Must Know: Takeaways Gartner Data and Analytics Summit 2024
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Must Know: Takeaways Gartner Data and Analytics Summit 2024

Didn't make it to Gartner's Data and Analytics Summit this year?

Don't worry, we did. This month's Ignition newsletter is all about the Gartner Summit, with Consulting Services Manager Kris providing his download, including key takeaways from specific sessions.

We'll also be hosting a webinar in early September with Kris & Nischay on optimising AI in your business. The discussion will focus on translating Gartner's trends into practical, business value. Register your interest here >.

Harj Chand - harj.chand@ignitedata.com.au


Must Know: Takeaways Gartner Data and Analytics Summit 2024

Ignite was founded on the belief that there are no data projects, just business projects that use data. The Garner summit reinforced this founding belief for both AI and governance; to focus on business outcomes not just the latest tech, compliance, or control.

Governance should be approached as an enabler, not a controller. We start our focus with Data Discovery, ensuring an end-user focus to understand what is available, usable and up to date. This can help inform governance efforts and overall data literacy across the organisation.

Chief Data and Analytics Officers and their teams need to be value-focused, where the discussion should be about investment – not budgets. We understand from working with our clients that the value discussion can be hard, the key is not just thinking about short-term ROI, but how capability enables business strategy-aligned outcomes.

A few of Gartner’s Top D&A Predictions from the summit that really resonated – surfacing the themes of being Outcome Focused; Governance as an Enabler; and the challenge of being AI Ready:

  • By 2026, 75% of CDAOs that have failed to make organization-wide influence their top priority, will be assimilated back into technology functions.
  • By 2027, more than half of CDAOs will secure funding for data literacy and AI literacy programs, fueled by enterprise failure to realize the expected value from generative AI.
  • By 2027, 40% of CDAOs will have rebranded governance as business enablement of strategic business initiatives from the outset.
  • By 2027, 80% of data and analytics (D&A) governance initiatives will fail due to the lack of a real or manufactured crisis.
  • By 2028, more than 50% of enterprises that have built their own large language models (LLMs) from scratch will abandon their efforts due to costs, complexity, and technical debt.

Continue reading >


Technical Highlights from the Gartner Summit

Solution Architect Nischay Thapa shares his technical highlights from the 2024 Data and Analytics Summit.


How to Make Your Data AI-Ready and Why It Matters

Preparing data for AI is crucial for leveraging the full potential of AI technologies. The emphasis on data governance, continuous quality assessment, and the alignment of data management practices with AI needs highlights the evolving landscape of data strategies. Organizations must prioritize these changes to stay competitive and maximize the benefits of AI initiatives.

Continue Reading >


Upcoming Webinar | 5th September 2024

How To Optimise AI In Your Business

A discussion with Ignite’s Consulting Services Manager Kris and Solution Architect Nischay on how to translate Gartner’s trends into practical, business value.

Register >


What to put in place now, for AI success in the future

Organizations must evolve their data and analytics strategies to keep pace with technological advancements and the growing complexity of data environments. Embracing AI, managing complexity, ensuring trust, and empowering employees are critical to achieving business success in 2024 and beyond. The emphasis on practical actions and governance underscores the need for a structured yet flexible approach to data management.

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Practical Composable Analytics? What you need to know

There is a growing need for composable analytics to adapt to the changing demands of businesses. By shifting from rigid, IT-driven models to flexible, business-composed analytics systems, organizations can achieve greater agility and responsiveness. The integration of natural language processing and establishing fusion teams highlight the importance of collaboration and advanced technologies in driving analytics innovation.

Continue Reading >


What is the REAL cost? Measuring and Quantifying Cost, Risk & Value of AI

Past mistakes and the complexity and variability of costs associated with AI and GenAI initiatives highlight the need for detailed cost modelling and risk assessments. By categorizing AI opportunities and employing comprehensive cost and risk management strategies, organizations can better navigate the financial and operational challenges of AI implementation.

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Emerging Practices for Decision Intelligence: The Next Leap for Data, Analytics and AI

Decision Intelligence (DI) is extremely important in transforming how your organisation makes decisions. By integrating advanced data analytics, AI, and process modelling, DI provides a structured approach to improving decision accuracy, speed, and impact.

Continue Reading >


Data Mesh vs Data Fabric? Identify the Benefits and Risks Before Investing

It is important to understand both data mesh and data fabric before making investment decisions. This means you need strong metadata management and governance practices for successful implementation.

Continue Reading >


How do you justify your analytics investment?

Effort, usage and health. The three key criteria to determine if your analytics investment is worth its spend.

Through Ignite’s DataPulse reporting tool, plan your analytics investment based on value, follow through to adoption/consumption and see which investments are creating a return.

Open Live Demo >


Ignition curates the essential data science and analytics news from across the globe, delivered to you, free.

Sign up: ignitedata.com.au/ignition

Godwin Josh

Co-Founder of Altrosyn and DIrector at CDTECH | Inventor | Manufacturer

2mo

Kris's insights on translating Gartner's AI trends into actionable business value are invaluable for organizations seeking to leverage this transformative technology. Optimizing AI requires a deep understanding of the unique challenges and opportunities within each industry, which Kris expertly addresses. Nischay's expertise in bridging the gap between theoretical frameworks and practical implementations will undoubtedly enrich this webinar. Given your focus on AI optimization, how do you envision integrating explainable AI methodologies into your clients' data governance strategies to ensure responsible and transparent AI deployments?

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