Erin O'Brien Hawley’s Post

Cloudera's Chief Product Officer, Dipto Chakravarty, talks about turning #EnterpriseAI hype into business reality with our #OpenDataLakehouse and partner ecosystem. http://spr.ly/6043VvzPv #ClouderaPartners #GenAI #TrustYourData

Sure, you've heard of Dagster. But do you really KNOW about Dagster? Check out this high-level overview and learn about Dagster's philosophy, core components, benefits, and why it stands out as the ideal tool for modern data orchestration. Whether you're a seasoned data engineer or new to the field, it'll help you understand Dagster and its potential to transform your data processes. Read here: https://bit.ly/3yPUf27 ---------- Follow Dagster Labs to learn about #dataengineering and building a productive #data platform through our talks, deep dives, and Dagster updates.

Clari ‘s Revenue Cadence Playbook is the jam! Without this framework, or similar, sales teams run full steam but go nowhere special. 😭 I have found so much value from using this playbook with clients to shift from wandering revenue to a scientific process. Repeatable, measurable and results focused! It all starts with the first interaction (you might call it a lead, qualified inquiry, stage 0 opport, etc). Once the opportunity is in motion, Clari is a fantastic tool to keep your sales team focused on managing the risk in their pipeline and delighting customers. It’s not the only tool, but Clari’s out of the box package is super impressive. How do you approach the process driving your revenue cycle? #forecasting #revenue #sales #salesops #gtm #automation #ai

Hear our CPO - Dipto Chakravarty - talk about the scale and rate of innovation around Generative AI, how our customers are discovering thousands of new use cases, and how our open data lakehouse, AI Quickstarts (aka: Applied Machine Learning Prototypes), and our unique approach to Hybrid help deliver with reduced cost and complexity while assuring security and compliance. #EnterpriseAI  #OpenDataLakehouse #ClouderaPartners #GenAI #TrustYourData

All about #RevOps: Scale up your team and tech stacks 🚀   Improving your team and ops at the same time? Follow these 5 strategies shared on June 13th by industry experts: - Prakash Raina, Co-Founder of Subskribe - David Ma, Head of GTM Ops at Zip - Mollie Bodensteiner, VP of Operations at Sound Agriculture Get the tools and insights you need to scale your RevOps functions from early-stage startup to IPO.  💯 Key Takeaways: - Foundation: Right data governance and architecture save future headaches. - RevOps structure: Optimal team setup and scaling at each growth stage. - Tech stack: Framework for evaluating, onboarding crucial tools, and offboarding ineffective ones. Register here! - https://lnkd.in/dmsS7Hma

Learn from the best and join us at an upcoming event with Google team members! Hear from Lucas Thelosen, head of product, and Freddy Fang, software engineer, as they discuss what companies that have been successful with data & AI have in common—and what you can do to be a Data Hero yourself.

#RAG provides a way to give an #LLM superpowers. RAG models can 1. Provide More Accurate and Current Information: The retrieval system can access recent data, articles, studies, and other resources that the LLM may not have been trained on, ensuring that the generated content is informed by the latest information. 2. Enhance Contextual Understanding: RAG models can pull in contextually relevant information, which helps in generating more accurate and detailed responses, especially for queries where specific, up-to-date knowledge is crucial. 3. Improve Relevance and Specificity: The retrieval system can help focus the model's responses on more specific topics or details, tailoring the output to better match the user's query. 4. Expand Knowledge Base: RAG allows LLMs to transcend the limitations of their training data, accessing a broader range of information and knowledge. In an enterprise setting, these capabilities can be particularly valuable, as they enable LLMs to provide more precise and current information, which is often critical in business contexts. Databricks has many solution accelerators aimed at accelerating the #DataToAI and #DataDemocratization journey.

@dagster’s launch week starts tomorrow. We’re launching a bunch of new initiatives and features embedded right in the orchestrator: * Embedded Data Quality * Insights for Cost Management * Dagster University * Embedded ELT * Deconstructing Dagster: Pipes and External Assets https://lnkd.in/g9p4Rj4F The theme of the week: It’s time for the data engineer to rise again and “escape the modern data trap”. Composability and embedding need to make a comeback, as the pendulum has swung too far towards managed, opaque SaaS tools. What do we mean by a trap? Well, the MDS was not designed for data engineers, and it shows. It doesn’t scale with their needs. The MDS was a huge leap forward for the data ecosystem and it delivered a ton of value. But it also has trouble meeting the demands of data engineers who want a leveraged platform where they can embed and composable capabilities, and automate them, rather than mash together off-the-shelf tools. It ends up coming apart at the seams in the real world. This is feedback we have heard from our community and customers: * Presumption of homogenous storage and compute * Too many disconnected tools * Too expensive. * Descends into chaos at moderate scale * Lack of automation, flexibility, composability The MDS tools great and built by great companies. But they just aren’t always the right choice. We think engineers should be able to choose between standalone tools and embedding technology. Only adopting standalone tools is the trap. You end up with “easy” solutions that end up not composing and compounding. We believe the orchestration layer/control plane is the right place to do that. What is critical is that the control plane is a single pane of glass that can bring cohesion. Learn more about our vision on this starting toward. Data engineering's making a comeback.