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Essential Strategies for Effective Analytics Infrastructure Development

  • Schedule

    28 June 2024

    18.30 – 20.30 (WIB)

  • Online-Interactive Learning

    Via Zoom

OVERVIEW

In the Public Guest Lecture segment, we bring industry professionals with valuable experience to assist our public academy students. These professionals serve as mentors, equipping our students with practical knowledge and real-world perspectives. By sharing their insights and experiences, our public guest lecturers play a vital role in expanding the knowledge of our students, enabling them to thrive in their chosen fields.

Keynote Session
Keynote presentations will offer their perspectives on the current state and future of data science and its impact on businesses, emphasize its importance in driving business success in the data-driven era. Our guest lecturer will also share their insights, experiences, and perspectives about the topic.

Live Coding Session
In this session our guest lecturer will showcase their projects and features that utilize Data Science based on their experience in respective field/industry. They will also demonstrate the practical implementation of data science techniques using coding languages such as R, Python, or SQL.

Q&A Session
Attendees will have the chance to interact with our panel of industry experts during the Q&A session. This interactive session will provide valuable insights and an opportunity to learn from the leaders in the field by asking questions and getting expert answers on the topic.

Our Speaker

Yusuf Fachruddin – Head of Data Management at Danone

Yusuf Fachruddin is an experienced professional with a robust background in the Banking, Insurance, and FMCG industries, specializing in CRM, Data Management, Business Intelligence, and Analytics. Over the years, he has led teams in developing robust data foundations, spearheaded intricate projects, and focused on improving data quality. His expertise includes leading teams to build comprehensive Single Source of Truth (SSOT) systems, developing advanced database solutions, and enhancing business intelligence and analytics capabilities.

Course Syllabus

 As the business environment evolves to become more data-driven, it is fundamentally reshaping the way organizations operate. Building a robust analytics infrastructure is essential for driving informed decision-making, gaining competitive advantage, and fostering innovation. This session will explore strategies for effectively designing, implementing, and managing a scalable and resilient infrastructure that meets the evolving needs of the organization.

Syllabus

  • Provide a brief professional summary highlighting your experience and expertise in your respective field/industry.
  • Emphasize your background in data science, you may mention notable achievements or projects related to data science.
  • Highlight the critical role of analytics infrastructure in supporting data-driven decision-making and driving corporate growth.
  • Explain the impact of a robust analytics infrastructure on improving operational efficiency, identifying new opportunities, and mitigating risks.
  • Discuss the importance of aligning technology investments in analytics infrastructure with business objectives and strategic goals.
  • Provide insights into how to prioritize investments based on the organization’s priorities and anticipated return on investment (ROI).
  • Discuss the core components of a scalable analytics infrastructure.
  • Highlight the importance of flexibility, scalability, and security in the infrastructure to accommodate future growth.
  • Discuss the role of advanced analytics technologies, such as machine learning, artificial intelligence (AI), and predictive modeling, in enhancing the capabilities of analytics infrastructure.
  • Provide examples/case studies of organizations that have successfully leveraged analytics technologies to gain competitive advantage and drive innovation.
  • Explore strategies for fostering collaboration between IT, data, and business teams in the design and implementation of analytics infrastructure. Highlight the importance of cross-functional collaboration in ensuring that the analytics infrastructure meets the needs of end-users and stakeholders.
  • Highlight the analytics infrastructure built in the speaker’s industry.
  • Detail the tools and technologies used, such as data warehouses, cloud platforms, and analytics software.
  • Discuss the challenges faced during the implementation and how they were overcome.
  • Present the outcomes and benefits realized from the infrastructure, including any measurable improvements in decision-making, efficiency, or innovation.
  • If applicable, engage the audience with a live coding session related to one or some of the presented case studies.
  • Demonstrate the practical implementation of data science techniques using coding languages such as R, Python, or SQL.
  • Explain the step-by-step process, highlight key code snippets, and showcase the visualization of results.

RUNDOWN

ScheduleContent
18.30 – 18.35Opening
18.35 – 20.15Keynote
20.15 – 20.25Q&A Session
20.25 – 20.30Closing