"Years of enterprise experience have taught me that models are only as good as their data. Data science teams spend on average over half their time cleaning and preparing data for processing, using fallible processes that impact project delivery and team morale." We were honored to have Avi Zurel contribute to the Ultimate Guide for AI Data Pipelines. If you are working on releasing an AI product. you need to get your data ready for AI! How does that work ? What are the steps to follow to obtain a high quality data output that will help train a high performing model? We are telling you everything you need to know!...And even more in our FREE Ultimate Guide to AI Data pipelines. Get a copy below 👇 Enjoy! It's on us 😉 https://mltwist.com/guide/ #datapipeline #etlfora #dataquality #datacleaning #datalabeling #datatransformation #dataopsforai
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🔬"Getting your Data sorted is a prerequisite for your approach to AI" Some wise words from Simon Asplen-Taylor - with an associated plug too 😉. Some businesses are heading straight to AI without this consideration. Question is, how many will get their underlying Data Infrastructure prepared first? #databeforeai, #ai Mohit Joshi, Seun Sotuminu, Eddie Short, Katy Gooblar, Anna Gevorgyan, Joe Reis 🤓
CEO & Founder of DataTick | AI, Data, and Analytics (AIDA) expert | Data Strategy and Analytics Author | Creator of the AIDA Consulting Subscription Product | Board Advisor | Chief Data Officer
DATATICK POINT OF VIEW = AI is an extension of Data Science. We believe that AI is an extension of your existing analytics and data science capabilities. Which means that the barrier to entry isn’t as high as you may think. Getting your underlying data sorted is a prerequisite for approaching AI. This hasn’t stopped some firms from trying to go straight to AI without the right infrastructure, experience, or culture. But that’s short-sighted and not calculated for success. Because it’s a fact — AI performs best when it’s based on high quality data sets. If you base your AI on more complex data sets, you're going to get more value. Value over and above your existing data science capabilities. And if you empathise with our DataTick Points of View, keep an eye out…we have an announcement coming out tomorrow that might just provide clarity around how you can get started with AI… #datasorted #DataTick
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DATATICK POINT OF VIEW = AI is an extension of Data Science. We believe that AI is an extension of your existing analytics and data science capabilities. Which means that the barrier to entry isn’t as high as you may think. Getting your underlying data sorted is a prerequisite for approaching AI. This hasn’t stopped some firms from trying to go straight to AI without the right infrastructure, experience, or culture. But that’s short-sighted and not calculated for success. Because it’s a fact — AI performs best when it’s based on high quality data sets. If you base your AI on more complex data sets, you're going to get more value. Value over and above your existing data science capabilities. And if you empathise with our DataTick Points of View, keep an eye out…we have an announcement coming out tomorrow that might just provide clarity around how you can get started with AI… #datasorted #DataTick
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The key to harnessing the power of AI depends on more than just technology. It's also in how you embed AI into your organisation's culture, strategy, and decision-making processes. 1️⃣ Purpose Over Hype: AI isn't just about what's possible - it's about what’s meaningful. >> Focus on real-world problems where AI will deliver value. 2️⃣ Trust Is Essential: Governance, transparency, and ethics are not optional! >> Build trust in your AI systems by aligning them with clear standards and ensuring fairness, accountability, and compliance with laws and regulations. 3️⃣ Empower Your Teams: Foster a data-driven culture where innovation thrives. >> Equip your teams with the skills and tools they need to make AI a true enabler of success. 4️⃣ Scale Strategically: Move from pilot to production with a focus on scalability, reliability, and integration into core business processes. >> How you build your AI solutions today will determine how you are able to deliver more solutions and scale in the future. Technical debt from poor solution designs will amplify over time - just as well designed architectures will enable you to go faster. Don't underestimate the value of investing in getting your architecture and operating model right up front. What are you doing to harness the power of AI to deliver real, lasting business value? _________________________________ Baringa have a world-class Data, Analytics, AI and Solutions Engineering capability. We are different in the way we work: we put people first, bring the best from across our industry and capability specialist teams, and deliver impact that lasts. If you are interested in how we could help you, please do get in touch. _________________________________ Follow me if you’d like to hear more tips and thought leadership on AI and Data Strategy, Data Management, Data Analytics, Data & AI Culture. #Data #Value #Success #DataGovernance #DG #Analytics #AI #ArtificialIntelligence #ML #MachineLearning #GenAI #DataManagement #DataLiteracy #DataCulture
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𝐖𝐡𝐞𝐫𝐞 𝐬𝐡𝐨𝐮𝐥𝐝 𝐨𝐫𝐠𝐚𝐧𝐢𝐬𝐚𝐭𝐢𝐨𝐧𝐬 𝐬𝐭𝐚𝐫𝐭 𝐰𝐡𝐞𝐧 𝐭𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐚𝐛𝐨𝐮𝐭 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐢𝐧𝐠 𝐀𝐈? During our Webinar last Wednesday, Aaron Zamykal 🚀 shared a thought-provoking perspective – we're not at the start of AI; we're actually approaching the end of it, in terms of its foundations. As Aaron explained, the roots of AI date back to 1756 with the first prediction theorem, and since then, AI has always been about mathematics and code. In fact, as we advocate for more advanced AI applications, it's easy to overlook the unsung heroes behind it all: data engineers. At the core of AI is data. Most organisations already have the answers they’re looking for hidden in their data sets. The real challenge? They haven’t figured out how to bring them together to solve the right problems. As an AI company, Aaron believes in the freedom to be more human. AI can support people, but only if organisations start with the right foundations. That foundation is data architecture. If you're thinking about implementing AI, start with the basics – get your data strategy right first. It’s the key to unlocking AI’s true potential for your organisation. #AI #DataEngineering #DataArchitecture #BusinessTransformation #Innovation #HumanCenteredAI
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Excited for our webinar series kicking off November 7th at 1 PM EDT! We're diving into data management and AI success strategies—don't miss out on valuable insights and real-world examples. Register now! #GenerativeAI #DataManagement #AISuccess #WebinarSeries #MutuallyHuman #MicrosoftFabric
Join us for the first session of our webinar series, The Path to Generative AI, on Nov. 7th at 1 PM EDT. In this session, Laying the Foundation, we'll focus on how effective data management prepares your organization for AI success. 🔍 Explore key roles like database admins, data engineers, and data stewards 📊 Learn essential data management strategies 💻 See Microsoft Fabric in action with real-world use cases This webinar is designed to help you understand the critical components of a successful data strategy, setting the stage for future AI innovation. Don't miss this opportunity to gain valuable insights and practical knowledge as we kick off our journey to Generative AI - Register now! ⬇️ https://hubs.la/Q02TGLCx0 #AI #GenerativeAI #DataManagement #MicrosoftFabric #Webinar #AIInnovation Nick VanderLaan Jordan Poortenga
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👥🗣️Discussion Group: Where do I Start with AI?: Identifying the Use Cases that Can Provide Value Quickly and Accelerate your AI Adoption 📊📈 • What problems within my org can I address NOW with AI that can show value to stakeholders? • My data isn’t perfect, but I don’t want to be left behind with AI adoption, what are my options? • Build or buy? What resources, tools, and funding do I have available to begin an AI project? • What governance frameworks do I need in place to make sure we are compliant and that we can deploy with confidence 🎤Moderator: Alex T., Senior Data Scientist, DataRobot 👉Follow us for more content like this! #CDAOChicago 2024 #data #analytics #dataanalytics #DataAndAnalytics #Ai
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The future of AI in data analytics isn't just about fancy algorithms – it's all about metadata! While current AI solutions might not be the silver bullet for data practitioners just yet, the focus on building strong metadata platforms is an exciting development. I think that rich layer of context is what will truly unlock the potential of AI in our field and allow tools to connect to the data models and documentation we build in a meaningful way that moves the ball 🏀 for the business. The workflows dbt brought us really get us to the next steps of interacting with AI to build more meaningful development for our stakeholders. A recent thought-provoking piece by Tristan Handy from dbt Labs explores the intersection of AI and data analytics. While AI has made significant strides, it's not quite tackling the core challenges data teams face today. The key seems to lie in better data understanding through robust metadata. Imagine a future where AI can not only generate documentation for models but also help debug complex issues like conversion rate drops. This is the power of marrying advanced AI with a comprehensive metadata platform. What are your thoughts on the role of metadata in the future of AI for data analytics? I'd love to hear your insights in the comments! #AI #dbt #analyticsengineering #dataengineering #data #datadriven
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Automate Data Cleaning & Preprocessing with AI: Boost Your Productivity! | Digital Profits Say goodbye to tedious manual data cleaning! In this video, learn how to use AI to automate data cleaning and preprocessing tasks, saving you hours of work and boosting your productivity. Discover top AI tools like Trifacta Wrangler, DataRobot, and Pandas AI that can help you efficiently handle missing values, outliers, and feature scaling. Whether you're a data scientist, marketer, or analyst, this tutorial will show you how AI can streamline your workflow and ensure your data is ready for analysis or machine learning. Check the link for the tools I’m using! https://lnkd.in/gTWwhYxN Don’t forget to like, subscribe, and hit the bell icon for more tips on using AI to grow your business and skills! #AIDataCleaning #AutomatedDataPreprocessing #DataScience #AIForBusiness #DataCleaningTools #PandasAI #MachineLearning #DataAutomation #ProductivityBoost #DataAnalysis #AIinBusiness #Trifacta #DataRobot #DigitalProfits
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How do you know if your organization is ready for AI? 🤔 In her latest #DataManagement blog post, Terry Dorsey, Sr. Data Architect/Evangelist North America at #Denodo, explores the key indicators that determine if your business is prepared to adopt #AI effectively. From assessing your data readiness to understanding your organization's objectives, Terry breaks down the essential steps for transitioning into an AI-driven future. 🚀 Whether you're just starting your AI journey or refining your strategy, this blog offers valuable insights into making #datadriven decisions with confidence. 👉 https://okt.to/6JWs1N Let's discuss: What steps are you taking to ensure your AI readiness? Share your thoughts below! ⬇️
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What’s the secret to data reliability? 🔑 Is it the right team skills? Just think about how automation and machine learning can change the play for your data reliability. Swipe to know what it takes to succeed in today’s complex data space. Dive into more insights 👉 www.qualdo.ai/drx #DataObservability #Data #AI #DataReliability #Machinelearning #DataJourney #DataVisibility #Qualdo #ML #TechInnovation #techskills #dataskills
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