LGITSA - Local Government Information Technology South Australia’s Post

🚀 Exciting News! Join us at the AWS Databases & Analytics Day to discover how AWS can help your organization build the next generation data foundation in the AI era. 🌟 We have three tailored tracks to enhance your learning experience: 1️⃣ Databases 2️⃣ Analytics & Big Data 3️⃣ Executive Track In the Executive track, you'll gain insights from AWS Data experts on best practices for developing a modern data strategy, foundation, and governance model to scale data, analytics, AI/ML, and generative AI innovations across your organization. In the technical tracks, AWS experts will deep dive into services powering data ecosystems for numerous customers. Explore generative BI capabilities in Amazon QuickSight, leverage vector databases for AI applications, integrate data with zero-ETL for analytics and ML, and build resilient applications with Amazon Aurora, and more! Customer spotlights will offer valuable insights from others using managed AWS Databases & Analytics services. Don't miss this opportunity to immerse yourself in the future of data and AI, and network with fellow data innovators. Register now! 🌐 #AWS #Databases #Analytics #AI #DataInnovation #AWSInnovate Sign up here —-> https://lnkd.in/eEBYsDmP

BigQuery data canvas - a new AI-oriented tool Overcoming complexities in the journey from data to analytical insights can be frustrating. Data specialists spend precious time analyzing data sources, reinventing the wheel with each new question that arises along the way. They manipulate multiple tools, switch between coding languages, and collaborate with a wide range of teams in their organizations. This fragmented approach is rife with bottlenecks, preventing analysts from generating valuable insights and performing high-impact work as quickly as they should. At Google Cloud Next '24, BigQuery data canvas was introduced, reimagining how data professionals work with data. This new user interface helps clients create graphical data workflows that align with their mental model, while AI innovations accelerate the discovery, preparation, analysis, visualization, and sharing of data and insights.

"AI-ready data platforms are revolutionizing the way organizations handle information...AI-ready data platforms aren't just a trend; they're a strategic imperative for staying competitive in today's data-driven landscape." - Gerrit Kazmaier, VP & GM of Data Analytics, Google Cloud Want to learn more about how AI-ready data platforms can revolutionize your business? Read Gerrit's latest blog post on data analytics innovations that are fueling AI initiatives: https://lnkd.in/dnQ7Ec4T #AI #DataPlatforms #GoogleCloudAI #GoogleCloud #Artificialintelligence #GenerativeAI #GenAI #AIDrivenTransformation #BusinessTransformation #DigitalTransformation #VertexAI #Gemini #Singapore #SingaporeBusiness #SG

Quick Guide to Building Scalable Data Pipelines for AI & ML Imagine you're constructing a highway for data, a road that needs to handle small cars today but be ready for heavy trucks tomorrow. That’s what scalable data pipelines are all about. Let’s break it down: Start with a Strong Foundation Understand your data: What's flowing through your pipeline? Define the goal: Analytics? Predictions? Real-time insights? Choose the Right Tools ETL vs. ELT: Pick the right strategy for your needs. Cloud-first approach: AWS, GCP, or Azure future-proofing starts here. Orchestrators: Airflow, Prefect think of them as traffic controllers. Focus on Scalability Distributed processing: Spark and Dask handle big data like a pro. Decouple components: Let each part scale independently. Automate for the Win Monitor everything: Downtime isn’t an option. CI/CD pipelines: Keep updates smooth and risk-free. Final Touches Add redundancy: Think backups and failovers. Prioritise security: Encrypt data at rest and in transit. Remember, every great pipeline starts with small steps. The key? Build with tomorrow in mind. Think big, start small, and scale smart ♻ Repost to share with others. ⬆ Follow Shahzad Ali Kulachi for more. 🔔 Hit the bell on my profile for more updates

Data strategy in the Era of AI with Luis Campos "Are humans better equipped to ask questions or to answer them?" Thanks Luis for asking the hard questions! Looking forward to your message

🚀 Unlock the power of your data with Databricks and Microsoft Fabric! 🚀 Databricks and Microsoft Fabric are leading platforms that offer unique strengths and seamless integration. Together, they create a powerful, integrated data ecosystem that can take your organization far into the future. Check out the latest article from our CTO Colin Van Dyke diving deep into this topic! Key Takeaways: ✔ Complementary Services: Databricks and Fabric align perfectly, leveraging Databricks’ advanced ML and AI capabilities with Fabric’s user-friendly interface. ✔ Enhanced Productivity: Seamless integration increases productivity and collaboration across technical and non-technical teams. ✔ Improved Governance: Combining fine-grained RBAC & ABAC capabilities ensures robust data governance and security. ✔ Scalability and Flexibility: A Lakehouse foundation allows for optimized resource utilization and future-proof data management. Read the full story here 🔗 https://lnkd.in/env4wJv7 #DataAnalytics #Databricks #MicrosoftFabric #DataStrategy #AI #Governance

Your Data Infrastructure Determines Whether You Can Leverage AI and Machine Learning—Design It Wisely Data is the fuel for AI and machine learning. However, raw data alone isn’t enough—the quality, accessibility, and architecture of your data infrastructure will define the success of your AI/ML initiatives. When designing or modernizing your data systems, here are key considerations: 🔹 Move Beyond Traditional Data Warehouses: A Data Lakehouse combines the best of data lakes and data warehouses. It handles structured, semi-structured, and unstructured data in one system, making it a game-changer for AI/ML workloads. 🔹 Leverage Cloud-Native Solutions: Tools like Snowflake, Databricks, and AWS Lake Formation offer scalable, flexible infrastructures for building AI-ready platforms. 🔹 Data Quality and Governance: Without high-quality, well-governed data, even the most advanced AI models will fail. Implement robust ETL/ELT pipelines to cleanse and transform data. Ensure security, compliance, and data masking to protect sensitive information. 🔹 Automation and Real-Time Processing: Use streaming ingestion (Snowpipe, Kafka) to capture real-time insights. Automate data pipelines with CI/CD for faster deployment cycles. 🔹 Scalability for AI Workloads: Build an infrastructure that scales both compute and storage, ensuring efficient resource allocation for training and inference. 🔹 Performance Monitoring and Optimization: Fine-tune query performance with monitoring tools. Optimize storage tiers with a clear Bronze, Silver, Gold structure to keep data fresh and usable. 🔹 Collaboration Across Teams: Data engineers, data scientists, and AI specialists need a single source of truth for seamless development. A well-designed data lakehouse bridges this gap. The Foundation Matters: AI is no longer a far-future technology. It’s here, and your data infrastructure will determine whether your organization can harness its full power. Investing in future-ready architecture today ensures sustainable innovation tomorrow. #DataLakehouse #AI #MachineLearning #DataEngineering #DataArchitecture #Snowflake #CloudComputing #BigData

Another great launch at re:Invent today. Amazon Bedrock Knowledge Bases now support structured data retrieval from Amazon Redshift and Amazon SageMaker Lakehouse to build powerful and contextual Gen AI applications tailored to your business. Check the blog https://lnkd.in/gbUjV3Sb . Congratulations and great collaboration across Amazon Redshift and Amazon Bedrock teams.

Are you frustrated with your colleagues debating which data should be used or is correct? Do you have specific business problems you want to solve with data insights? Would you like to start making decisions using data faster, but you don’t know where to start? Have you already made investments in data solutions, but you are not getting the expected value? If any of these apply to you, our capability assessment can help! Our data capability assessment will provide actionable insights and recommendations to enable you to get started on your data-driven decision-making journey. Sound good? Reach out to our team of experts! #dataanalytics #ai #mdts #datacapability #datamanagement