1. Data Management &
Analytics in IoT: Extracting
Value from Data in Africa
Gloseije (Jessy) Bazolana

2. Understanding IoT
u The Internet of Things, or IoT, refers
to the billions of physical devices
around the world that are now
connected to the internet, all
collecting and sharing data.

3. “
”
As Africa's digital transformation
unfolds, effective data management
and sophisticated analytics are key to
unlocking the true potential of IoT

4. Digital Transformation in Africa: Unlocking
IoT's Potential through Data Management &
Analytics

5. Africa’s digital transformation
u Africa is currently witnessing a significant digital transformation, driven by
rapid advancements in technology and increased internet connectivity.
u Internet penetration is growing exponentially, with mobile connectivity
leading the charge.
u The rise in digital literacy and the availability of affordable smart devices are
also contributing to this digital boom.

6. Role of IoT in Africa’s Transformation
u The Internet of Things (IoT) is playing a crucial role in this digital
transformation. IoT refers to the network of physical objects—“things”—that
are embedded with sensors, software, and other technologies for the purpose
of connecting and exchanging data with other devices and systems over the
internet.
u From smart agriculture and healthcare to transportation and energy
management, IoT is creating new opportunities and solutions for long-
standing challenges in Africa.

7. The Importance of Effective Data
Management
u With IoT, comes the generation of massive amounts of data. Effective data
management is essential for the successful implementation and operation of
IoT systems.
u This involves ensuring that data from various IoT devices is accurately
collected, securely stored, efficiently processed, and readily available for
use.
u Poor data management can lead to significant issues such as data breaches,
loss of data, or incorrect data analysis, which can hinder the performance and
potential benefits of IoT systems.

8. Sophisticated Analytics: From Raw Data to
Valuable Insights
u Beyond managing the data, deriving meaningful insights from it is vital. This is
where sophisticated analytics come into play.
u By applying advanced analytics techniques to the data collected by IoT
devices, organizations can gain real-time insights, improve decision-making,
predict future trends, and identify potential issues before they occur.
u For example, predictive analytics can be used in smart farming to predict
weather patterns and determine the optimal time for planting crops, thereby
increasing yield and profitability.

9. Data Management
u Data management is the
practice of collecting,
organizing, protecting, and
storing an organization's
data so it can be analyzed
for business decisions.

10. Data Management in IoT
Effective data management is crucial in an IoT infrastructure. It involves
collecting, validating, storing, protecting, and processing required data to
ensure its accessibility, reliability, and timeliness
u Data Collection & Validation: "IoT devices generate vast amounts of data that
need to be accurately collected and validated for quality and integrity.”
u Data Storage & Security: "The collected data must be securely stored and
protected from any potential breaches or loss.”
u Data Processing: "Data is processed and transformed into a usable format for
further analysis."

11. Analytics
u Analytics is the scientific process of
discovering and communicating the
meaningful patterns which can be
found in data.
u It is concerned with turning raw
data into insight for making better
decisions. Analytics relies on the
application of statistics, computer
programming, and operations
research in order to quantify and
gain insight to the meanings of data.
It is especially useful in areas which
record a lot of data or information.

12. Analytics in IoT
Analytics is the systematic computational analysis of data. In IoT, it helps
derive valuable insights from raw data, drive decisions, and predict future
trends.
u Descriptive Analytics: "This form presents data in a way that interprets the
past. It helps understand what has happened.”
u Predictive Analytics: "Using historical data, predictive analytics forecasts
future events. It's particularly helpful in preventive maintenance of IoT
devices.”
u Prescriptive Analytics: "It suggests various course of actions to eliminate
future issues. This can be beneficial in automated decision-making systems."

13. “
”
IoT can act as a catalyst for
technological growth and
socioeconomic development in Africa
by leveraging effective data
management and sophisticated
analytics.