Analytics and the Internet of Things
Analytics and the Internet of Things
Analytics are vital to well-performing IoT deployments. Learn why it's vital, how to optimize, and the state of IoT analytics today.
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In previous posts, we’ve touched on the key values of the Internet of Things (IoT) and the criteria to check before adopting into IoT. Despite mixed messages on security and standards, there is a clear takeaway that a tidal wave of data is on the way. The major question remains: how do we convert all that data into useful information?
The volume and speed of this connected data will overwhelm organizations that aren’t able to mine quickly. Analytics act as the translation systems for IoT data. The careful application of analytics can unlock an endless wealth of information in support of rapid decision-making amid volatile economic indicators. Resting on top of a sea of structured data, your business will acquire a clear vision for strategies such as: how to tailor your best offerings for preferred customer segments, how to streamline your internal processes for a lower total cost of ownership and how to develop the items or services that are already in demand in the market.
Related reading: Breaking Down the Internet of Things
Optimizing Your IoT Performance
Analytics can help businesses capture the maximum value from connected data, but they have to be prepared before the flood of data starts to arrive. There are four core requirements for accomplishing this:
- The ability for the solution to store a high volume of data economically.
- Automatic correlation of performance data with customer engagement.
- The ability to allow managers to easily query the data in order to turn it into information and insights.
- Make the process repeatable and scalable to support any IoT deployment in the future.
Developing IoT for the End User
Amid the discussion of how businesses need to adapt to IoT, it’s easy to forget that IoT can still be a baffling change for the average consumer. To business users and developers who have seen the steady rise of M2M communication and intelligence, IoT is just the next step. Consumers with their attention locked on other priorities often express that they have no time to learn new interfaces. An IoT-based product/service should be invisible to the consumer. As Steve Jobs famously mused, new technology should be as effortless as a refrigerator. That’s one of the reasons that he introduced the iPod with a single button.
Due to the fact that IoT is often being built directly into familiar devices, it has to go further. Ideally, IoT should sit in the background, enhancing experiences and their daily life—like the new smart thermometers. To get there, most companies will need to use analytics to further refine their IoT services/products until it reaches that point.
In outlining the phenomena, Alvin Toffler said: “We may define future shock as the distress, both physical and psychological, that arises from an overload of the human organism’s physical adaptive systems and its decision-making processes.” Individual IoT gadgets (such as smart thermostats, drone-mounted cameras, real-time inventory sensors, and health wearables) improve the end user’s life, but the cumulative effect can trigger IoT overload.
The same applies to all of your customers, whether that means consumers, businesses or end-users. The solution begins with seeing the end-product from the customer’s point of view and how it fits into their lives. In other words, the answer starts with analytics.
The State of Analytics
The state of the current analytics market is that the offerings are not suited to the needs of IoT. The main types of analytics available are:
- Business Data Analytics: Concerned with metrics like revenue, new customer growth, and churn. Examples include Oracle Business Activity Monitoring, Teradata, and GoodData. These are too siloed to capture all the ways IoT will impact your business.
- Marketing Data Analytics: Concerned with customer preferences, behavioral information, and new feature usage. Examples include Google Analytics, Omniture from Adobe and Webtrends. These are too narrowly focused and require specialized skills to interpret the results.
- Application Analytics: The unified solution that focuses on a real-time analysis and visualization of automatically collected data to get insights into IT operations, customer success, and business outcomes. Leverage Transaction Analytics to deliver answers on performance and business metrics in real-time, User Analytics for a comprehensive IT operations visibility, and Browser & Mobile Analytics to optimize your end user’s journey.
It takes a more unified analytics solution to educate and develop the end-user to the point where the most effective, personalized IoT solution feels essential to their productive lives without triggering a future shock reaction. AppDynamics Unified Analytics actually connects the dots between your application’s performance, end users and business outcomes in real time. Auto-correlated rich, integrated data not only optimizes customer experiences, but drives a better business outcome as well. With the next generation of Unified Analytics solution—enterprise customers can quickly answer more meaningful questions than ever before, all in real-time, to power their connected initiatives.
Responding Faster to the Connected World
The future demands that you see, act and know in one elegant motion. Like all technological solutions, that sounds simple on the outside but is enormously complex on the inside. You will need instant answers to questions that cross-analytical boundaries, such as:
- What was the total value of Gold-level customers purchasing new features?
- What is the breakdown of who is driving our cars at the moment, by customer tier?
- Which device is most popular for connecting to our customer app?
- How many new customers have signed up for our service?
It can be incredibly frustrating for everyone concerned when basic management questions like these demand an intense amount of IT resources—but that is the future. Options in the world of analytics must evolve to meet the challenges of IoT and the new market forces.
We’ve built a more evolved solution to specifically address those forces. We streamline the entire IoT development process by giving you one unified platform to work on, with a single install and a consistent UI. Our production monitoring requires a very low (<2%) resource overhead. You can jump right into processes because we can auto-discover complex transaction flows and save you the hours you’d normally spend on manual configurations. Just like the Internet of Things itself, we set a baseline of healthy performance and learn from there, alerting you immediately to any performance deviations.
IoT applications cannot operate without a more comprehensive understanding of your customers and what they are striving to achieve. The right analytics will deliver reliable performance data on the complex mix of software, hardware, networks and third parties that make up any IoT application.
A flawless performance is the heart of your business. Your analytics should isolate any mission-critical issues and guide you in resolving them long before your customer service department hears about it. Adding the right analytics module to your connected applications not only brings real-time analysis and visualization of automatically correlated data to get insights into cross-functional outcomes, but also enables IT and business users alike to quickly answer more meaningful questions than ever before, all in real-time.
Published at DZone with permission of Saba Anees , DZone MVB. See the original article here.
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