligence about data – such as type, confidentiality, when it was created and the last time it was accessed – to index and classify it. Policies can provide specific rules to automatically move relevant data to more cost-effective storage. File Analysis (FA) tools for instance, can help organizations make more informed decisions around prioritizing their unstructured data management needs for classification and information governance, providing insights on retention policies for data movement. Many FA tools also offer reporting capabilities that help define these retention policies. According to Gartner, “the value of reports in FA tools is that they can be used to determine policy and strategy in areas such as access, retention and location.[4]

Storing IoT data indiscriminately in the long-run is wasteful and costly, and prevents organizations from easily finding what they need. By understanding how data flows through the organization, managers can keep what is valuable and get rid of what is not, reducing their costs and risks. Intelligent archiving technologies, such as content-based retention, can save organizations up to 70 percent in storage capacity and costs[5]. This is especially valuable for highly regulated industries, such as healthcare and financial services, that must store data for seven or more years for compliance and quickly retrieve it when required.

2)    Securely consolidate IoT data regardless of where it  stored or where it comes from

Powerful smart devices and remote work environments allow anyone to always stay connected. Efficient IoT management starts with consolidating data stored by individual users in their devices, backing it up and putting in controls for secure access. Redundant copies can be deleted through deduplication. In January 2015, CommVault launched Simpana for Endpoint Data Protection, a new solution that effectively helps organizations protect and enable mobile workforces by efficiently backing up laptops, desktops and mobile devices, providing secure access and self-service capabilities. This new functionality empowers organizations to reduce cost and risk by protecting against data loss, while enabling enterprise-wide compliance and eDiscovery. As a result, productivity is increased across the enterprise through self-service capabilities for data restore, secure file sharing, and advanced data analytics and reporting.

3)    Offer new ways to access information, be productive and add value

Once an organization’s data has been consolidated from servers, laptops, mobile devices and remote offices, the IoT can offer new ways to be more productive. Content indexing enables IT, legal and business units to search across the enterprise using granular keywords. New access methods, through file sync and mobile apps, allow employees to create personal data   clouds and quickly find, view and use documents across all their devices.

The focus on IoT also confirms the need for more advanced analytics than the ones currently available. In fact, according to IDC, the big data and analytics market will reach $125 billion worldwide in 2015[6]. In addition, cloud computing opportunities will multiply as the IoT becomes more widespread. Applications, which drive the functionality of sensors and other mobile devices, will increasingly be hosted and developed in the cloud, while the analytics of vast amounts of data will also be performed more and more in the cloud. Over the next five years, spending on cloud-based big data and analytics (BDA) solutions will grow three times faster than spending for on-premise solutions, resulting in hybrid on/off-premise deployments becoming a requirement[7].

Capitalizing on the vast potential of IoT will require an intelligent approach, particularly with regards to the enterprise’s data management strategy. IT needs to ensure that its organization best leverages the technology available to “filter the huge amounts of data coming from the IoT, social media and wearable devices, and then deliver exactly the right information to the right person, at the right time[8]. By implementing modern data management techniques to IoT data, organizations can reduce storage space, increase productivity and gain real-time visibility into their operations.


Mark Bentkower is the Director of Enterprise Solutions Asia Pacific, CommVault Systems


[1] Gartner, November 2014: Gartner Says 4.9 Billion Connected “Things” Will Be in Use in 2015

2 Gartner, October 2014: Gartner Identifies the Top 10 Strategic Technology Trends for 2015

3 Frost and Sullivan, July 2014: “Analysis of the Internet of Things Market in the Asia Pacific

4 Gartner, March 2014: Does File Analysis Have a Role in Your Data Management Strategy”, Garth Landers, Alan Dayley

5 CommVault, October 2013: “CommVault Intelligent Archive Solution Makes Content Retention, Compliance And Cloud Storage More Affordable

6 IDC, December 2014: “IDC Predicts the 3rd Platform Will Bring Innovation, Growth, and Disruption Across All Industries in 2015”

7 IDC, December 2014: “IDC Reveals Worldwide Big Data and Analytics Predictions for 2015”

8 Gartner, October 2014: Gartner Identifies the Top 10 Strategic Technology Trends for 2015