Take one good step away from the larger picture, and all of a sudden, it makes complete sense that the internet of things (IoT) are ideal devices to take full advantage of data analytics. Consider the features contained in devices these days: cameras, sensors, accelerometers — all of these can collect valuable and unique data that can be transformed into equally valuable and unique information and knowledge. The nature of IoT makes this collecting and sharing of data even more potent, as devices can share information between each other and aggregate newly married data with even greater potential for change and improvement.
A World Of Riches For Data Analysis
The process of data analysis thrives in environments that are generating data sets both large and small. This is where you seek patterns, trends and other statistics that reveal new secrets and behaviors to target and serve. While the world remains enchanted with their toys, you envision those devices as valuable tools:
- Data structures: Collected data may come as free-form (or unstructured), fully structured, or semi-structured; each type has its own intrinsic value that can be mined.
- Leading edge: While other businesses blissfully continue their older, less effective data-collection practices from limited sources (emails, newsletters, promotions, etc.), companies tapping into the fuller IoT potential maintain a greater lead in the marketing game.
- Revenue driven: A sharper and fuller glimpse into the personality and motivations of your prospects and clients can open new worlds of prospective sales opportunities.
- Volume: Visualize the difference between a dripping faucet and a full-force fire hose, and you can imagine the vast chasm between passive and casual data collection as compared to aggressive and complete data gathering; by virtue of volume alone you can make incredible gains.
It's not enough to just stumble into a vast data paradise; the next equally important phase is determining which forms of data analytics are best served for each dataset.
Delving Into Your Wealth of Data
Thanks to the growing number and kinds of devices sweeping up data without pause, your problem may no longer be finding data but becoming clever enough to get the most out of the varying types of data coming your way. As you are examining incoming data from the multiplicity of devices capable of generating it, you will find different methodologies of analyzing your data available to you:
- Prescriptive analytics: Describes the art of merging and balancing descriptive analytics (events of the past) with predictive analytics (best estimates of future results) to define present actions that can influence the outcomes you seek.
- Spatial analytics: The ability to analyze and define geographical patterns delivers data, which can then be used to make the best use of spatial relationships between physical objects.
- Streaming analytics: These in-motion data sets can become gigantic, but the data analytics of event stream processing (as it is also known) can make on-the-spot decisions and urgent corrections. They're ideal for traffic analysis, financial transactions and air fleet tracking situations.
- Time series analytics: Having the capacity to monitor ongoing events and identifying emerging trends or patterns are regular practices for data analysts who work in such diverse areas as health monitoring systems and weather forecasting applications.
As more devices join the expanding IoT universe, expect even more data collection and analytical opportunities to emerge and evolve. Taking advantage of these growing data collection and analytics technologies offers its own set of challenges, which an agile and informed C-suite team, along with its tech crew, can use to their own competitive advantage by viewing it as an opportunity instead of dreaded hurdles that require constant clearing.
Managing The Challenges That IoT Big Data Analytics Pose
While visions of new and improved raw data from existing and new IoT devices can be enticing, preparing for this data boost is as essential as finding new methods of collecting data. Fortunately, foresight is your best weapon against unexpected data overload and the ripple effect it can have.
By maintaining a focus on the following areas, you can ensure that your data remains valuable instead of becoming overwhelming, unwieldy and unmanageable:
- Confidentiality and privacy: Remaining vigilant over the growing flow of data also means staying ahead of confidentiality and privacy concerns, especially as more devices communicate together.
- Data storage and management: Having the capacity to grow your storage and management systems in tandem with the growth of your data flow is more than logical — it is critical to your continuing success.
- Data visualization: Appropriate management as different kinds and formats of incoming heterogeneous data (structured, semi-structured or unstructured) are fed into your banks should transform the data for better visualization and comprehension.
- Integrity: Balancing the demand for sharing data and information across a broad swath of devices is the equally necessary protection of selected information, requiring robust systems that know the difference between private information and marketable data.
- Power: Being able to access data without missing a bit of potentially valuable information demands reliably powered devices that run smoothly and continuously, creating new challenges and demands in the arena of powering devices.
- Security and backup: This remains both a micro issue and macro issue, as both personal users and big data collectors have parallel motivations in place, which is the protection of their information through vigorous security measures and regularly scheduled backup practices.
The future landscape for big data appears to be expanding at an exponential rate, thanks to the continuing explosion of IoT equipment entering the marketplace and serving users both great (companies, governments, institutions, etc.) and small (all of us little guys).
The best advantage C-suite and IT professionals can give themselves in this growing marketplace is the right attitude — one of confidence, not uncertainty. While others are fearing the impending flood of data, you should be getting your boats, paddles and nets ready for the grandest fishing expedition known in the world of big data analysis!
Syndicated content featured from Forbes.