The Importance of Data-Driven Decision Making
The drive to make information more accessible and mobile is evolving rapidly. Almost a watershed moment in technological history, IoT (Internet of Things) and cloud computing are slowly changing life on planet Earth, whether for business, personal convenience or to keep in touch with friends and family.
IoT is increasingly being included in many companies’ data-driven transformation decisions. Indeed, those that have managed to embrace IoT have already started to see benefits such as improved inventory management, better operational processes, and increased equipment maintenance to name a few.
But a successful IoT data-driven strategy is more than just connecting a bunch of sensors to the internet and gathering data from them. There must be a robust way to effectively analyze the vast amount of data that IoT creates and make sense of it to gain genuine business insights. That is why an analytics strategy and data-driven decision-making should be a top priority for any company looking to get the most out of connectivity.
What is Data Analytics (DA)?
Data analytics is defined as a process that is used to examine small and big data sets carrying different data properties to extract meaningful conclusions and actionable insights. These conclusions usually take the form of trends, statistics, and patterns that help business organizations engage with the data proactively for effective decision-making processes.
What are the Different Types of Data Analytics?
- Spatial Analytics: This type analyzes geographic patterns that can determine spatial relationships between physical objects. Location-based applications such as smart parking can benefit from this method.
- Streaming Analytics: Also known as event stream processing, this type analyzes huge data sets in motion. Real-time data streams are analyzed in this process to detect any urgent situations and take immediate actions. IoT-enabled applications such as traffic analysis, assembly line tracking, financial transactions, and air fleet tracking can benefit from this type.
- Prescriptive Analytics: This type combines prescriptive and predictive analytics to understand the most efficient steps of action that can be implemented in a particular situation. Commercial IoT applications will benefit from this type of analysis to derive better conclusions.
- Time-Series Analytics: This type analyzes time-based data to identify associated patterns and trends. Applications such as weather forecasting and health monitoring can benefit from this method.
How Will the Merging of Data Analytics and IoT Positively Affect One’s Business?
Data analytics plays a huge role in the success and growth of IoT investments and applications. Analytics tools can help businesses make good use of their data sets in the following ways:
- Structure – IoT applications involve data sets that may be unstructured, semi-structured, or structured. There may also be a significant variation in data types and formats. Data analytics helps an individual to analyze all these different data sets using automated tools and software.
- Volume – IoT applications make use of large clusters of data sets. Organizations need to manage these large volumes of data and analyze the same for extracting relevant insights and patterns. Data analytics software can easily do the above along with efficient real-time data analysis.
- Competitive Advantage – With numerous IoT providers and developers present in the market, the competition is high. Incorporating data analytics in your IoT investments will allow your business to offer better services, thereby gaining a competitive edge over the others.
- Driving Sales – Using data analytics with IoT will enable businesses to get an insight into their customer choices and preferences. This will lead to developing the services according to the customer expectations and demands, which in turn will increase the profits and drive revenue for the organization.
Several scenarios have seen immense benefits from data-driven decision-making. For example, by applying data analytics to product usage, actionable marketing can be carried out by product companies. Data-driven decision making IoT can also enable increased surveillance and safety abilities through video sensors. Healthcare is another prime sector where increased diagnosis and treatment, telehealth services, remote health monitoring, and reduction of costs can be achieved using the same.
Data analytics coupled with IoT can therefore enhance customer engagement, improve revenues and gain that competitive edge. By collaborating with the right people, businesses can leverage their data for strategic and operational decision-making.
Start applying data analytics to your own business from today! Thingstel’s next-generation sensors, visualization platforms, and customizable analytics modules come with increased intelligence, reliability, and improved accuracy specifications. Our technologies can empower and strengthen your business, providing you with a wide array of solutions ranging from predictive maintenance to remote monitoring to real-time analytics and data visualization. Reach out to us in case you have any questions or simply want to know more.