The Internet of Things (IoT) sounds like a consumer fantasy come true — who wouldn’t want to be able to turn off the lights at home from two towns away, or leave it to their refrigerator to make sure they know when milk, butter and other staples need to be replenished? But there’s more to IoT than lifestyle enhancement. IoT also caters to the corporate side, enabling organizations to collect and analyze data from sensors on manufacturing equipment, pipelines, weather stations, smart meters, delivery trucks and other types of machinery. Iot Energy Management and Analytics serves as a guide in your journey with Internet of Things devices.
IoT Energy Management and Analytics
IoT analytics applications can help companies understand the Internet of Things data at their disposal, with an eye toward reducing maintenance costs, avoiding equipment failures and improving business operations. In addition retailers, restaurant chains and makers of consumer goods can use data from smartphones, wearable technologies and in-home devices to do targeted marketing and promotions; the business side of IoT’s futuristic world of connected consumer gear.
Building and running the big data analytics applications typically required with IoT data isn’t a simple task. If your organization is looking to make sense of the data it collects from the Internet of Things, IoT Energy’s team of expert is here to guide you towards efficient data management and analytics.
Big data analytics is the process of examining large data sets containing a variety of data types — i.e., big data — to uncover hidden patterns, complex correlations, market trends, customer preferences and other useful business information. The analytical findings can lead to more effective marketing, new revenue opportunities, better customer service, improved operational efficiency, competitive advantages over rival organizations and other business benefits.
Big data can be analyzed with the software tools commonly used as part of advanced analytics disciplines such as predictive analytics, data mining, text analytics and statistical analysis.
Big data management is the organization, administration and governance of large volumes of both structured and unstructured data.
The goal of big data management is to ensure a high level of data quality and accessibility for business intelligence and big data analytics applications. Corporations, government agencies and other organizations employ big data management strategies to help contend with fast-growing pools of data, typically involving many terabytes or even petabytes of information saved in a variety of file formats. Effective big data management helps companies locate valuable information in large sets of unstructured data and semi-structured data from a variety of sources, including call detail records, system logs and social media sites.
Each company must decide what data must be kept for compliance reasons, what data can be disposed of and what data should be kept and analyzed in order to improve current business processes or provide a business with a competitive advantage. This process requires careful data classification so that ultimately, smaller sets of data can be analyzed quickly and productively.