The 4 main trends in Data - Betting the Business, Managed Complexity, Be Trusted, Empowered Workforce

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As always, a shoutout to our superstar sponsor, ANZ for helping bring this event to life!

Introducing… Girls in Tech Australia's Powerskill Panel: The 4 main trends in Data

Gartner has identified several key trends in data and analytics (D&A) for 2024, which are shaping the way organisations utilise these technologies to drive business value. Source: Gartner (April 2024) Here are the main trends:

Betting the Business: AI is transforming industries, and D&A leaders must develop and demonstrate a strategic skill set in AI to lead enterprise AI strategies effectively. This includes aligning AI initiatives with business outcomes to avoid resource misallocation and underutilised investments​. As AI continues to transform industries, demonstrating strategic AI skills and leading AI initiatives is crucial. This trend opens opportunities for women to take on leadership roles in AI and data strategy, showcasing their capabilities and influencing major business outcomes

Managed Complexity: The increasing complexity of D&A systems requires leaders to embrace and manage it using AI-enabled tools. These tools, such as augmented data management and natural language processing, help automate processes and improve productivity. Gartner predicts that by 2025, data fabric will play a crucial role in addressing data management complexity​. This trend highlights the need for diverse skill sets, offering women the chance to excel in technical roles that involve automation, data management, and analytics, and contribute to the evolving tech landscape.

Building Trust: Trust in data is essential for accurate decision-making. D&A leaders need to implement decision intelligence practices and effective AI governance to ensure data is ethically governed, secure, and free from bias. This helps build trust among stakeholders and enhances the reliability of data. Women in technology can lead efforts in AI governance and responsible AI practices, promoting ethical standards and trust in data, which are key for the success of AI initiatives​.

Empowered Workforce: It's important for organisations to empower their employees through AI, rather than making them feel threatened. This involves investing in AI literacy programs, adopting adaptive governance practices, and creating a trust-based approach to managing information. By 2027, more than half of Chief Data and Analytics Officers (CDAOs) are expected to secure funding for data and AI literacy programs to maximise the value of generative AI.

Join us for an engaging session featuring an inspiring panel:

Elisa Koch, Head of Data & Analytics, AFL
Elisa has worked as a Data & Analytics leader in the US and Australia in industries spanning finance, FMCG, technology, and sport. She is currently the Head of Data & Analytics at the AFL. Elisa serves as an Advisory Board Member for the Institute of Analytic Professionals Australia and is on the board of Spectrum Migrant Resource Centre.

Janine Lloyd, Head of Home Loan Data, ANZ
Janine is collaborative, strategic data leader who builds international data led cultures, creating value for businesses, our people and our customers. She has over 20 years experience working in finance, identifying, championing and leading strategic projects and teams. Janine is particularly passionate about developing data professionals and leaders and was an IAPA top 25 Analytical leader in 2022.

Rose Skandari, AI & Data Science Manager, BP
Rose is a professional data and AI leader with extensive experience in developing and running AI and Data Science capabilities and practices across various industries, including finance, energy, retail, and engineering. She has worked global companies like BP and been lecturing on AI at Kaplan Business School. She was named one of Australia's top 25 Analytics Leaders in 2020 and was a finalist in the Women in AI Awards in 2022.

And moderated by the always incredible Vanessa Kelly, Girls In Tech Australia Board Member. 


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