Emma Louise Smith’s Post

In an era of rapid technological advancement, Chief Data and Analytics Officers (CDAOs) must stay ahead of the curve. Gartner's latest insights reveal four key trends shaping the data and analytics landscape in 2024: AI as a bet-the-business skill set Managing complexity over chaos Navigating data trustworthiness challenges Empowering teams through data literacy These trends highlight the critical role of AI, the need for structured approaches to data management, the importance of data trust, and the empowerment of employees through data literacy. CDAOs must proactively respond to these trends to drive tangible business value and maintain a competitive edge in an increasingly data-driven world.

REPORT: Gartner for Data & Analytics - over 100 Data, Analytics and AI predictions through 2023 Data and analytics leadership is evolving rapidly, requiring chief data and analytics officers and responsibilities to adapt to a ever changing and more complex environment. Gartner key predictions for 2024-2028 shed light on the future landscape: ☑ By 2027, 60% of multinational companies will adopt localized data strategies to align with regional needs and regulations. ☑ 75% of data responsibles who fail to make an organization-wide impact by 2026 will be integrated into tech functions. ☑ Over half of data responsibles will secure funding for data and AI literacy by 2027. ☑ 25% of data strategy responsibles by 2028 will shift focus to decision-making behaviors over data-driven approaches. ☑ Success will depend on building AI literacy, driving cultural change, and developing skilled teams. Governance in data and analytics is also undergoing a transformation, with key predictions for 2027: ✅ 80% of governance initiatives will fail without a crisis to drive change. ✅ 75% of data products may become redundant due to lack of usage. ✅ 60% of organizations could struggle to extract value from AI due to weak ethical frameworks. ✅ 40% of data responsibles will reposition governance as business enablers. ✅ Generative AI will boost the value of governance programs by 40% by 2027. The path to success for data responsible involves strategic foresight, adaptability, and a proactive approach to navigating the changing landscape of data and analytics leadership. https://lnkd.in/dnyVnvt3 #DataLeadership #AnalyticsStrategy #AIInnovation #GenerativeAI #DataGovernance #AITrends #BusinessTransformation #TechLeadership #AI2024 #DigitalTransformation #DataLiteracy #AIEthics #DataDriven #FutureOfData

Gartner's Over 100 Data and Analytics Predictions Through 2028 Exciting insights from Gartner's last research I received, highlight the evolving landscape of data and analytics, crucial for business leaders to stay ahead. Here are the key take outs from the document: CDAO Leadership: Chief Data and Analytics Officers will be pivotal in driving measurable business outcomes. By 2025, data fabric will be central to data management strategies. AI and Machine Learning: AI is set to revolutionize product management and business processes. By 2027, autonomous analytics will handle a significant portion of these tasks. Data Management Innovations: Adoption of data fabrics and active metadata will enhance efficiency and sustainability in data management. Sustainability will become a key criterion by 2026. Cloud and Digital Transformation: Cloud computing will underpin digital transformation initiatives, becoming essential for 75% of organizations by 2025. Data Security and Privacy Evolution: A shift towards human-centric cybersecurity and new identity management models will be critical. By 2027, social media will pivot towards decentralized identity. Industry-Specific Adaptations: Customized predictions for automotive, banking, healthcare, manufacturing, and retail sectors will drive growth and innovation through data and analytics. I find it quite interesting that although AI is the big topic of discussion at the moment, I can still see the basics of data is top of the agenda and we should definitely be tracking the progress on these predictions, as the landscape are changing fast. Things like Analytical AI, Gen AI, Causal AI and Autonomous AI will all dependent on the underlying platform. #DataAnalytics #AI #MachineLearning #CloudComputing #Cybersecurity #DigitalTransformation #GartnerPredictions #Innovation #BusinessGrowth #DataManagement https://lnkd.in/d8GJsSrj

In today's fast-paced business environment, managing #data effectively is crucial for staying competitive. #Data_Fabric is a groundbreaking approach that integrates structured, semi-structured, and unstructured data from various sources, eliminating data silos and enhancing data governance. At iTechtions, we're dedicated to helping businesses harness the full potential of Data Fabric. Ensuring data consistency, quality, and compliance is paramount. Data Fabric guarantees robust governance frameworks, upholding stringent standards to maintain data integrity across the organization. By seamlessly integrating diverse data types, Data Fabric improves analysis and decision-making. This holistic view of data enables businesses to derive actionable insights, driving smarter strategies and outcomes. Real-time analytics and #dataprocessing capabilities allow businesses to act quickly and intelligently. Adaptability to changing market conditions and maintaining competitiveness are key benefits of leveraging Data Fabric. Data Fabric leverages #AI and #machinelearning to automate numerous data management tasks. This reduces the need for human intervention, boosting productivity and efficiency across the board. Whether on-premises, #hybrid, or #multicloud configurations, Data Fabric architecture scales effortlessly to meet growing data volumes. This flexibility allows organizations to adjust to evolving business needs seamlessly. At iTechtions, we provide expert insights and tailored solutions to help your business implement and maximize the benefits of Data Fabric. Our team of specialists is here to guide you through every step of your data transformation journey. #DataFabric #DataIntegration #DataGovernance #RealTimeAnalytics #BigData #DataManagement #DataStrategy #BusinessIntelligence #AI #MachineLearning #DataAutomation #TechInnovation #Scalability #HybridCloud #MultiCloud #DataSolutions #DigitalTransformation #DataDriven #TechTrends

What are the top data and analytics trends you need to know? 🤓 Gartner, a leading authority in data and analytics, explores four key trends that are reshaping the industry. Discover how AI, data trust, and empowered teams can drive strategic business decisions:  https://lnkd.in/geUVsyqi Strata Analytics Group is staying on top of these trends—contact us if you need help navigating these changes! ✅ #DataAnalytics #Gartner #BusinessTrends #AI #DataStrategy

🌐 Navigating the Future: Why Small-Scale Data Interventions Are Obsolete in Forward-Thinking Enterprises 🚀 The business landscape is evolving rapidly, and the era of isolated data efforts is over. Discover why comprehensive data transformation is the key to success. Read More: https://lnkd.in/gBJEeV7t #DataTransformation #BusinessEvolution #AIIntegration

#Digitaltwins empower businesses to #simulate and #optimize products and processes in a #virtual environment, detecting potential problems before they happen and helping preserve valuable resources. From #sustainablemanufacturing to enhanced process control, explore how this powerful technology is reshaping industries by driving smarter, #datadriven decisions and setting new standards for operational and environmental performance. We live in a world inundated with data. IDC predicts that the global datasphere will grow to 163 zettabytes by 2025, and unstructured data represents an estimated 80-90% of all enterprise data. #Digitaltwins have reemerged as a #transformative force—letting organizations harness this data and contextualize it for #AIagents to use in high-value use cases across industries, from #manufacturing to #supplychainmanagement. #industry4pointzero #digitalmanufacturing #productivity #costefficiency #predictiveanalytics

Get ready for the APAC Data2030 Summit and dive deep into the future of data management across 3 powerful stages! Here's what each stage will cover: 𝐌𝐨𝐝𝐞𝐫𝐧 𝐃𝐚𝐭𝐚 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲 𝐒𝐭𝐚𝐠𝐞: Learn how to craft a future-proof, agile data strategy that supports advanced analytics and AI across your enterprise. From ownership to implementation, this track ensures you stay ahead of the curve. 𝐌𝐨𝐝𝐞𝐫𝐧 𝐃𝐚𝐭𝐚 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐒𝐭𝐚𝐠𝐞: Explore disruptive data platforms that adapt to shifting business models and changing workforce dynamics. Topics include data integration, transformation, orchestration, and more to help businesses scale efficiently. 𝐌𝐨𝐝𝐞𝐫𝐧 𝐃𝐚𝐭𝐚 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐒𝐭𝐚𝐠𝐞: Focus on building scalable, intelligent architectures that support data processing, analytics, and machine learning workloads. Learn how to align these architectures with both short- and long-term enterprise goals. Experience thought-provoking sessions and networking on 27th November 2024 at the Online Edition of APAC Data 2030 Summit! Register now at just US$ 99: https://lnkd.in/ev-DufW3 #DataArchitecture #APACData2030 #Analytics #VirtualEvent #APACData2030Summit2024 #OnlineEdition #Networking #DataDriven #Data Management #DataInsights

🌟 Transforming Data as Products 🌟 I recently read an insightful article from Gartner: "Apply 5 Top Practices to Improve Data Engineering." It digs into templatizing data products to better manage, automate, and streamline data-as-a-product frameworks. 🔍 Key Components of the Framework: Data Marketplace/Exchange: Product Catalog: Centralized repository for all data products. Usage Agreements: Standardized contracts for data usage. Usage Tracker: Monitoring and analytics for data product utilization. Templates: Semantics: Standardized meanings and interpretations of data. Datasets: Predefined data sets ready for use. Pipelines: Automated workflows for data processing. Interfaces: User-friendly access points for data interaction. Provisioning: Version Control: Ensuring consistency and traceability of data changes. Configurations: Customizable settings for different data products. Continuous Integration: Seamless updates and integrations. Regression Test Packs: Automated testing to ensure reliability. Contracts: Terms and Conditions: Clear guidelines for data usage. Service Level Agreements: Defined expectations for data service quality. Access Controls: Security and permission settings. Billing Policies: Transparent and fair billing mechanisms. By templatizing data products, organizations can achieve greater efficiency, reliability, and scalability in their data operations. This approach not only accelerates time-to-market but it may also ensures robust designs and smooth AI integration. Image Source: Robert Thanarj Actual Document: https://lnkd.in/efCzH3Kw #DataProducts #ProductEngineering #DataStrategy #Innovation #Gartner