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What Makes Analytics The Key Element Of Enterprise IoT Projects

As millions of connected devices flood the market, the IoT ecosystem is undergoing a massive transformation. Gartnerpredicts the total economic value add for IoT will be $1.9 trillion dollars in 2020 making it the largest technology transformation ever. Analytics is increasingly fueling the adoption of connected devices and plays a significant role in the growth and success of IoT applications and investments.

The Importance of Analytics

While organizations realize the value of storing and managing IoT data, there are also many organizations which struggling to find opportunities to deliver value. Although IoT is making great strides in every industry, its effects aren’t as wide-reaching. Strategy Analytics reports that just 25 percentof enterprises are operating full-scale IoT deployments. In order to analyze the humongous volumes of IoT data, it is vital for businesses to leverage the power of analytics to encourage innovation in the products and services they offer. It’s only when collected data is turned into information that organizations can augment business decisions with actionable insights. To unlock the potential of IoT at the enterprise level, organizations will need to synchronize the entire IoT ecosystem with analytics.

  • The huge clusters of datasets that IoT applications make use of are not easy to manage – it is only through analytics that business organizations can manage these large volumes of data and analyze the same in real-time for extracting relevant patterns.
  • Since IoT data sets are most often unstructured, there is a significant difference in data formats and types. Using automated tools and software, analytics allows businesses to analyze varying sets of data and unearth crucial insights.
  • Analytics does not just help analyze data; by understanding buying behavior and trends, it also allows businesses to gain an insight into customer preferences and choices. This helps in the development of products and services that meet customer demands and expectations, improving revenues and profits earned. GoPro,for instance, uses event processing and analytics data from its products to build a range of new features for improved customer experience.
  • As businesses improve their decision-making capability through IoT and analytics, the end result is not just added revenue, but also improved competitive standing. By building better products, organizations can achieve a competitive edge in the market and drive substantial business growth.

Enterprise IoT Use Cases

The growth of IoT is leading to a significant rise in the amount of data generated that needs to be properly analyzed to maintain competitive edge, improve customer experience, and deliver new business value. Although IoT enables organizations to manage and control a web of smart, connected devices, it is only through analytics that they can drive value:

  • Predictive maintenance:Analytics is fueling predictive maintenance, supply chain management and on-demand delivery of goods and services. By offering access to data in real-time, organizations can assess the health of machines, carry out maintenance activities and ensure the safety of machinery and workforce. For example, Microsoft’spredictive maintenance solution accelerator proactively predicts the remaining useful life of an aircraft engine which is extremely useful to ensure safety of every flight.
  • Product usage analysis:Analytics doesn’t just end at understanding consumer behavior; it can also be used to carry out product usage analysis. Self-service and guided analytics solutions can then be correlated with social media data to determine how consumers use a particular product and how likely they are to actively discuss the brand on social media.
  • Video analytics:Deploying cameras, motion, and radar sensors can enable the safety and security of premises and people. In the surveillance context, the detection of anomalies is extremely important. Smart machines can be used to identify the state of the feed and derive normal or abnormal things over time. Bosch’svideo analytics systems can enable advanced intrusion detection, enforce health and safety regulations, detect blocked emergency exits, and even analyze behavior in retail environments.
  • Actionable marketing:The data gained from IoT analytics can help companies get good understanding on product forecasting. By understanding buying behavior, market fluctuations, and industry trends, companies can ensure optimum production while maintaining a tighter grip on quality control. Amazonuses WiFi robots to scan QR codes on its products to track and triage its orders.
  • Remote health monitoring:Analytics in healthcare is enabling practitioners to improve care outcomes. By analyzing critical health data captured by sensors and wearables, analytics is aiding doctors in more efficient diagnosis and enabling them to make better treatment and medication decisions. IBM WatsonHealth is providing critical data and insights to doctors across the world, helping them optimize their performance.
  • Precision agriculture: By leveragingIoT, farmers can gain access to actionable intelligence about their crops – they can know how the crops are growing, how much water or fertilizer is required or how potential threats such as weather are affecting plantings. John Deere’sself-driving tractors use GPS guidance systems that help make farming more efficient and precise.

Analytics at the Core

With IoT devices generating continuous streams of data, it is imperative for businesses to be able to handle this data and make it actionable. By equipping themselves with analytics, organizations can analyze massive amounts of data coming in every second from IoT devices. Analytics is enabling organizations across industries to get the most out of their IoT investment: from predictive maintenance to product usage analysis, video analytics to actionable marketing, remote health monitoring to precision agriculture – analytics is undoubtedly the key element of enterprise IoT projects today.

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