Samuel Iheagwam
Data Developer / DBA @ Qore Technologies
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Samuel Iheagwam is a growth-oriented data professional with extensive experience in multiple data roles and a mastery of complex data tools. His unwavering passion for leveraging data to solve problems and collaborating with teams to deliver exceptional value has propelled him to create products that genuinely captivate users and drive business success. In addition to his remarkable track record of developing innovative data products and securing investor support for data-led projects, Samuel's expertise extends to being a seasoned data trainer.
Demonstrating his commitment to fostering talent in the data field, Samuel has successfully led nearly 10 consecutive cohorts of the prestigious Tech4dev Women Techsters Bootcamp Program. He has also established fruitful partnerships with esteemed organizations, including the Lagos state government, to empower data enthusiasts and newcomers on their transformative journey toward data greatness. Having trained over 2000 individuals from around the world, Samuel's profound impact resonates globally, enabling clients to unlock the full potential of data for unparalleled business success.
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Automated Intelligence: How Agentic Analytics Elevates Data Workflow Automation in Power BI
Efficiency and agility in data workflows are very key to maintaining business success, especially with the rapid innovations storming the tech and business world today. Organizations all over the world are no longer just focused on extracting insights for decision-making, but are now working to improve and strengthen their ability to efficiently manage and analyze vast amounts of data autonomously as this shift is very crucial for long-term business success.
In this session, we'll explore the concept of agentic analytics and its impact on data workflow automation within Power BI. How intelligent, autonomous agents can streamline data ingestion, transformation, and visualization processes, enabling organizations to achieve faster, more accurate insights, enhance scalability, and empower data professionals to focus on strategic decision-making.
This session would explore agentic analytics as a fancy term for intelligent systems that can think and act on their own to handle repetitive or complex tasks, the core principles of agentic analytics, adaptive workflows, self-optimizing systems, and how integrating agentic analytics into Power BI can significantly enhance organizations data workflows without manual processes.
Participants of this session will learn how to leverage Power BI's advanced features to automate repetitive tasks such as data preparation, refresh cycles, and report generation. The session will also cover best practices for integrating agentic capabilities with tools like Power Automate to create dynamic, end-to-end workflows that adapt to real-time data changes.
Think AI Will Fix Your Data Skills? Think Again
As new AI technologies emerge, the expectations to put upon them become more and more inflated. In the rush to adopt these AI technologies, many enthusiasts/professionals overlook the foundational data skills essential for career growth as well as successful Artificial Intelligence implementation. Of course, we can agree that Artificial Intelligence promises transformative potential, but it is crucial to point out how diving into the use of Artificial Intelligence without a solid grasp of data fundamentals is a ticking time bomb for anyone with growth in mind.
This session emphasizes on the importance of mastering core data functions/roles before engaging in Artificial Intelligence utilization and tackles the misconception that Artificial Intelligence can compensate for weak data practices.
By the end of this session, participants will recognize that foundational data skills are necessary for Artificial Intelligence implementations, learn how to develop a step-by-step approach to building a strong data foundation and enhance their capability to integrate Artificial Intelligence tools seamlessly and effectively.
Building Scalable & Resilient Database Systems with AI: From Concept to Execution
Ensuring the resilience and performance of databases is very crucial for organizations aiming to maintain uninterrupted business operations. In high-demand environments, database performance is often bottlenecked by several limitations. Many organizations have their data infrastructure established on robust, relational database platforms. However, as businesses evolve to meet the rising demands for efficiency, the limitations of these platforms become more apparent.
This session focuses on the scalability and resilience of database systems and how you can build them better with AI.
We'll start by explaining what resilience means for databases, why it matters, and the best ways to design database systems that can mitigate disaster and performance disruptions. Then, we'll dive into how AI can make these systems better by predicting and preventing problems before they happen, automating recovery processes, and keeping everything running smoothly with little human operation.
Through real-life case studies, we'll explore how companies have successfully used AI to improve their database systems, making them more efficient and cost-effective.
Database Management for Business Continuity
In the ever-evolving landscape of data management, ensuring the resilience and performance of databases is very crucial for organizations aiming to maintain uninterrupted operations and unlock the full potential of their data. As a database administrator at Qore Technology, my session is birthed out of real-life experiences over the months with disaster recovery challenges and ensuring database resilience. For this session, I will be sharing real-life case experiences on disaster recovery, actionable strategies my team and I have solved problems with, and best practices that will empower you to safeguard your data, as well as establish a more robust backup and recovery plans while proactively monitoring database health, and performance optimization for seamless operations.
Some of the key points to be discussed broadly include:
1. A practical exploration of best practices for database backup, including backup types, storage options, and recovery objectives.
2a. Learning how to establish effective disaster recovery plans, conduct regular testing, and ensure data integrity during recovery processes.
2b. My real-life case experiences and lessons learned from successful backup and recovery operations.
3. Exploring strategies for optimizing database storage, improving performance, and ensuring compliance with data retention policies.
4. Gaining insights into the importance of proactive database monitoring and its impact on performance tuning as well as exploring powerful tools and techniques for monitoring key performance metrics, identifying bottlenecks, and detecting anomalies.
5. Discuss continual improvement and growth, and the importance of capacity planning, scalability considerations, and adopting emerging technologies to meet evolving business needs.
Understanding Client Requirements & Driving Business Success
In today's competitive business landscape where data is abundant, understanding client requirements is key to driving business success and as such, the ability to understand and translate client requirements into successful business strategies has become paramount. In this dynamic session, we will explore the transformative power of data analysis in unraveling client requirements and driving remarkable business success. Drawing from real-world examples and industry best practices, we will delve into actionable strategies and insights by leveraging the wealth of data available that will equip organizations with valuable insights into their client's needs, preferences, and expectations, enabling them to develop tailored strategies, products, and services that meet and exceed client expectations.
My session will focus on the following key aspects:
1. Importance of Data in Client Understanding, where we'll discuss the significance of data in gaining deep insights into client behavior, demographics, and preferences.
2. Utilizing Data Analysis Techniques to segment-specific client needs and purchase patterns.
3. Enhancing Customer Journey and Experience, where we'll discuss identifying customer pain points and personalizing customer experiences, to deliver exceptional customer service.
4. Building Long-Term Client Relationships & strategies for leveraging client data to build and nurture long-term relationships
Through real-world examples and case studies, this session will provide attendees & organizations with a comprehensive understanding of the role of data analysis in uncovering client requirements and driving business success. Attendees will gain valuable knowledge on how to leverage data-driven approaches to drive business success, improve client satisfaction, and build long-lasting client relationships.
How data literate is your organization?
Becoming a data-driven organization is a journey, which unfolds over time, measured in years, and many a times decades. A feat more and more companies strive to become, especially in these times of uncertainty.
However, as more and more companies realize the power of data to inform business decisions, predict customer behaviors, and drive transformative technologies like machine learning and predictive analytics, chief data officers are under pressure to build a data-driven culture, one of the biggest obstacles many non tech focused organizations believe is that data is very often linked to or perceived as something which is purely technical.
In this regards, my session will be centered on the need for data literacy throughout an organization, creating a long lasting data sharing culture, further talks about why data literacy matters at all levels of an organization, as well as explanations that bring data out of that technology perspective and into a business perspective.
We will have a more closer look about how data culture influences behaviors in an organization, possible steps organizations and business leaders should take to accelerate these efforts.
I would also briefly talk about how broad access to data can help problem solving, how open communication can make it easier to gain support for and manage projects, and why experimentation delivers better results and reduces decision-making churn.
I am strongly of the believe that when everyone ‘speaks data’ in the same way, everybody can understand each other and as such, organizational leaders should invest in data literacy training for all their staff to ensure they have the skills necessary to effectively read and work with data, which will set the stage for increased data use and smarter decision-making.
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