Manas Jain

Working in #data policy and governance, there has been constant talk of #opendata and "interoperable datasets". However, #FAIRdata is not often a commonly used terminology within local landscapes (like India). Yet, its essence for making data more accessible and easier to share, has been at the forefront of many a policy discourse. In this blog, I write about the semantics and jargon of data governance. I question if it is the letter or the spirit which should matter more, and argue that the latter can prove more useful in promoting the use and adoption of FAIR data principles. https://lnkd.in/eNi2YibW #datagovernance #agtech #FAIR #responsibledata Martin Parr Chipo Msengezi Arun Jadhav Toby Penrhys-Evans Zoe Philpott Gideon Abegunrin Ashitha Ganapathy Henry Mibei Lucy Brett On Ki L. Melissa Allan Jessica Cagley

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Sarath Sasidharan and I have prepared the video for Episode 06, in which we'll study Objective Key Results (OKRs): a goal-setting framework that enhances alignment, engagement, and transparency within businesses, and its pivotal role in managing your data strategy. To ensure a practical understanding, we'll demonstrate using #MicrosoftPurview. We'll guide and define OKRs, enrich them with key results, and link everything to data products. The data itself, is managed within #MicrosoftFabric, so we'll also show that. For subscribing, here's the link: https://lnkd.in/eMw9c-_V

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AIM Research recently collaborated with USEReady to release a research report on the topic - 'Retiring Legacy and Modernizing Analytics Systems Among Enterprises'. This comprehensive survey report explores the transformative shift from legacy BI systems to modern BI systems among large enterprises across various industry sectors. Some of the key findings of the survey report: ⁍ A significant number of organizations (82.8%) recognize the need to migrate from legacy to modern BI systems ⁍ 54.3% respondents are planning to migrate away from legacy to modern BI systems within the next 12 months ⁍ CXOs are deeply involved in migration decisions (94.3%), with 54.3% of the time the decision being solely made by them ⁍ The majority of organizations (68.6%) prefer cloud-based solutions for transitioning their legacy systems to modern BI systems ⁍ Most organizations (70.6%) across sectors expect a small reduction (0-25%) in the size of their analytics teams with the adoption of modern analytics solutions ⁍ Most organizations (77.1%) prefer a phased approach to migration from legacy to modern BI systems Uday Hegde Harjot Singh Kohli Bhasker Gupta Kashyap Raibagi Read the complete report here: https://lnkd.in/eAaiCqXu #SurveyReport #AIMResearch #ModernBISystems #USEReady #LegacytoModernBISystems #AIM

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Data Mapping - Part 2 In this post, I will cover the areas to focus on when drafting the Data Mapping for an organization. Areas to focus when drafting the Data Mapping for an organization: 1. Share the benefits of Data Mapping with the relevant stakeholders which will enable in getting their buy-in along with all the important information required to prepare the Data Mapping 2. Understand the existing process within the organization including the Standard Operating Procedures (SOP's) along with the process flow of data from its origin to the destination 3. Data Mapping is a collaborative effort and hence should include all the processes/ departments within the organization that processes the personal data 4. Detailed review of the asset/ data inventory & follow the data flow 5. Understand whether the organization has good identity and access management controls which will enable in addressing the 3 parameters of security i.e. Confidentiality, Integrity and Availability 6. Identify any unforeseen uses of data within the organization 7. Understand why the data is collected by the organization 8. Understand the format in which the personal data is stored (structured or unstructured) 9. Identify all the different storage system interfaces which corresponds to the data collected My final post on Data Mapping will focus on the important aspects that should be covered as part of Data Mapping and about the good practices to maintain a Data Map.

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#GenAI models necessitates training on extensive datasets, which in turn requires robust #cloud storage solutions. As Gen AI continues to advance, demand for cloud services would surge correspondingly, creating a symbiotic growth relationship b/w the two. https://t.ly/9Rg-C

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✨ Excited to share my latest achievement! ✨ I recently completed the Snowflake Education Services Hands-On Essentials: Data Engineering Workshop. This workshop provided in-depth insights into modern data engineering practices using Snowflake's powerful cloud data platform. With hands-on experience, I gained practical knowledge in areas like data ingestion, transformation, and optimization, which will greatly enhance my ability to work with data at scale. Looking forward to applying these skills to drive impactful data solutions! 🚀💡 #DataEngineering #Snowflake #CloudData #DataTransformation #ContinuousLearning #ProfessionalGrowth

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It’s no secret that #ArtificialIntelligence is becoming more and more important, and so is data quality. Check out this article featuring SingleStore's CMO, Madhukar Kumar, where he shares his insights on #AI and data quality.

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Recently read a very detailed and compelling article from Mckinsey & while talking to few customers, some thoughts around the cost of implementation for Gen AI initiatives. These cost includes models which will go into production & not CSV based data for POC. :) These are still a very high view & will vary how the data is organized across the organization, catalogued and finally deployed into prod & its size. Most organizations still fall in the first category, while the CAPEX and OPEX are heavy but the value realization is manifold. Images generated using Stability AI . #ai #genai #tco #deeplearning #aiml #stabilityai #machinelearning

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The rise of foundation models like TimesFM is transforming time series forecasting by delivering zero-shot accuracy on massive datasets, changing how industries approach prediction challenges. 📈 Power of pre-trained models: Foundation models like TimesFM are simplifying forecasting across industries by reducing the need for custom setups while handling over 307 billion data points. 🤖 AI-driven precision: Google's latest advancements in time series forecasting leverage AI's ability to make accurate predictions without prior data training in specific contexts. 🛠️ Applications across industries: From retail to finance, these models optimize processes like stock management, customer service, and workforce planning by providing reliable forecasts. 🔄 NLP meets time series: The success of large pre-trained language models inspired their application to time series forecasting, benefiting from similar data structures but addressing unique challenges. #AI #Forecasting #TimeSeries 📊 Scalable solutions: These models handle huge datasets, making them ideal for complex forecasting needs in dynamic environments. 🧠 Bridging language and data: The sequential nature of time series data aligns with language models, driving innovations in prediction strategies. ♻️ Repost if you enjoyed this, and follow me for more content about telecom, generative Al, and leadership! https://lnkd.in/gAb6dTEk

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✨ Data for AI Leaders Roadshow Abstractions ✨   One dynamic month of public speaking, client (CDAO) connects, learnings. Multiple forums - AWS DataCon, Informatica World Tour, HETT Show, Snowflake World Tour; 100+ client and prospect conversations.   My abstractions:   AI | GenAI reality check - After we get past the "How great my AI use case ('experiment' is what most mean) is" narrative, the real conversation and learning begins, when leaders face the brutal facts that there is work to be done.    Pre-requisite for Scaling AI - Health | Wealth | Consumers | Citizens - Whichever domain you belong to, if you don't have "ready" data for AI, forget about scaling AI use cases. No mind-blowing product can scale AI unless- you know where to look to start navigating this puzzle.    'Lego'fying the foundation - Often data becomes the blocker for AI scaling. Productised data can become the catalyst to scale.    Trust worthy data and AI - Transparent, responsible, explainable, fair structures, policies, which can be set and monitored are key to a healthy data + AI scale-worthy solution    AI for Data and Data for AI - Data needs AI to solve it's problem. AI needs Data to solve its problem. You separate both - you lose the plot.    Data + AI portfolio value - It is no longer data value assessment, or AI value assessment, but the vertical integration of the Data + AI portfolio value, to make CDAOs win the AI race.    Double click on each of these topics with us. Let's learn more from each other. #data for #genAI, #responsibleAI, #artificialintelligence Sriram Narasimhan, Pushpa Ramachandran, Ashish Sharma, Ajay Upadhyay, Balasubramani Harikrishnan, Bijoy C, Soumya Chowdhury, Prakash K., Sukhvinder Phalora, Hema Hariharan, Jayakumar Rajaretnam, Tushar Marathe, Antonio Sawaya, Nishant Jain, Varun Khanna, Sangeeta Kar, Debojit Biswas

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I have been through many professional conflict situations. I have realized that conflicts are the unavoidable reality of a product management role. 😮 The role requires us to work with cross-functional teams, collaborate with competing priorities, and juggle through varied expectations and many such situations. ⚙ But there are some techniques and principles which has proved handy for me: 🗣️ Open Dialogue: Create a culture of open dialogue where team members feel comfortable expressing their concerns and opinions. Communication is key to resolving conflicts. 🤝 Build Trust: Invest time and effort in building trust among team members. Trust fosters collaboration and makes it easier to navigate conflicts when they arise. 🎯 Focus on Common Goals: Keep the team focused on common goals and objectives. When everyone is working towards the same mission, it's easier to set aside differences and work together towards success. 🔥 Conflict Resolution Skills: Equip yourself with conflict resolution skills. Learn to listen actively, empathize with others' perspectives, and find win-win solutions to disagreements. Conflicts are a natural part of any team dynamic. The ability to manage conflicts is used in several aspects of product management. Embrace them as opportunities for growth and collaboration! 💪 🚀Ready to supercharge your product journey? 💡 🔥 Book a complimentary catchup call with me (https://lnkd.in/g4QpwCjV) to learn more about unlocking your potential in this exciting field. #ProductManagement #TeamCollaboration #ConflictResolution

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🤯 Gen AI has crazy potential not just for transformation, but for automation and career trajectory. While traditional AI ML come with a demand of coding, data science skill set requirement, Gen AI can turn novice tech enthusiasts into engineers who can tune and deploy models. The reason being, they are pretrained for language - something we’re all comfortable with. 💡In fact, English is touted to be the next big programming language.. ✅ Can you give good instructions? - Great hop on board Sure, proficiency takes time, but considerably easy to get started. And if you mangage to find yourself a neat little role - Try and speak the whole story.. Do not be naive and place all bets on tech ❌If history has taught us anything, it’s that tech has two sides always. For instance, Take the case of LLM or Gen AI While the theoretical use cases remain large, the challenge lies in bias and hallucination. The transformative potential is huge but since these are pretty much non deterministic systems, it’s not cure all and we need to have a human in the loop approach. ⚡There are too many instances of racist bots, biased loan and hiring systems that turned out to be against women, and impact in law and media due to fictional case studies and copy right issues. I sincerely hope all discussions relating to Gen AI transcend the shiny moat, and incorporate what is the need of the hour ✅Developing these tech responsibly and skillng up workforce for the AI era.. Job displacement is an issue but skills like prompt engineering and tool adoption can ensure value added careers rather than mundane backoffice tasks - An area ripe for job displacement. And Indian workforce, whose large part of workday involves data entry, moving info between systems.. I feel are the ones who'll bear the brunt of the axe. PS:- ⚡Gen AI for non sexy office automation - A market of mindblowing proportions waiting for the right players.. Video & image creation is interesting as hell, but it all boils down to the King: ROI #generativeAI #artificailintelligence IBM IBM watsonx #jobdisplacement #automation #responsibleai

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It is quite alarming to note from this article on #'Heart of worry' as a caution that our health system demands us to take some time to pay serious attention to how the #life quality management index is compromised. While there could be multiple reasons and compelling situations that drives an individual to such a life state, can we ignore the fact that factors such as #willful ignorance, sense of insecurity, and lack of #self-realization of inner potential among other factors plays major role in transforming our life quality? Should this not trigger all of us, especially youngsters, to adopt healthy practices that facilitate overcoming #stress and experience a #joyful life for the rest of our life span? The views above are shared in the individual capacity to create awareness.

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Taming the Data Zoo: 3rd-Party Data & Security Let’s imagine data as a zoo full of valuable insights! But wild 3rd-party data can be a security risk. Do share your thoughts on securing bridge to manage this data without letting the tigers loose. #fractal #datagovernance #dataprivacy #collaboration

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Glad to have attended a luncheon organised by Alation on Empowering Excellence in Enterprise Data Management. Great sharing by Zach McIntyre on data governance uses cases from code repository sharing, usage reporting, and dashboard ownership along with a great panel of speakers from the industry. One question I asked was how do they see offensive data governance use cases in their organisation. Now the reason I asked this is because data governance and data management is not a sexy topic, it doesn't get business overly excited as all they want is for someone to just store my data, clean it up, and let me know where to get it. That's why it's important to balance between the defensive use cases (i.e. regulatory, risk, compliance) to offensive ones (i.e. customer touchpoints, marketing improvements, sales and operations) so business can feel the impact of having good data governance practices equalling to better business outcomes for them. PwC Singapore Greg Unsworth Mark Jansen Dion Hamler Avinash Raghu Kumar SG Aditya Shankar Vincent Tham Valerie Nanqi Liu 南齊 Ivy Lim Bee Ser Chan

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It was a grand start to snowflake data cloud summit'24. Wipro is uniquely positioned on the joint partnership with Snowflake and Nvidia in 3 areas: 1. AI and Machine Learning Integration: Wipro's WDIS powered by Snowflake’s data capabilities and NVIDIA’s GPUs to accelerate data processing and analytics, leading to faster insights. • AI Model Training: NVIDIA’s GPUs can significantly speed up the training of AI models on data stored in Snowflake, reducing time-to-market for AI-driven solutions. (Sridhar Ramaswamy spoke about "moving computing to data than data to the computer and Cortex AI next to data" ) • Inference at Scale: Combining Snowflake’s scalable data platform, with Wipro's WEGA framework and NVIDIA’s inference capabilities can enable real-time AI applications 2. Enhanced Data Work Load Processing • GPU-Accelerated SQL: Integration of NVIDIA’s RAPIDS libraries with Snowflake can enable GPU-accelerated SQL operations, along with seamless integration of WDIS • Complex Data Workloads: Leverage NVIDIA’s powerful GPUs to handle complex data workloads with Snowflake’s ecosystem and Wipro's WDIS 3. Industry-Specific Solutions • Healthcare : Use cases where Snowflake’s data sharing and analytics capabilities can be combined with NVIDIA’s AI tools to drive integrated value based care in health. • Financial Services: Wipro's fraud detection, risk management, and high-frequency trading by combining Snowflake’s data capabilities with NVIDIA’s AI technologies. • Retail and E-commerce: Enhance customer insights, recommendation systems, and inventory management using the combined power of Snowflake’s data platform and NVIDIA’s AI and analytics tools. Looking forward to exciting next 3 days and great partnership: Tyler Prince Amy Hirst-Kodl Dan Waters Sundara Ramalingam Nagalingam Scott Sharpley Alvin Da Costa Puneet Khanna Nagendra Bandaru Jason Eichenholz Ravi Seshadhri Narayan Kamat Pushpa Ramachandran Ajay Mangilal Jain Ajay Upadhyay Ashish Sharma Raju Gopalan Balasubramani Harikrishnan Tanusree Saha Anindito De Brijesh Singh Rahul Deshpande

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I had the privilege of joining an insightful discussion on ‘Bridging the AI skill gap’ with Dr. Shalini Lal and Shirin Rai Gupta. The conversation revolved around navigating organizational change and the transformative impact of technology. We explored how organizations like Fractal and Unqbe are evolving, identifying micro-trends such as Generative AI and the shift to cloud technology over time and leveraging them to stay ahead. During the session, I shared how Fractal focuses on problem-solving, decision-making, and hardcore upskilling to future-proof its workforce. We also discussed the significance of fostering an organizational mindset that embraces learning, adaptability, and continuous improvement. The ‘Smarter Everyday’ program at Fractal empowers our global teams to become GenAI-ready by embedding prompt engineering into daily workflows, fostering greater productivity and innovation.. A big thanks to Manish Sharma and Jerry Moses at People Matters and Shirin Rai Gupta at upGrad Enterprise for organizing this engaging session. It was a pleasure to exchange ideas, share real-life examples, and learn from the experiences of others. Looking forward to more such impactful conversations that inspire growth and transformation! #Fractal #Upgrad #PeopleMatters

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Good takeaways from your post Shanthi Srinivasan! Thanks for sharing. AI Adoption Trends: AI adoption is rapidly increasing, with 34% of organizations already using AI and 22% planning to adopt it this year. Generative AI is also gaining traction. Industry-Specific Use Cases: AI is revolutionizing sectors like fintech, healthcare, and retail with applications such as interactive chatbots, drug discovery automation, and hyper-personalized product descriptions. Cross-Industry Applications: Conversational AI, company-specific large language models, and digital asset management are some of the cross-industry AI applications gaining momentum. Future Predictions: The future of AI includes agentic AI, affordable development of large language models, and a strong emphasis on ethical and responsible AI.

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🎇 Light Up Your Data Insights this Diwali with BigQuery & Vertex AI Agent Builder! 🎇 Tired of fumbling in the dark to find insights in your BigQuery data warehouse 🕶? What if you could search your massive BigQuery datasets as easily as Googling 🤔? This Diwali, illuminate your data with the power of Vertex AI Search 🚀! Dive into my latest blog post to learn how to build a powerful, AI-driven search application for the 'tourism' use case. Link: https://lnkd.in/grt36_fU #Vertex_AI hashtag#Search hashtag#BigQuery Google Cloud

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