With Viya’s performance advantage, data scientists can explore more model options without increasing operational costs, select models that deliver strong results while reducing costs, and enjoy the flexibility and cost-effectiveness of Viya's platform. Learn more about how Viya can enhance your analytics and automation capabilities: https://lnkd.in/gswp6MWh #sas #viya #performance #analytics #automation #data #ai #ml
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It’s time for the premier data and #AIconference series of the year - Cloudera’s #EVOLVE24! Join us to learn strategies to enhance data-driven insights and productivity in the era of #generativeAI https://bit.ly/3xUirjD
Trusted Data Today Fuels Tomorrow’s AI at Cloudera’s EVOLVE24 Event Series
cloudera.com
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As August gives way to September 2024, the landscape of data engineering is rapidly evolving, driven by groundbreaking trends. Here's a quick rundown of what's hot and how you can leverage these trends to enhance your skills and operations: 1. AI-Enhanced Automation in Data Pipelines The integration of AI into data workflows is transforming data quality management and pipeline efficiency. Actionable Step: Start incorporating AI tools like TensorFlow or PyTorch in your ETL processes to automate data cleaning and preparation tasks. 2. Real-Time Data Streaming With real-time data processing becoming more critical, it’s essential to adapt to technologies that facilitate instant data analysis. Actionable Step: Experiment with streaming platforms like Apache Kafka or Amazon Kinesis to manage real-time data feeds effectively. 3. From Model to Market: Operationalizing AI Operationalizing AI continues to be a dominant trend, requiring robust support from data engineering to be effective. Actionable Step: Enhance your understanding of MLOps platforms to streamline the deployment and monitoring of machine learning models in production environments. 4. Cloud-First Data Management Strategies Cloud platforms are increasingly central to data strategies, offering scalability and cost efficiency. Actionable Step: If you haven’t already, begin migrating key data operations to the cloud using services like AWS, Azure, or Google Cloud, focusing on hybrid architectures to optimize your existing infrastructure. 5. Advanced Analytics and Decision Intelligence As decision intelligence platforms evolve, they require sophisticated data models to predict and optimize business outcomes. Actionable Step: Dive into decision intelligence tools and start integrating them with your data warehouses to drive smarter business strategies. By staying ahead of these trends and implementing these actionable steps, you'll not only enhance your professional skill set but also add substantial value to your organization. Let's make September 2024 a milestone month for innovation in data engineering! Looking to discuss more? Connect with me today! #DataEngineering #AnalyticalEngineering #AI #CloudComputing #RealTimeData #September2024 #TechTrends #ActionableInsights
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🚀 Curious about how people are transforming their data game with #Databricks? Rick Rofe and the Adelaide Databricks User Group have an upcoming lunchtime session where we'll get an insight including a look at real-world #AI use cases via Databricks. This is going to be an eye-opener if you're not that familiar with Databricks. If you're already a user this is a great group to join for networking among the community. https://lnkd.in/g9ZMJeae #DataScience #BigData #Meetup
Adelaide Databricks Usergroup | Meetup
meetup.com
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Join Edward Screven, Chief Corporate Architect, Oracle as he talks about HeatWave and Generative AI! Build Generative AI Applications—Integrated and Automated with HeatWave GenAI [SOL3724] Edward Screven (Chief Corporate Architect, Oracle) and Nipun Agarwal (Senior Vice President, Oracle) and Vijay Sundhar (Founder and CEO, SmarterD) 📆Wednesday, Sep 11 ⌚8:30 AM—9:15 AM PDT 🎤 Ballroom E, The Venetian, Level 2 Join Edward Screven to learn how you can use HeatWave to develop generative AI applications without specialized expertise. Developers can create a vector store for enterprise documents with a single SQL command using built-in embedding models. You’ll also learn how to perform semantic searches in a single step using either in-database or external large language models (LLMs). Discover how HeatWave’s integrated and automated generative AI capabilities including in-database LLMs; an automated, in-database vector store; and in-memory vector processing help deliver accurate answers with best performance and price performance in the industry. https://lnkd.in/ghD6bG2Z #OracleCloudWorld #oci #heatwave #genai #aws #oltp #olap #lakehouse #datalake #objectstorage #cloud #ml
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The fastest path to relevant recommendations and search #ShapedAI #AITraining #MachineLearning #DataScience #AIModels #MLPlatform #ArtificialIntelligence #DataDriven #TechInnovation #AIOptimization #DataAnalytics https://www.shaped.ai/
Shaped | Recommendations and Search
shaped.ai
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🌟 Hands-on Workshop: Monitor Tens of Thousands of Clusters with Petabytes of Data in Real-time 🔹 Having a robust and efficient database is crucial for managing the massive volumes of data needed for AI-driven insights and operations. As such, a backend that offers a real-time data platform designed specifically for demanding AI applications that need low-latency horsepower is essential. The ability to read, write, and reason on petabyte-scale data in just milliseconds to enable real-time data processing is critical for today's AI workloads, which in turns, empowers organizations to innovate faster and more effectively. 🔹Learn more in a hands-on webinar on Thursday, July 25 @ 10-11 AM PDT / 10:30-11:30 PM IST to discover how to efficiently monitor tens of thousands of clusters with petabytes of data in real-time. As data volumes continue to grow exponentially, the need for efficient and effective monitoring solutions has never been greater. 🔹 You’ll learn: ➡️ How to monitor tens of thousands of clusters efficiently ➡️ The technologies behind handling petabytes of data in real-time ➡️ Strategies for optimizing database performance ➡️ Real-world use cases and best practices ➡️ Access to tools and code snippets for implementing similar solutions ✅ The workshop will include a live demo and code-share session. If you can't attend it live, you'll get the code and webinar recording in your inbox if you've registered. 📅 Register here: https://lnkd.in/gh9y9FDz #databases #artificialintelligence #ad
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“We call it data intelligence—the intelligence to understand your own data..that’s the big business opportunity for us.” Ali Ghodsi ~ CEO of Databricks In a bold move, Databricks, the global powerhouse in data, analytics, and artificial intelligence, has unleashed DBRX. DBRX isn't locked away behind corporate walls—it's open source. This means companies have the reins over their proprietary data. And where can you find DBRX? It's right there on GitHub and Hugging Face. Databricks isn't just being open for the sake of it; there's a purpose behind it. While tech giants like Google have been sprinting ahead with GenAI. Many other industries have been hesitant fearing the risks associated with sharing sensitive data to the cloud. Databricks seeks to close that divide, especially in sectors such as finance and medicine, where there is a strong desire for AI tools, yet apprehension looms large. With DBRX, the power is in the hands of the enterprise. No longer are they shackled by proprietary systems; they're free to refine their AI models effortlessly. From the central governance of training data in Unity Catalog to the magic worked by Apache Spark™ and Lilac A to process and clean data. But DBRX isn't just about giving enterprises control. With advanced features like RAG systems and the efficiency of the MoE training platform, companies can tailor-make DBRX models that fit like a glove. All while safeguarding their data privacy on their own servers. Already, companies like JetBlue and NASDAQ have taken the plunge into the DBRX world. The Hugging Face link to DBRX is available in the comments section 👇
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Hear from Databricks customers about their experiences using the Data Intelligence Platform. From ETL to data warehousing to #Generative AI, see what our customers have to say about simplicity and unification for their data, AI and governance use cases. Check out the reviews!⭐️
The G2 on Databricks Data Intelligence Platform
g2.com
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A new feature debuting in the GA release is the ability to specify data sources at the card level. This can be useful, for example, if you want to use only a subset of the available data to generate a given output. #Data #Technology #GenerativeAI
Amazon Q Apps Aim to Simplify the Creation of Generative AI Apps for the Enterprise
infoq.com
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Databricks is “doubling down” on working with its systems integrator partners, with co-founder and CEO Ali Ghodsi viewing services partners as an important part of the vendor’s go-to-market and widespread adoption of artificial intelligence tools. “The AI revolution is not going to happen without the SIs,” Ghodsi said during a Q&A session at the Data+AI Summit. Here’s what else he said during #DataAISummit:
Databricks CEO Ghodsi: Systems Integrator Partners Are Key To Winning 'The AI Revolution'
crn.com
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Sr Partner , Solutions at IBM Global Systems Inc.
3moYou nailed it - Viya optimizes model exploration, selection and cost-effectiveness. Empowering move.