MetaDAMA

"Det er vanskelig å komme seg ut av det jeg kaller: et excel-helvete. / It is hard to escape, what I call: Excel-hell." How can mid-sized companies balance resources and create effective #DataGovernance and #DataStrategy? Join us on #MetaDAMA as we talk to May Lisbeth Øversveen, from Eidsiva Bredbånd. Here are Winfried Adalbert Etzel key takeaways: 🔸 The way we talk about data as a profession has changed, the lingo has changed and we adopt to trends. 🔸 To display and evaluate data from different sources that are not connected, excel becomes the tool of choice. 🔸 There is a very calculated amount of resources, that limit your ability to set up substantial teams to work exclusively on eg. Data Governance. 🔸 Data Governance in SME (Small Medium sized enterprises) can be modeled as a repeatable process that incrementally enhances your data governance maturity. 🔸 Identify sizable initiatives, ensure that they can be handled with a set amount of resources, and create metrics that enable you to track your progress. 🔸 You need to find ways to ensure observability and monitoring over time. 🔸 Don’t create something that you have no resources to maintain and improve going forward. 🔸 To identify the right initiatives at the right time, you need to ensure a close collaborating with your business users. 🔸 Ensure transparent and traceable ownership of the initiatives from the business side. 🔸 To create a movement and engagement in data requires continuous and structured communication. #DataMaturityAssessment 🔸 There is a need for speed and agility in SME, to ensure compatibility. 🔸 Data Maturity Assessments are a welcome introduction to ensure that you create a baseline when working with data. 🔸 There are advantages to both an internal view and to get some external perspective on your data maturity. 🔸 Results from a maturity assessment can be a reality check that is not always easy to convey, yet you need to be realistic. 🔸 It is good to start with cases that are understandable for business users, create interest, and can easy show value to leadership - this is what creates buy-in. 🔸 You need to ensure that you keep a clear communication towards bigger, more substantial tasks, so your resources are not limited to quick win actions. #DataStrategy 🔸 Data Strategy needs to be closely aligned with business strategy. 🔸 Have a clear vision of where you want to go. 🔸 To have a structure approach run our data strategy on how to handle both people, process, and technology is important for any work with data. 🔸 Technology is not the staring point, but rather a consequence of your strategic choices, your organizational setup and your available resources. 🔸 You need to include well-defined metrics to track progress. 🔸 Find metrics that are closely connected to business outcome and value creation. 🎧 👇 Data Management Association Norway (DAMA) Den norske dataforening (DND)

🎙 #MetaDAMA will be back with a new episode on Monday! May Lisbeth Øversveen, Head of Data & Insight at Eidsiva Bredbånd and our host Winfried Adalbert Etzel had a conversation about Data Strategy for mid-sized businesses. Here are some of the topics this episode sheds light on: 🔸 How to you lift a mid-sized organization beyond Excel? 🔸 How feasible is a Data Governance framework for mid-sized companies? 🔸 How to balance investment, resources, and goals? 🔸 What is the value of a Data Maturity Assessment? 🔸 Where to start, when trying to lift your organizations maturity? 🔸 Wht is Data Strategy important? 🔸 How can medium-sized companies get value from a Data Strategy? 🔸 How to you define and measure Return-of-Investment? And much more. 🎧 The episode will be online Monday morning.

💠 "Vectorizing data will be part of all common cloud data warehouses in the future." In our last episode of #MetaDAMA, Pedram Birounvand and Winfried Adalbert Etzel talked about the possibilities of AI, Vector databases, and RAG beyond its current use. Data Management as a profession has potential of advancement and scale by introducing new ways of working. The idea and identified need for automating Data Management as well as Vector Databases are already present in Gartner Hypecyle on Data Management. Pedram is connecting these to. And there are a couple good reasons here: 💡 #VectorDatabases provide semantic structure. 💡 Vector Databases store data through numerical representation. 💡 Vector Databases can due to the high-dimensional number of vectors represent structured, semi-structured and unstructured data. 💡 Vector Databases provide #vectorsearch functions that naturally return semantically similar terms. 💡 Vector search can ensure faster data retrieval due to the indexing possibilities of embeddings. 💡 Vectorizing data can potentially change semantic data modeling. 💡 The need for #datamodeling as a profession can be disrupted on the conceptual, semantic level. What do you think is the potential of Vector Databases for Data Management? Listen in to the episode here: https://lnkd.in/dgJdG2i9 Data Management Association Norway (DAMA) Den norske dataforening (DND)

«The notion of having clean data models will be less and less important going forward.» Unlock the secrets of the evolving data landscape with our guest, Pedram Birounvand, a veteran in data who has worked with notable companies like Spotify and in private equity. Pedram is CEO and Founder at UnionAll. Here are Winfried Adalbert Etzel's key takeaways: 🔹 When a new technology arrives, you need to adopt and figure out how to apply the new technology - often by using the new tools for the wrong problem. 🔹 There is substantial investment in AI, yet the use cases for applying AI are still not clear enough in many companies. 🔹 There is a gap I how we understand problems between technical and business people. Part of this problem is how we present and visualizer the problem. 🔹 You need to create space for innovation - if your team is bugged down with operational tasks, you are cannibalizing on innovative potential. 🔹 Incubators in organizations are valuable, if you can keep them close to the problem to solve without limiting their freedom to explore. 🔹 The goal of incubators is not to live forever, but top become ingrained in the business. 🔹 Find someone in the operational setting to take ownership from the start. 🔹 The more data you have to handle the better and clear should your Data Governance strategy be. 🔹 Small companies have it easier to set clear standards for data handling, due to direct communication. 🔹 You want to make sure that you solve one problem really well, before moving on. 🔹 Before intending to change, find out what the culture and the string incentives in your organization are. LLMs as the solution for Data Management? 🔸 ChatGP already today very good at classifying information. 🔸 It can create required documentation automatically, by feeding the right parameters. 🔸 It can supersede key value search in finding information. 🔸 This can help to scale Data Governance and Data Management work. 🔸 Data Management will become more automated, but also much more important going forward. 🔸 RAG architecture - first build up your own knowledge database, with the help of vectorizing the data into a Vector-database. 🔸 The results from querying this database are used by the LLM for interpretation. 🔸 Find a way to consolidate all your input information into a single pipeline to build your knowledge database. 🔸 Building strong controls on naming conventions will be less important going forward. 🔸 Vectorized semantic search will be much faster. 🔸 Entity matching will become very important. 🔸 Fact tables and dimensional tables become less important. Data to value 💎 Be able to benchmark your internal performance to the market understand trends and how they affect you. 💎 How to use and aggregate third party data is even harder than internal data. 💎 You need to find ways to combine internal and third party data to get better insights. 🎧 👇 Data Management Association Norway (DAMA) Den norske dataforening (DND)

On Monday CEO and founder of UnionAll, Pedram Birounvand will be our guest on #MetaDAMA. Pedram and Winfried Adalbert Etzel talked about something big: A Paradigm Shift in Data through AI! Here are some of the topics that are addressed: 👉 How to find better companies to invest in? 👉 How does tech-investment change from AI hype to value creation? 👉 What is the power of LLMs for data as a profession? 👉 How much work do we need to do to structure data, when you can find a needle in a haystack with LLMs? 👉 What does it mean to architecture, governance, data modeling? 👉 How does a Vector Database work? 👉 What is RAG? 👉 How can this help to turn "Data teams from cost center to profit center" And much more. Tune in on Monday! Data Management Association Norway (DAMA) Den norske dataforening (DND)

"Think about cloud security!" This was one of my tips and cloud migration pitfalls to avoid that I shared and discussed with Winfried during my recent episode at MetaDAMA podcast 🎙️https://lnkd.in/dgnXBg_n 🔗YouTube Short: https://lnkd.in/dy4iEz7N #cloudmigration #cloudmigrationpitfalls #cloudsecurity #cloudcomputing #azure

"Take time to do cost optimization and cost management on the cloud" This was one of my tips and cloud migration pitfalls to avoid that I shared and discussed with Winfried during my recent episode at MetaDAMA podcast 🎙️https://lnkd.in/dgnXBg_n 🔗YouTube Short: https://lnkd.in/du35Jhwg #cloudmigration #cloudmigrationpitfalls #costmanagement #cloudcomputing

"Don't move to the cloud without truly understanding what you are getting into! You need to be prepared." This was one of my tips and cloud migration pitfalls to avoid that I shared and discussed with Winfried during my recent episode at MetaDAMA podcast 🎙️https://lnkd.in/dgnXBg_n 🔗YouTube Short: https://lnkd.in/dNBZiui6 #cloudmigration #cloudmigrationpitfalls

«Don’t go over to the cloud without truly understanding what you are getting into.» Unlock the secrets of cloud migration with industry expert Jonah Andersson, a senior Azure consultant and Microsoft MVP from Sweden. Learn how to seamlessly transition your data systems to the cloud. Jonah shares her knowledge on #cloudinfrastructure, AI integration, and the balance between #EdgeAI and Cloud #AI, providing a comprehensive guide to building resilient cloud systems. Here are Winfried's key takeaways: ☁ Azure services can be tailored to use cases and service needs. But you need to understand your requirements and needs. ☁ Once you understand what you need to do, you need to gain perspective in the how - what methods and processes are supported? ☁ Think security at every step. ☁ #Security with integrations is an important part, we need to focus more on. ☁ Bringing different competencies together is a vital ingredient in building resilient applications. ☁ #Cloud is about where your data resides, how you protect it and how you handle big data. ☁ Cloud should support the entire data lifecycle. Cloud and AI 🤖 «Cloud computing is the backbone of AI.» 🤖 AI pushed for Edge AI, in addition to cloud. Reasons for Edge AI are latency, but mainly security. 🤖 Cloud can provide an attack surface for eg. data poisoning, lack of control for training data, etc. 🤖 AI tools can pose concerns on what and how you are exposing data. 🤖 Awareness and education are important, when building something with AI. 🤖 You need to at least understand your input to track your output - explainability starts with understanding of your data sources. 🤖 There is a risk to Model Governance by on-perm due to the level of competency needed. Multi-Cloud vs. Single Cloud 🚚 This is one of the questions to consider at the beginning of a cloud migration. 🚚 Drivers for multi cloud strategy are: - Avoiding proprietary vendor lock-in, - Existing applications or infrastructure in another platform, - Choosing according to the quality of services offered by cloud vendors. 🚚 If you choose multi cloud for automated resource management, you need to consider support platforms. #CloudMigration 🌥 Reason for cloud migration boil often down to gaining resiliency in the cloud, due to redundancy. 🌥 You need to uphold Data Quality not just after the migration but also during the transit. 🌥 Cloud migration requires strategy. 🌥 There are great resources to help with your cloud migration, like the Cloud Adaption framework or the Well-Architected framework. 🌥 Use observability and orchestration tools for your migration process. 🌥 Ensure you understand your cost, and can optimize it to fit with your needs. 🎧 👇 Data Management Association Norway (DAMA) Den norske dataforening (DND)

🎙️ My new podcast interview with MetaDAMA podcast by Winfried in Norway 🇳🇴 released today! 🎉 We discussed some interesting topics related to cloud migration, multicloud, hybrid cloud, Edge AI, security mindset, DaaS and a lot more! In this episode, I also shared my cloud migration journey that made me write my first book, Learning Microsoft Azure: Cloud Computing and Development Fundamentals (O'Reilly) 🔗 https://lnkd.in/da-h6dWm 🎧 Spotify 🔗 https://lnkd.in/dJNXdiUV 🎧 Buzzsprout 🔗 https://lnkd.in/dhm-eEjz 📖 Blog 🔗 https://lnkd.in/dZfvqy7e #cloudcomputing #cloudmigration #azure #podcastinterview