This week, the Gartner Data & Analytics Summit highlighted key strategies for organizations to enhance their use of advanced analytics and artificial intelligence. A major theme of the conference was the ongoing challenge of poor data quality, which hinders AI deployment. Experts emphasized three critical journeys for data and analytics leaders: focusing on business outcomes, improving data and analytics capabilities, and fostering behavioral change in teams. Recommendations included establishing trust models for data, creating a modular tech ecosystem, and ensuring data governance and literacy among staff. Additionally, various companies announced innovative tools and platforms to help organizations streamline their data management and AI initiatives. Stay updated with our weekly summaries for more insights into real-time analytics and AI developments.
In recent news from the tech world, the Gartner Data & Analytics Summit highlighted crucial steps organizations should take to enhance their use of advanced analytics and artificial intelligence (AI). As businesses increasingly rely on data-driven decision-making, the summit addressed vital concerns, particularly the lingering issues surrounding data quality that could hinder the deployment of AI solutions.
Throughout the conference, leaders underscored that poor data quality will remain a significant barrier until at least 2025. To overcome this challenge, D&A (Data and Analytics) leaders need to navigate three essential journeys aimed at fostering AI initiatives effectively. These journeys are centered on achieving business outcomes, enhancing D&A capabilities, and encouraging behavioral change within organizations.
For business outcomes, Gartner recommends:
– Establishing trust models to ensure high-quality data.
– Monetizing improvements in productivity by evaluating total costs and risks.
– Clearly communicating the value of data and analytics initiatives.
In the pursuit of stronger D&A capabilities, organizations should:
– Create a modular and open ecosystem to swiftly adapt to evolving technologies.
– Ensure data is AI-ready and reusable.
– Explore the use of AI agents that can dynamically respond to new conditions.
Behavioral change is crucial as well. D&A leaders can facilitate this by:
– Instituting repeatable habits through training focused on data literacy.
– Embracing new roles that adapt to shifting AI landscape.
– Fostering collaboration across various teams for integrated success.
Overall, the Gartner summit provided a roadmap for organizations eager to harness the power of AI and analytics. Companies committed to embarking on these journeys can not only address existing challenges but also position themselves for future growth and innovation in an increasingly data-driven world.
Keywords: Gartner Data & Analytics Summit, advanced analytics, artificial intelligence
Secondary Keywords: data quality, business outcomes, D&A capabilities
What is Real-time Analytics News for the Week Ending March 8?
Real-time Analytics News covers the latest updates and trends in data analysis that happened during the week. It includes news on technologies, tools, and methods that help businesses make quick decisions based on live data.
Why is Real-time Analytics important?
Real-time Analytics is important because it helps businesses respond quickly to changes in the Market. By analyzing data as it comes in, companies can make informed decisions, improve customer experiences, and boost sales.
What are some key trends from this week’s news?
This week, two major trends in Real-time Analytics are the rise of AI-powered tools and the increased focus on data security. AI is helping businesses process data faster, while stronger security measures are essential to protect sensitive information.
How can businesses use Real-time Analytics?
Businesses can use Real-time Analytics to track sales, monitor customer behavior, and optimize Marketing campaigns. By understanding what is happening right now, they can adapt strategies to improve results.
Where can I find more information on Real-time Analytics?
You can find more information about Real-time Analytics in online articles, blogs, and industry websites. Social media platforms and professional networks can also provide the latest insights and updates on this topic.