IoT: Challenges and Opportunities
Summary
TLDRThe Internet of Things (IoT) connects physical assets, sensors, and devices, leading to an exponential rise in data. This data brings opportunities for new value and revenue generation. However, IoT environments face the challenge of real-time data analysis. Unlike the pre-IoT era where issues took days to resolve, IoT requires action within seconds or milliseconds. Applications in operations, customer-focused marketing, and innovation depend on fast action and advanced analytics. Predictive maintenance, demand optimization, and outage management are a few key use cases. Success demands unified analytics that process historical and real-time data for smarter, faster decisions.
Takeaways
- 🌐 **Internet of Things (IoT) Overview**: IoT digitizes physical assets by connecting sensors, devices, and machines through a network, enabling real-time communication between people and things, as well as between things themselves.
- 📈 **Data Explosion**: IoT networks can grow rapidly, leading to an exponential increase in data variety, velocity, and volume, which presents opportunities for significant data creation and revenue generation.
- 🤖 **Real-time Analysis Challenge**: The main challenge in IoT environments is analyzing the large volume of data from various sources and taking action in real time.
- 🚀 **Urgency for New Analytics**: The complexity of IoT, combined with high expectations from mobile and 24/7 IT environments, necessitates new analytics approaches and technologies.
- ⏱️ **Time to Action**: In the IoT era, the time to action has shrunk dramatically, from days to minutes, seconds, or microseconds, requiring real-time decision-making to capitalize on opportunities and address issues promptly.
- 🔌 **Provisioning Speed**: IoT applications demand swift provisioning, such as 30 minutes to provide electric service, reflecting the need for rapid response times.
- 🛡️ **Security Response Time**: IoT environments require quick responses to security breaches, with actions needed in as little as 5 milliseconds.
- 📊 **Data Value Degradation**: The value of data in IoT can diminish quickly, emphasizing the importance of timely action.
- 📈 **Application Categories**: IoT applications can be broadly grouped into operations, customer-focused sales and marketing, and innovation for new products and services.
- 🛠️ **Predictive Maintenance**: IoT enables predictive maintenance, demand and supply optimization, and one-to-one marketing, which are use cases that require critical time to action.
- 💡 **Advanced Analytic Solutions**: IoT demands advanced analytic solutions that unify historical, real-time streaming, predictive, and prescriptive analytics to provide faster analytics and smarter actions.
Q & A
What is the Internet of Things (IoT)?
-The Internet of Things is a system of interrelated computing devices, mechanical and digital machines, objects, animals, or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.
How does IoT digitize physical assets?
-IoT digitizes physical assets by using sensors and devices to collect data from these assets, which can then be analyzed and used to make informed decisions.
What are the challenges of analyzing large volumes of IoT data?
-The challenges include the need for real-time analysis, handling the variety, velocity, and volume of data, and taking immediate action based on the insights gained from the data.
How does IoT create opportunities for data creation and revenue generation?
-IoT creates opportunities by enabling the collection and analysis of vast amounts of data, which can lead to improved operational efficiency, customer insights, and the development of new products and services.
What is the significance of real-time action in IoT environments?
-Real-time action is significant because it allows businesses to quickly take advantage of opportunities and address problems as they arise, which is crucial in a fast-paced, data-driven environment.
How has the pre-IoT era differed in terms of time to action?
-In the pre-IoT era, issues could be addressed in two to three days, whereas in IoT environments, the time to action is often measured in minutes, seconds, or microseconds.
What are some examples of the time-sensitive actions required by IoT?
-Examples include 30 minutes to provision electric service, 30 seconds to act on information from devices, and 5 milliseconds to address a security breach.
How does the value of data in IoT applications change over time?
-The value of data in IoT applications can slip away quickly due to the high expectations and rapid pace of the IoT environment.
What are the three broad categories of IoT applications mentioned in the script?
-The three categories are operations and fulfillment, customer-focused sales and marketing, and innovation and new products and services.
What are some specific use cases for IoT applications?
-Specific use cases include predictive maintenance, demand and supply optimization, predictive one-to-one marketing, and outage management.
What does an advanced analytic solution for IoT need to provide?
-An advanced analytic solution for IoT should unify historical, real-time streaming, predictive, and prescriptive analytics, and provide faster analytics and smarter actions.
Outlines
🌐 The Internet of Things (IoT): Challenges and Opportunities
The paragraph discusses the digitization of physical assets through the Internet of Things (IoT), which connects people to things and things to things in real time. It highlights the rapid growth of IoT networks leading to an exponential increase in data variety, velocity, and volume. This data presents opportunities for significant data creation and revenue generation. However, the challenge lies in analyzing the large volume of information from all sources and taking action in real time. The IoT environment demands new analytics approaches and technologies due to its complexity and the high expectations set by the internet, mobile, and 24/7 IT environment. The need for real-time action to take advantage of opportunities and address problems quickly is emphasized, contrasting the pre-IoT era where issues could be addressed in days, to the IoT era where the time to action is measured in minutes, seconds, or microseconds. The paragraph also mentions specific use cases like predictive maintenance, demand and supply optimization, and outage management, which require an advanced analytic solution that unifies historical, real-time streaming, predictive, and prescriptive analytics.
Mindmap
Keywords
💡Internet of Things (IoT)
💡Real-time
💡Data Variety, Velocity, and Volume
💡Analytics
💡Time to Action
💡Predictive Maintenance
💡Demand and Supply Optimization
💡Customer-Focused Sales and Marketing
💡Innovation
💡Operational Efficiency
💡Outage Management
Highlights
The Internet of Things (IoT) digitizes physical assets, sensors, devices, machines, gateways, and networks, connecting people to things and things to things in real time.
IoT networks can grow rapidly, leading to an exponential increase in data variety, velocity, and volume.
The data generated by IoT opens opportunities for significant data creation and revenue generation.
The real challenge for IoT environments is analyzing the large volume of information from all sources and taking action in real time.
The complexity of IoT, combined with high expectations from the internet and mobile environment, has made the need for new analytics approaches and technologies more urgent.
Achieving business objectives requires the ability to act in real time to take advantage of opportunities and address problems quickly.
In the pre-IoT era, a supply chain issue could be addressed in two to three days, but in IoT, time to action is in minutes, seconds, or microseconds.
Examples of IoT time to action include 30 minutes to provision electric service, 30 seconds to act on device information, and 5 milliseconds to address a security breach.
The value of data in IoT can slip away quickly, emphasizing the importance of time to action.
IoT applications can be grouped into three categories: operations, customer-focused sales and marketing, and innovation.
Operations applications aim to prove out efficiency gains at fulfillment.
Customer-focused sales and marketing applications have the potential to increase customer satisfaction and long-term growth.
Innovation and new products and services can drive new revenue and business value.
Specific use cases within IoT applications include predictive maintenance, demand and supply optimization, and predictive one-to-one marketing.
Outage management is another critical use case that requires a fast time to action.
IoT demands an advanced analytic solution that unifies historical, real-time streaming, predictive, and prescriptive analytics.
The advanced analytics solution should provide faster analytics and smarter actions.
Transcripts
the internet-of-things digitizes
physical assets sensors devices machines
gateways and the network it connects
people to things and things to things in
real time a typical internet of things
network can grow rapidly resulting in an
exponential increase in the variety
velocity and the overall volume of data
this data opens opportunities for
significant daya creation and revenue
generation but the real challenge for
Internet of Things environments is how
to analyze the large volume of
information from all sources and take
action in real time what does this mean
for you the complexity of Internet of
Things combined with the high
expectations created by the internet
mobile and 24/7 IT environment has made
the need for new analytics approaches
and technologies more urgent achieving
desired business objectives requires the
ability to act in real time to take
advantage of opportunities and address
problems quickly in the pre-internet of
things era an issue in a typical supply
chain scenario could be addressed in two
to three days cycles for satisfactory
results but in Internet of Things time
to action is in minutes seconds or
microseconds 30 minutes to provision
electric service 30 seconds to act on
information from devices 5 milliseconds
to address a security breach this
explosion of data and the high
expectations in the Internet of Things
environment means the value of data will
slip away quickly the importance of time
to action for Internet of Things
applications could be seen in a wide
variety of applications and use cases
broadly speaking these applications can
be grouped into three categories
operations at fulfillment are a
convenient place to prove out efficiency
gains to customer-focused sales and
marketing applications have the
potential to increase customer
satisfaction and long-term growth three
innovation and new products and services
can drive new revenue and business value
there are also specific use cases within
these applications predictive
maintenance demand and supply
optimization predictive one-to-one
marketing outage management addressing
the critical time to action requirement
for these use cases and applications and
Internet of Things demands an advanced
analytic solution that one unifies
historical real-time streaming
predictive and prescriptive analytics
and 2 provides faster analytics and
smarter actions
you
Посмотреть больше похожих видео
5.0 / 5 (0 votes)