Podcast appearances and mentions of ahmed elsamadisi

Ahmed Elsamadisi, CEO & Co-Founder at Narrator, talks about how they are building an innovative data platform based on his own innovation of data schema (called Activity Schema). We talk about how he's come up with this brand new data modelling paradigm, how they're trying to build a business around this now open-sourced innovation, their customer acquisition strategy & lot more.The interview covers the following topics:The ways in which Narrator empowers data analysts in enterprises, offering quicker insights via the Activity Schema.Their journey to acquiring over 200 paying customers, including some prominent brands.Efforts to encourage data enthusiasts to amplify their innovation, fostering a ripple of positive online conversations.A glimpse into their current sales cycle.The intriguing "0 to 1" journey of Narrator.Insights into their team, funding trajectories, and a peek into their vision for the future.

Ahmed Elsamadisi is the founder and CEO of Narrator. Narrator enables companies to understand their customer, ask questions, and analyze data across all their systems from a single universal data model that grows with them. Ahmed started his career at Cornell's Autonomous Systems Laboratory building algorithms for autonomous vehicles and human-robot interaction. He then joined Raytheon to develop AI algorithms for missile defense, focusing on tracking and discrimination. In 2015, Ahmed joined WeWork as the first hire on their data team. He built their data engineering infrastructure and grew the team to forty data engineers and analysts. As WeWork grew, its data became difficult to maintain and the data team struggled to deliver work to stakeholders. It became impossible for the data team to maintain a single source of truth, consistent metrics, and delivery of quality analyses in a timely manner. Ahmed realized that a traditional data model designed for dashboards increases in complexity too quickly as a company scales. He prototyped a new kind of data model, one that would take advantage of a single time series table and allow analysts to get accurate data in minutes instead of weeks. From that experience, Ahmed founded Narrator to allow anyone to adopt this approach. Recently, Ahmed was recognized as one of Forbes' 30 under 30 for 2021 Connect with Jon Dwoskin: Twitter: @jdwoskin Facebook: https://www.facebook.com/jonathan.dwoskin Instagram: https://www.instagram.com/thejondwoskinexperience/ Website: https://jondwoskin.com/LinkedIn: https://www.linkedin.com/in/jondwoskin/ Email: jon@jondwoskin.com Get Jon's Book: The Think Big Movement: Grow your business big. Very Big!   Connect with Ahmed Elsamadisi: Website: https://www.narrator.ai/ Twitter: https://www.twitter.com/ae4ai LinkedIn: https://www.linkedin.com/in/elsamadisi/

Join Shane Gibson as he chats with Ahmed Elsamadisi on the Activity Schema Modeling pattern. You can get in touch with Ahmed via LinkedIn or over at https://www.narratordata.com/ If you want to read the transcript for the podcast head over to: https://agiledata.io/podcast/agiledata-podcast/the-patterns-of-activity-schema-with-ahmed-elsamadisi/#transcript   Listen to more podcasts on applying AgileData patterns over at https://agiledata.io/podcasts/ Read more on our AgileData Way of Working over at https://wow.agiledata.io/way-of-working/   If you want to join us on the next podcast, get in touch over at https://agiledata.io/podcasts/#contact   Or if you just want to talk about making magic happen with agile and data you can connect with Shane @shagility or Nigel @nigelvining on LinkedIn.   Subscribe: Apple Podcast | Spotify | Google Podcast  | Amazon Audible | TuneIn | iHeartRadio | PlayerFM | Listen Notes | Podchaser |    Simply Magical Data

Ahmed Elsamadisi is the founder and CEO of Narrator. Narrator enables companies to understand their customer, ask questions, and analyze data across all their systems from a single universal data model that grows with them. Ahmed started his career at Cornell's Autonomous Systems Laboratory building algorithms for autonomous vehicles and human-robot interaction. He then joined Raytheon to develop AI algorithms for missile defense, focusing on tracking and discrimination. In 2015, Ahmed joined WeWork as the first hire on their data team. He built their data engineering infrastructure and grew the team to forty data engineers and analysts. As WeWork grew, its data became difficult to maintain and the data team struggled to deliver work to stakeholders. It became impossible for the data team to maintain a single source of truth, consistent metrics, and delivery of quality analyses in a timely manner. Ahmed realized that a traditional data model designed for dashboards increases in complexity too quickly as a company scales. He prototyped a new kind of data model, one that would take advantage of a single time series table and allow analysts to get accurate data in minutes instead of weeks. From that experience, Ahmed founded Narrator to allow anyone to adopt this approach. Recently, Ahmed was recognized as one of Forbes' 30 under 30 for 2021 Connect with Jon Dwoskin: Twitter: @jdwoskin Facebook: https://www.facebook.com/jonathan.dwoskin Instagram: https://www.instagram.com/thejondwoskinexperience/ Website: https://jondwoskin.com/LinkedIn: https://www.linkedin.com/in/jondwoskin/ Email: jon@jondwoskin.com Get Jon's Book: The Think Big Movement: Grow your business big. Very Big!   Connect with Ahmed Elsamadisi: Website: https://www.narrator.ai/ Twitter: https://www.twitter.com/ae4ai LinkedIn: https://www.linkedin.com/in/elsamadisi/

Ahmed Elsamadisi is the founder and CEO of Narrator, a data modeling platform that allows data teams to answer questions and make business-critical decisions in minutes focusing on data analysis, engineering, and science. Guiding you to make the best decision, and ensuring the data is accurate, how to assist you in formulating the appropriate inquiries, and how influencing you to provide the appropriate responses. They help you understand the analysis and get you to take action based on it. Focusing on the psychology, the human aspect, and the data aspect, and all of it seamlessly come together to create an amazing experience.Ahmed explains that data is information and information can be used to make things better. From a marketing background, you would want to know which ad source is bringing consumers to our website and which ad source is keeping them there. The idea of making big decisions with data is not looking at individual customers, but seeing how people behave and what gets your customer to make the decisions they want. It's about you getting more detailed in making a more specific decision that affects your customers.It starts with the question that you're asking and then figuring out how to get there. If you are thinking about investing your time in getting more women or getting more elderly, for instance, Ahmed will tell you the conversion rates and give you a scale of where to dedicate your energy. All good data starts with a good question and a good question leads to a good analysis, which leads to a good decision. You must first have correct and accurate data that you trust and then get down to the individual customer journeys. When they built Narrator, the idea was to build something you can trust and understand, something that makes sense and has an intuitive nature.When you're using tools like Facebook Ad Manager and Google Ad Manager, they are lying to you. They're incentivized for you to give them money. Be aware of the fact that all these different tools are very misleading. Words are very misleading, especially since Facebook is notoriously been sued every single year for lying about its metrics or using words that are deliberately misleading. At Narrator, they try to nudge you into being very clear about your question and building a tool that enables you to get that clarity in the questions and in the answers.The Narrator standardizes all data as one of its functions. Being able to reason about data by having it in a consistent format with common assumptions. Some factors that could go and mess up your data and AI, causing you to have inconclusive results are bad Al algorithms. Ahmed explains what's happening in the industry now, that everyone is shoving in machine learning models and hoping it sticks out. The machine learning model is being trained and it's not understandable. When AI makes a decision; a human being cannot evaluate whether it makes sense or not. The AI then behaves badly, at which point they need to go and train it again. This represents a failure of the data team as well as data science. You have to do good data analysis and use suitable data algorithms in order to base your conclusions on what you are learning. In this episode:[01:46] Ahmed explains how Narrator, a data modeling platform works The Narrator is not just a data platform but helps and guides you to make the best decisions Asking the right question to understand the analysisIn this episode:[06:11] Seeing how data is color coding and ordering an Excel sheetPrioritizing what's...

In this episode, Ahmed Elsamadisi, founder and CEO of Narrator, shares how to use a data narrative to interpret and tell a meaningful story with your data. You'll learn: - Two problems with data analysis - What causes data discrepancy - What a data narrative is - How to interpret and tell a meaningful story with data

Leave a comment or a question for Ahmed or Ton This podcast interview focuses on product innovation that has the power to answer any question in minutes. My guest is Ahmed Elsamadisi, CEO of Narrator. Ahmed started his career at Cornell's Autonomous Systems Laboratory, building algorithms for autonomous vehicles and human-robot interaction. He then joined Raytheon to develop AI algorithms for missile defense, focusing on tracking and discrimination. In 2015, Ahmed joined WeWork as the first hire on their data team. He built their data engineering infrastructure and grew the team to forty data engineers and analysts. As WeWork grew, its data became difficult to maintain, and the data team struggled to deliver work to stakeholders. Ahmed realized that a traditional data model designed for dashboards increases in complexity too quickly as a company scales. And that sparked the idea of the founding of Narrator in 2017. It powers self-service analytics across all company data. It's on a mission to enable anyone to get answers in minutes instead of weeks.  And this inspired me, and hence I invited Ahmed to my podcast. We explore what's broken in the world of getting answers and how today's technology is holding us back. Ahmed is sharing his vision about the platform that he's creating to ask any question and have it answered in record time. He shares his big lessons in building a product designed to solve a problem that was perceived as impossible to solve. He digs into the messaging challenges he had to overcome to create predictable traction. Lastly, he shares how his drive to create something that's remembered and makes an impact serves everyone well: his customers, his employees, his business, and his investors.  Here is one of his quotes We started with a goal, but we had no idea about the implementation. And the goal was to ask the questions and give answers. And one of the things that I hated about the answers that we gave today was answers that are given in the form of dashboards. Dashboards are, I think, the worst way to communicate anything.  So how did we solve this problem before? And the answer was stories. Everyone who reads a story is able to understand. So I knew that whatever Narrative had to output when you are answering questions, we should be pushing people to create stories so people's opinions, people's thoughts, and people's thinking process is shared. Because sharing a chart doesn't mean anything, but sharing a story sharing your thinking, and sharing your process is key. During this interview, you will learn four things: That you're off on building something remarkable when everyone thinks it's impossible …..until it's not That by looking at how we solved problems in ancient times can give you the answers to instantly turn customers into fans today That the way to explain your solution most clearly is to have your fans do it That what makes you a good company is not what makes you a good investment. For more information about the guest from this week: Ahmed Elsamadisi Website Narrator AI Leave a comment or a question for Ahmed or Ton Subscribe to the Daily Value Inspiration Get my free, 2 min daily reflection on shaping a B2B SaaS business no one can ignore. Subscribe here Learn more about your ad choices. Visit megaphone.fm/adchoices

Ahmed Elsamadisi is the founder and CEO of Narrator. Narrator enables companies to understand their customer, ask questions, and analyze data across all their systems from a single universal data model that grows with them. Ahmed started his career at Cornell's Autonomous Systems Laboratory building algorithms for autonomous vehicles and human-robot interaction. He then joined Raytheon to develop AI algorithms for missile defense, focusing on tracking and discrimination. In 2015, Ahmed joined WeWork as the first hire on their data team. He built their data engineering infrastructure and grew the team to forty data engineers and analysts. As WeWork grew, its data became difficult to maintain and the data team struggled to deliver work to stakeholders. It became impossible for the data team to maintain a single source of truth, consistent metrics, and delivery of quality analyses in a timely manner. Ahmed realized that a traditional data model designed for dashboards increases in complexity too quickly as a company scales. He prototyped a new kind of data model, one that would take advantage of a single time series table and allow analysts to get accurate data in minutes instead of weeks. From that experience, Ahmed founded Narrator to allow anyone to adopt this approach. Recently, Ahmed was recognized as one of Forbes' 30 under 30 for 2021 Connect with Jon Dwoskin: Twitter: @jdwoskin Facebook: https://www.facebook.com/jonathan.dwoskin Instagram: https://www.instagram.com/thejondwoskinexperience/ Website: https://jondwoskin.com/LinkedIn: https://www.linkedin.com/in/jondwoskin/ Email: jon@jondwoskin.com Get Jon's Book: The Think Big Movement: Grow your business big. Very Big!   Connect with Ahmed Elsamadisi: Website: https://www.narrator.ai/ Twitter: https://www.twitter.com/ae4ai LinkedIn: https://www.linkedin.com/in/elsamadisi/

There's a 99.9% chance you have, or you currently are, analysing and interpreting your data, really. As we all know, data is very valuable and can really empower entrepreneurs and businesses to make the right decisions and formulate the right strategies, if interpreted and analysed correctly. In this episode, Ahmed Elsamadisi, CEO of Narrator.ai, narrates how Narrator.ai works and how it helps entrepreneurs view and analyse their data in a completely different and efficient way.Ahmed also shares the most common pitfalls that entrepreneurs get into with data, and how Narrator.ai can help you avoid that or get you out of that hole. He also shares how data can empower you to create better decisions and strategies, and how their tool can help you make these decisions as well through the prescriptions that Narrator.ai. And lastly, how Narrator.ai's magic creates its own magic of getting noticed.Get Otter with 1-month FREE Pro LiteGenerate rich notes for meetings, interviews, lectures, and other important voice conversations.Graphic design toolbox - VismeCreate visual brand experiences for your business whether you are a pro designer or a total novice.Build responsive quizzesGenerate higher quality, higher converting leadsVidyard - Use Video In Your EmailsVidyard is the easiest way to record and send videos that build personalPost-production, transcript and show notes by XCD Virtual Assistants Support the show

There's a 99.9% chance you have, or you currently are, analysing and interpreting your data, really. As we all know, data is very valuable and can really empower entrepreneurs and businesses to make the right decisions and formulate the right strategies, if interpreted and analysed correctly. In this episode, Ahmed Elsamadisi, CEO of Narrator.ai, narrates how Narrator.ai works and how it helps entrepreneurs view and analyse their data in a completely different and efficient way.Ahmed also shares the most common pitfalls that entrepreneurs get into with data, and how Narrator.ai can help you avoid that or get you out of that hole. He also shares how data can empower you to create better decisions and strategies, and how their tool can help you make these decisions as well through the prescriptions that Narrator.ai. And lastly, how Narrator.ai's magic creates its own magic of getting noticed.Get Otter with 1-month FREE Pro LiteGenerate rich notes for meetings, interviews, lectures, and other important voice conversations.Graphic design toolbox - VismeCreate visual brand experiences for your business whether you are a pro designer or a total novice.Build responsive quizzesGenerate higher quality, higher converting leadsVidyard - Use Video In Your EmailsVidyard is the easiest way to record and send videos that build personalPost-production, transcript and show notes by XCD Virtual Assistants Support the show

Ahmed Elsamadisi of Narrator.ai joins us in this episode to share how they are solving the data problems of all startups and tech companies using a very easy-to-use product. Ahmed will share his previous hustle working as a dev in WeWork and how they were able to grow fast and solve problems even though they were using fragmented data points. He will also share what triggered him to create Narrator because of the need to create a functional Business Intelligence tool that is easy to use despite the many data sources startups use. Ahmed will also share the grit it took to get Narrator to where it is today despite the years of having no functional product and getting pressure from investors and almost running out of runway.This episode is brought to you by PDAX. Join PDAX here: podlink.co/hustlesharepdaxFor show notes, go to hustleshare.comHustleshare is powered by Podmachine Hosted on Acast. See acast.com/privacy for more information.

Ahmed Elsamadisi built the data infrastructure at WeWork before realizing every company could benefit from his team's innovation. Traditional star schemas aren't the best way to manage data. Ahmed instead pioneered a new approach using a single-table column model better suited for real questions people ask. He launched Narrator in 2017 to make it easier to turn data questions into answers and has since raised $6.2M from Initialized Capital, Flybridge Capital Partners, and Y Combinator. Ahmed received his BS in Robotics from Cornell. Hear from a pioneer (and tech provocateur) how new data wrangling techniques are making it easier for mere mortals to get more value out of their data.Listen and learn…How a roboticist who got his start building self-driving cars and designing missile defense systems ended up redefining how data is storedWhy traditional approaches that require SQL to access data are brokenHow a single-column schema eliminates the complexity of joining systems and tablesWhy it's easier to tell better stories with data using temporal relationships extracted from customer journeysWhy Snowflake, Redshift, and BigQuery are really all the same… and data modeling is the place to innovate What it means to replace traditional tables with activities… and why they'll eliminate the need for specialized data analysts How to reduce data storage costs by 90% and time to generate data insights from weeks to minutes Why data management vendors are responsible for bad decisions made using your data What is data cleaning and how you should do it What is a racist algorithm Why querying data with natural language will never work Is the WeCrashed version of Adam Neumann's neuroticism accurate? Hear from someone who lived it... References in this episode:Google's LaMDA isn't sentientChandra Khatri from Got It AI on AI and the Future of Work Derek Steer from Mode on AI and the Future of Work Barr Moses from Monte Carlo on AI and the Future of Work Peter Fishman from Mozart Data on AI and the Future of Work Ahmed on Twitter 

This episode was amazing. I spoke with Ahmed Elsamadisi, founder and CEO of Narrator.ai, about data prep and cleaning prior to sending your model to production, and the importance of data preparation. We tend to forget about the process it takes to get accurate results and decision-making from your data. Ahmed breaks it all down for us and discusses how Narrator.ai plays a huge role in the data science industry.

Ahmed is the founder and CEO of Narrator. Narrator enables companies to understand their customer, ask questions, and analyze data across all their systems from a single universal data model that grows with them. Guest Bio Ahmed started his career at Cornell's Autonomous Systems Laboratory building algorithms for autonomous vehicles and human-robot interaction. He then joined … Focusing as a founder, AI, DATA, hiring, onboarding, dealing with going to zero, building MVPs, & more w/ Ahmed Elsamadisi CEO Narrator AI #135 Read More »

Ahmed and Brandon talk about how to set up your data stack so you can answer questions like "What three things happen in our customer's journey that leads to customers with the highest LTV". About Ahmed Elsamadisi Ahmed Elsamadisi is the Founder and CEO of Narrator.ai, a data modeling platform allowing companies to make better business decisions with their data. He started his career at Cornell's Autonomous Systems Laboratory building algorithms for autonomous vehicles and human-robot interaction. He then joined Raytheon to develop AI algorithms for missile defense, focusing on tracking and discrimination. In 2015, Ahmed joined WeWork as the first hire on their data team. He built their data engineering infrastructure and grew the team to forty data engineers and analysts. Since staring Narrator Ahmed has graduated the from the startup accelerator Y Combinator in 2017 and was named in Forbes's 30 under 30 list of 2021. SIGN UP FOR OUR NEWSLETTER HERE!Over 17,200 listeners and countinghttps://edge.ck.page/bea5b3fda6 EPISODE LINKS: Narrator AIhttps://www.narrator.ai RESOURCE LINKS: How to Write a Business Plan in 13 easy to Build Slides. FREE 30+ page ebook https://www.buildabusiness.io/guide-to-building-the-perfect-business-plan1600276207655 EDGE PODCAST INFO: Apple Podcasts https://podcasts.apple.com/us/podcast/edge/id1522407349 Spotify https://open.spotify.com/show/7a3WcnSn9PlvwwF5hn4p4S YouTube Channel: https://www.youtube.com/channel/UCabV9Rcw4MohWvTGr3OTzFw Website https://MyEDGEPodcast.com RSS Feed https://buildabusinesssuccesssecrets.libsyn.com/rss SUPPORT & CONNECT EDGE NEWSLETTEROver 17,200 listeners and countinghttps://edge.ck.page/bea5b3fda6 Please Support this Podcast by checking out our Sponsors: Mad River Botanicals 100% certified organic CBD products. The product is controlled from seed to end product by it's owners. Use code: EDGE22 to get 10% off all your orders. Shop now https://madriverbotanicals.com/?ref=18 EDGE Podcast. A top podcast for entrepreneurs! https://myedgepodcast.com

In this highly entertaining and educational episode of David Vs Goliath Adam DeGraide interviews Ahmed about his company Natural AI. This spicy interview is loaded with tips, tricks and things that every business owner and aspiring entrepreneur needs to to be successful. Brought to you by https://automatemysocial.com and https://anthemsoftware.com . Enjoy! --- Send in a voice message: https://anchor.fm/david-vs-goliath/message

In this highly entertaining and educational episode of David Vs Goliath Adam DeGraide interviews Ahmed about his company Natural AI. This spicy interview is loaded with tips, tricks and things that every business owner and aspiring entrepreneur needs to to be successful. Brought to you by https://automatemysocial.com and https://anthemsoftware.com . Enjoy! --- Send in a voice message: https://anchor.fm/david-vs-goliath/message

How do companies make decisions? Data certainly don't make decisions, nor do analytics, nor do the computers they run on. Human begins make decisions — the human factor is crucial. Subjectivism is paramount, even in the age of big data and A.I. The key still lies with the people who are interacting with the data to generate human insights. Ahmed Elsamadisi is one of the leading data scientists in the world. He's worked on self-driving cars and nuclear defense and some of the biggest business challenges on earth. He believes that it is the stories we tell from data that drive business success. We are privileged to interview him at Economics For Business podcast, and he gave us a lot of useful advice we can all use every day in managing our businesses. Key Takeaways and Actionable Insights The data community has made data and algorithmic analysis far too complex, to the point where it's no longer useful for business. The path-dependent route to today's complex data tables was paved with lots and lots of columns and lots and lots of rows. These data tables are leftovers from the early days of computing SQL language was designed to manipulate these rows and columns. A.I. comes along and can analyze all the possible combinations of data cells. Business executives ask their data departments to generate a lot of these combinations to search for patterns. It often takes a long time, a lot of revisions, and generates no clear answers. Another aspect of history is the use of dashboards. We tend to design dashboards rather than formulate good business questions. The metrics on dashboards are sometimes useful for operations but they're often not at all useful for understanding the causal connections between data points. Consequently, different people can interpret them in different ways and there is no consensus as to what they mean and what to do about it. The purpose of data analytics is to generate good decisions that lead to action. The entrepreneurial method drives towards D and A: decisions and actions. Analytics should help to formulate the hypotheses on which to base decisions. The problem with complex dashboards and algorithmic pattern recognition is that they often don't give clear direction on recommended action, especially when the interpretation varies depending on who is doing the interpreting. Ahmed's experience is that sharing a numerical dashboard with 10 executives is very likely to result in 10 different interpretations, and the resultant confusion and disagreement freezes action rather than accelerating it. We need data to tell us stories that we can all rally around. The most powerful tool for developing consensus around action is narrative — often called storytelling. While 10 dashboard interpretations might lead to 10 different action plans, a single well-told story can align everyone who hears it, understands it, and internalizes it. We heard about the power of narrative in episode #181 (Mises.org/E4B_181) in which Brian Rivera explained the role of storytelling and sensemaking in The Flow System of management, and in episode #152 (Mises.org/E4B_152) where Derek and Laura Cabrera explained the power of aligned mental models for driving business. Stories achieve alignment. Ahmed Elsamadisi built his service, narrator.ai, to output data analytics in the form of a story. The complexity riddle is removed and replaced with a narrative that all executives, not just data scientists, can understand. Narrator.ai re-integrates data science with the all-important human element of understanding stories. The way to get data to tell stories is with a conversation. Ahmed says that the way we ask questions (data queries) is flawed. It's quite a normal practice to set the A.I. to search the data tables to look for patterns to see if anything interesting emerges. This is what Ahmed calls “lazy hypothesis generation”, which is never going to yield useful actionable insights (yet many big analytics companies are taking in huge customer revenues for just this service). Clients may claim to be making data-driven decisions but that's mis-characterizing this business behavior, typical though it may be. Ahmed advises us to think more in terms of a conversation with data. To facilitate this, he has developed a universal data model with just three variables: an entity (such as a customer), an action, and time. Every business question is about a customer taking some action in some time period. The universal data model enables the conversation: what action did the customer take in what period of time, e.g., when did they open the email and what action did they take after opening it. This is not a database query, it's a more thoughtful question about the customer experience and how to understand it. Ahmed told us that training customers in this conversational mode of interaction with the universal data model results in a cultural shift in thinking. The conversation can go back and forth in several iterations until the understanding is fully honed. Clients hear the data talking to them through the stories that narrator.ai generates. The have deeper insights and a story to share to form a consensus around the action that the story suggests. Narrator.ai clients have used stories for everything from describing new product specs to updating board decks. Great conversations with data are based on empathy and thinking about the customer experience. At Economics For Business, we elevate customer empathy a the most important business skill, in the context of an understanding of customer value as subjective, a good feeling from an enjoyable or satisfying experience. Ahmed advises us to think in this same way when formulating conversations with data to generate insights. If we think about the customer's experience, desired and actual, and the actions they take before and after that experience, and the time context of the experience, we'll do well in formulating good questions. The action component of the universal data model is central to the Austrian deductive method: knowing what people do can help us deduce motivation and expectation. Knowing what they did next can shed light on the ends they had in mind. Actions like opening e-mails or repeat buying are also revealing of intent and expectations. The more we converse with the data, the more insight we can gain. Storytelling with data is another implementation of subjective quantification — with the benefit of enhanced intuition over time. In episode #176 (Mises.org/E4B_176), Peter Lewin introduced us to the Austrian concept of subjective quantification — turning customers subjective valuations into numbers such as capital value on a balance sheet. We tested the subjective quantification term with Ahmed, and he endorsed it — with a major addition. It's important to include the dimension of time. If, over time, we have better and better conversations with data and formulate better questions and hypotheses, we'll get better and better at generating insights. Our intuition will improve. We'll get a better “feel” for the data. Even our empathy can become more accurate. Additional Resources Narrator.ai and its excellent blog, Narrator.ai/Blog "Top Ten Signs You Have A Data Modeling Problem": Mises.org/E4B_183_Blog Ahmed Elsamadisi on LinkedIn: Mises.org/E4B_183_LinkedIn

How do companies make decisions? Data certainly don't make decisions, nor do analytics, nor do the computers they run on. Human begins make decisions — the human factor is crucial. Subjectivism is paramount, even in the age of big data and A.I. The key still lies with the people who are interacting with the data to generate human insights. Ahmed Elsamadisi is one of the leading data scientists in the world. He's worked on self-driving cars and nuclear defense and some of the biggest business challenges on earth. He believes that it is the stories we tell from data that drive business success. We are privileged to interview him at Economics For Business podcast, and he gave us a lot of useful advice we can all use every day in managing our businesses. Key Takeaways and Actionable Insights The data community has made data and algorithmic analysis far too complex, to the point where it's no longer useful for business. The path-dependent route to today's complex data tables was paved with lots and lots of columns and lots and lots of rows. These data tables are leftovers from the early days of computing SQL language was designed to manipulate these rows and columns. A.I. comes along and can analyze all the possible combinations of data cells. Business executives ask their data departments to generate a lot of these combinations to search for patterns. It often takes a long time, a lot of revisions, and generates no clear answers. Another aspect of history is the use of dashboards. We tend to design dashboards rather than formulate good business questions. The metrics on dashboards are sometimes useful for operations but they're often not at all useful for understanding the causal connections between data points. Consequently, different people can interpret them in different ways and there is no consensus as to what they mean and what to do about it. The purpose of data analytics is to generate good decisions that lead to action. The entrepreneurial method drives towards D and A: decisions and actions. Analytics should help to formulate the hypotheses on which to base decisions. The problem with complex dashboards and algorithmic pattern recognition is that they often don't give clear direction on recommended action, especially when the interpretation varies depending on who is doing the interpreting. Ahmed's experience is that sharing a numerical dashboard with 10 executives is very likely to result in 10 different interpretations, and the resultant confusion and disagreement freezes action rather than accelerating it. We need data to tell us stories that we can all rally around. The most powerful tool for developing consensus around action is narrative — often called storytelling. While 10 dashboard interpretations might lead to 10 different action plans, a single well-told story can align everyone who hears it, understands it, and internalizes it. We heard about the power of narrative in episode #181 (Mises.org/E4B_181) in which Brian Rivera explained the role of storytelling and sensemaking in The Flow System of management, and in episode #152 (Mises.org/E4B_152) where Derek and Laura Cabrera explained the power of aligned mental models for driving business. Stories achieve alignment. Ahmed Elsamadisi built his service, narrator.ai, to output data analytics in the form of a story. The complexity riddle is removed and replaced with a narrative that all executives, not just data scientists, can understand. Narrator.ai re-integrates data science with the all-important human element of understanding stories. The way to get data to tell stories is with a conversation. Ahmed says that the way we ask questions (data queries) is flawed. It's quite a normal practice to set the A.I. to search the data tables to look for patterns to see if anything interesting emerges. This is what Ahmed calls “lazy hypothesis generation”, which is never going to yield useful actionable insights (yet many big analytics companies are taking in huge customer revenues for just this service). Clients may claim to be making data-driven decisions but that's mis-characterizing this business behavior, typical though it may be. Ahmed advises us to think more in terms of a conversation with data. To facilitate this, he has developed a universal data model with just three variables: an entity (such as a customer), an action, and time. Every business question is about a customer taking some action in some time period. The universal data model enables the conversation: what action did the customer take in what period of time, e.g., when did they open the email and what action did they take after opening it. This is not a database query, it's a more thoughtful question about the customer experience and how to understand it. Ahmed told us that training customers in this conversational mode of interaction with the universal data model results in a cultural shift in thinking. The conversation can go back and forth in several iterations until the understanding is fully honed. Clients hear the data talking to them through the stories that narrator.ai generates. The have deeper insights and a story to share to form a consensus around the action that the story suggests. Narrator.ai clients have used stories for everything from describing new product specs to updating board decks. Great conversations with data are based on empathy and thinking about the customer experience. At Economics For Business, we elevate customer empathy a the most important business skill, in the context of an understanding of customer value as subjective, a good feeling from an enjoyable or satisfying experience. Ahmed advises us to think in this same way when formulating conversations with data to generate insights. If we think about the customer's experience, desired and actual, and the actions they take before and after that experience, and the time context of the experience, we'll do well in formulating good questions. The action component of the universal data model is central to the Austrian deductive method: knowing what people do can help us deduce motivation and expectation. Knowing what they did next can shed light on the ends they had in mind. Actions like opening e-mails or repeat buying are also revealing of intent and expectations. The more we converse with the data, the more insight we can gain. Storytelling with data is another implementation of subjective quantification — with the benefit of enhanced intuition over time. In episode #176 (Mises.org/E4B_176), Peter Lewin introduced us to the Austrian concept of subjective quantification — turning customers subjective valuations into numbers such as capital value on a balance sheet. We tested the subjective quantification term with Ahmed, and he endorsed it — with a major addition. It's important to include the dimension of time. If, over time, we have better and better conversations with data and formulate better questions and hypotheses, we'll get better and better at generating insights. Our intuition will improve. We'll get a better “feel” for the data. Even our empathy can become more accurate. Additional Resources Narrator.ai and its excellent blog, Narrator.ai/Blog "Top Ten Signs You Have A Data Modeling Problem": Mises.org/E4B_183_Blog Ahmed Elsamadisi on LinkedIn: Mises.org/E4B_183_LinkedIn

How do companies make decisions? Data certainly don't make decisions, nor do analytics, nor do the computers they run on. Human begins make decisions — the human factor is crucial. Subjectivism is paramount, even in the age of big data and A.I. The key still lies with the people who are interacting with the data to generate human insights. Ahmed Elsamadisi is one of the leading data scientists in the world. He's worked on self-driving cars and nuclear defense and some of the biggest business challenges on earth. He believes that it is the stories we tell from data that drive business success. We are privileged to interview him at Economics For Business podcast, and he gave us a lot of useful advice we can all use every day in managing our businesses. Key Takeaways and Actionable Insights The data community has made data and algorithmic analysis far too complex, to the point where it's no longer useful for business. The path-dependent route to today's complex data tables was paved with lots and lots of columns and lots and lots of rows. These data tables are leftovers from the early days of computing SQL language was designed to manipulate these rows and columns. A.I. comes along and can analyze all the possible combinations of data cells. Business executives ask their data departments to generate a lot of these combinations to search for patterns. It often takes a long time, a lot of revisions, and generates no clear answers. Another aspect of history is the use of dashboards. We tend to design dashboards rather than formulate good business questions. The metrics on dashboards are sometimes useful for operations but they're often not at all useful for understanding the causal connections between data points. Consequently, different people can interpret them in different ways and there is no consensus as to what they mean and what to do about it. The purpose of data analytics is to generate good decisions that lead to action. The entrepreneurial method drives towards D and A: decisions and actions. Analytics should help to formulate the hypotheses on which to base decisions. The problem with complex dashboards and algorithmic pattern recognition is that they often don't give clear direction on recommended action, especially when the interpretation varies depending on who is doing the interpreting. Ahmed's experience is that sharing a numerical dashboard with 10 executives is very likely to result in 10 different interpretations, and the resultant confusion and disagreement freezes action rather than accelerating it. We need data to tell us stories that we can all rally around. The most powerful tool for developing consensus around action is narrative — often called storytelling. While 10 dashboard interpretations might lead to 10 different action plans, a single well-told story can align everyone who hears it, understands it, and internalizes it. We heard about the power of narrative in episode #181 (Mises.org/E4B_181) in which Brian Rivera explained the role of storytelling and sensemaking in The Flow System of management, and in episode #152 (Mises.org/E4B_152) where Derek and Laura Cabrera explained the power of aligned mental models for driving business. Stories achieve alignment. Ahmed Elsamadisi built his service, narrator.ai, to output data analytics in the form of a story. The complexity riddle is removed and replaced with a narrative that all executives, not just data scientists, can understand. Narrator.ai re-integrates data science with the all-important human element of understanding stories. The way to get data to tell stories is with a conversation. Ahmed says that the way we ask questions (data queries) is flawed. It's quite a normal practice to set the A.I. to search the data tables to look for patterns to see if anything interesting emerges. This is what Ahmed calls “lazy hypothesis generation”, which is never going to yield useful actionable insights (yet many big analytics companies are taking in huge customer revenues for just this service). Clients may claim to be making data-driven decisions but that's mis-characterizing this business behavior, typical though it may be. Ahmed advises us to think more in terms of a conversation with data. To facilitate this, he has developed a universal data model with just three variables: an entity (such as a customer), an action, and time. Every business question is about a customer taking some action in some time period. The universal data model enables the conversation: what action did the customer take in what period of time, e.g., when did they open the email and what action did they take after opening it. This is not a database query, it's a more thoughtful question about the customer experience and how to understand it. Ahmed told us that training customers in this conversational mode of interaction with the universal data model results in a cultural shift in thinking. The conversation can go back and forth in several iterations until the understanding is fully honed. Clients hear the data talking to them through the stories that narrator.ai generates. The have deeper insights and a story to share to form a consensus around the action that the story suggests. Narrator.ai clients have used stories for everything from describing new product specs to updating board decks. Great conversations with data are based on empathy and thinking about the customer experience. At Economics For Business, we elevate customer empathy a the most important business skill, in the context of an understanding of customer value as subjective, a good feeling from an enjoyable or satisfying experience. Ahmed advises us to think in this same way when formulating conversations with data to generate insights. If we think about the customer's experience, desired and actual, and the actions they take before and after that experience, and the time context of the experience, we'll do well in formulating good questions. The action component of the universal data model is central to the Austrian deductive method: knowing what people do can help us deduce motivation and expectation. Knowing what they did next can shed light on the ends they had in mind. Actions like opening e-mails or repeat buying are also revealing of intent and expectations. The more we converse with the data, the more insight we can gain. Storytelling with data is another implementation of subjective quantification — with the benefit of enhanced intuition over time. In episode #176 (Mises.org/E4B_176), Peter Lewin introduced us to the Austrian concept of subjective quantification — turning customers subjective valuations into numbers such as capital value on a balance sheet. We tested the subjective quantification term with Ahmed, and he endorsed it — with a major addition. It's important to include the dimension of time. If, over time, we have better and better conversations with data and formulate better questions and hypotheses, we'll get better and better at generating insights. Our intuition will improve. We'll get a better “feel” for the data. Even our empathy can become more accurate. Additional Resources Narrator.ai and its excellent blog, Narrator.ai/blog "Top Ten Signs You Have A Data Modeling Problem": Mises.org/E4B_183_Blog Ahmed Elsamadisi on LinkedIn: Mises.org/E4B_183_LinkedIn

Is marketing data management too complex, or is it marketed to marketers that way? We dive into deriving insights from digital advertising metrics in this interview with Ahmed Elsamadisi and learn how constraints and predictability can be your key to unlocking the secrets of marketing data. SHOWPAGE - www.ninjacat.io/blog/mastering-marketing-and-advertising-analytics  © 2022, NinjaCat

Highlights from this week's conversation include:Ahmed's background and career journey (2:27)Why the modern data stack “sucks” (4:53)The limitations of progress (9:13)Showing data with only 11 columns (11:55)Managing one table that rules them all (19:02)Viewing the world as timestamped activities (32:40)When this model becomes harder to use (35:15)The two parts you need in a company (44:41)Those who use Narrator (48:32)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we'll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

Ahmed Elsamadisi is the Founder and CTO at Narrator.ai, a data modeling platform that allows data teams to answer any and all data questions within minutes. He is a passionate and driven entrepreneur who began to obsess over how humans and robots make decisions…. Which led him to launch this amazing company which is solving big problems for businesses today.Before Narrator, Ahmed joined WeWork as the first hire on their data team. In just four years since the founding of Narrator, Ahmed graduated from startup accelerator Y Combinator and was named a member of the Forbes 30 Under 30 list for 2021.Check out this episode to hear more about:Why finding the right team is critical to your successHow you can gain funding for your startup by selling “the dream”The key difference between building different or building better and how it affects your approach to growing a startup (and funding it!)Connect with your host on Instagram at @shauna.armitage and listen to more Startup Renegade stories at www.startuprenegades.com

Eric and Kostas preview their upcoming episode with Ahmed Elsamadisi of Narrator AI.

Turning data into decisions for growth and traction is where many startups stumble.Our guest, Ahmed Elsamadisi, is the Founder and CEO of Narrator.ai, an innovative platform allowing companies better and quicker access to their critically important data. Before Narrator, Ahmed was the first member of the data team at WeWork, a team he helped grow to over 40 people. He has also worked as an AI engineer for missile defense systems as well as for self-driving cars. Narrator allows companies to answer questions about their data in just minutes instead of weeks, using a single 11-column table. Since its founding in 2017, Narrator has helped dozens of companies and graduated from startup accelerator Y Combinator.To learn more about Narrator, please visit: https://www.narrator.ai/Follow and connect with Ahmed and Narrator on social media here:LinkedIn: https://www.linkedin.com/in/elsamadisi/ and https://www.linkedin.com/company/narratorai/Twitter: https://twitter.com/ae4ai and https://twitter.com/narratorai https://www.narrator.ai/ Thank you for carving out time to improve your Founder Game - when you do better, your business will do better - cheers!Ande ♥https://andelyons.com#bestpodcastforstartups #knowyourdata #growyourbusinesswithdata00:00 - Andelicious Announcements - accelerators; pitch events; founder opportunities08:00 - Meet Ahmed Elsamadisi - Founder & CEO of Narrator14:20 - I don't care about the data, I care about making better decisions27:10 - VC funding advice you rarely hear33:50 - Pitching to Y Combinator VCs43:25 - how founders can avoid getting lost in data, resulting in poor decisions52:55 - If you have found purpose and you're doing it every day - you are crushing it! Stitch That On A Pillow!55:00 - how Narrator has changed company cultures by helping them ask better, smarter questions58:00 - how entrepreneurship has changed Ahmed's life for the betterCONNECT WITH ME ONLINE: https://andelyons.com https://twitter.com/AndeLyonshttps://www.facebook.com/StartupLifew... https://www.linkedin.com/in/andelyons/ https://www.instagram.com/ande_lyons/ https://www.pinterest.com/andelyons/ https://angel.co/andelyons TikTok: @andelyonsANDELICIOUS RESOURCES:JOIN STARTUP LIFE LIVE MEETUP GROUPGet an alert whenever I post a new show!https://bit.ly/StartupLifeLIVEAGORAPULSEMy favorite digital marketing dashboard is AGORAPULSE – it's the best platform to manage your social media posts and presence! Learn more here: http://www.agorapulse.com?via=ande17STARTUP DOX Do you need attorney reviewed legal documents for your startup? I'm a proud community partner of Startup Dox, a new service provided by Selvarajah Law PC which helps you draw out all the essential paperwork needed to kickstart your business in a super cost-effective way. All the legal you're looking for… only without confusion or frustration. EVERY filing and document comes with an attorney review. You will never do it alone. Visit https://www.thestartupdox.com/ and use my discount code ANDE10 to receive 10% off your order.SPONSORSHIPIf you resonate with the show's mission of amplifying diverse founder voices while serving first-time founders around the world, please reach out to me to learn more about making an impact through sponsoring the Startup Life LIVE Show! ande@andelyons.com.STREAMYARD OVERLAYS AND GRAPHIC DESIGNNicky Pasquierhttps://www.virtuosoassistant.co.uk/Visit Nicky's CANVA Playlist: https://www.youtube.com/playlist?list=PLhUDgDHkkma3YhOf7uy8TAbt7HdkXhSjO

Watch this episode on YouTube: https://youtu.be/1BUxuHaZNBQ This Week's Guest is Data Modeling Platform Entrepreneur, Ahmed Elsamadisi Ahmed Elsamadisi is the Founder and CEO of Narrator.ai, a data modeling platform that allows data teams to answer any and all data questions within minutes. Before founding Narrator, Ahmed was the first member of WeWork’s data team, which he […]

Watch this episode on YouTube: https://youtu.be/1BUxuHaZNBQ This Week's Guest is Data Modeling Platform Entrepreneur, Ahmed Elsamadisi Ahmed Elsamadisi is the Founder and CEO of Narrator.ai, a data modeling platform that allows data teams to answer any and all data questions within minutes. Before founding Narrator, Ahmed was the first member of WeWork's data team, which he grew to include over 40 people. Since founding Narrator, Ahmed has graduated from startup accelerator Y Combinator and was named a member of Forbes' 30 Under 30 for 2021. Narrator.ai - https://Narrator.ai Twitter - https://www.twitter.com/ae4ai Email - ahmed@narrator.ai More Data Leadership: Data Leadership Training – https://DataLeadershipTraining.com Subscribe to Our Newsletter – http://eepurl.com/gv49Yr Follow Anthony Algmin on LinkedIn – https://www.linkedin.com/in/anthonyjalgmin Make an impact with a review on Apple Podcasts – https://podcasts.apple.com/us/podcast/data-leadership-lessons/id1505108710z

Ahmed is the founder and CEO of Narrator(narrator.ai). Narrator enables companies to make better decisions by providing them with the ability to answer any question in under 10 minutes. --- https://narrator.ai https://ideateandexecute.com --- Send in a voice message: https://anchor.fm/thinkfuture/message Support this podcast: https://anchor.fm/thinkfuture/support

This week we are thrilled to feature Ahmed Elsamadisi on our podcast. Ahmed is the founder and CEO of Narrator. Narrator enables companies to understand their customer, ask questions, and analyze data across all their systems from a single universal data model that grows with them. Ahmed started his career at Cornell's Autonomous Systems Laboratory, building algorithms for autonomous vehicles and human-robot interaction. He then joined Raytheon to develop AI algorithms for missile defense, focusing on tracking and discrimination. In 2015, Ahmed joined WeWork as the first hire on their data team. He built their data engineering infrastructure and grew the team to forty data engineers and analysts. Ahmed was also recognized as one of Forbes' 30 under 30 for 2021.  Tune into this week's episode to learn more about Making Consistent decisions.

In this episode, I sat down with Ahmed Elsamadisi, Founder of Narrator.ai, Forbes 30 under 30. We had a deep analytical discussion that covers the cookie-less future, how Ahmed's company, Narrator AI, is reinventing customer-centric datasets to answer marketing questions faster, how advertising platforms can be misleading about returns on ad spend, the value of negative information in measuring branding success, when to acquire customers at a greater cost than their LTV, the value of analytics and marketing, and more. Join the discussion below!  Twitter          |          LinkedIn Listen to more episodes on the Marketing x Analytics Homepage. Transcribed episodes of Marketing x Analytics are available on Podscribe.com. All view are our own.

Like most immigrants, Ahmed Elsamadisi felt he needed to assimilate. After moving from Egypt to the United States, the entrepreneur even decided to take acting classes to develop an American accent. As he got older, however, he realised the power in being unique. After overcoming many obstacles, Ahmed gained a degree in Robotics from Cornell University and is now the Founder of analysis software company, Narrator.ai. In this Peers2Peers episode, powered by Shopify, Ahmed shares how culture shock moulded his future, how to get a seat at the table, and why standing out shouldn't be feared. Discover more:Start your Shopify 14-day free trial: https://bit.ly/3fuq58C -Learn more about Narrator.ai: https://www.narrator.ai/ -Connect with Ahmed on Linkedin: https://www.linkedin.com/in/elsamadisi/ -Follow The Peers Project on Instagram: http://bit.ly/3adVmYG - See acast.com/privacy for privacy and opt-out information.

The perennial question of data warehousing is how to model the information that you are storing. This has given rise to methods as varied as star and snowflake schemas, data vault modeling, and wide tables. The challenge with many of those approaches is that they are optimized for answering known questions but brittle and cumbersome when exploring unknowns. In this episode Ahmed Elsamadisi shares his journey to find a more flexible and universal data model in the form of the "activity schema" that is powering the Narrator platform, and how it has allowed his customers to perform self-service exploration of their business domains without being blocked by schema evolution in the data warehouse. This is a fascinating exploration of what can be done when you challenge your assumptions about what is possible.

Narrator allows anyone to get answers in minutes instead of weeks, using the same data as your data team. Narrator is the first customer data analytics platform built for product teams that uses all of your data directly from your data warehouse. In this episode, we chat with Ahmed Elsamadisi, Founder of Narrator.ai, and member of the Forbes 30 under 30 As always, please add your views below and make sure you hit the subscribe button! #SaaS #Startups #Startuplife #EnterpriseSoftware

We know, we know. We went a little long this time, but you are going to love every minute of this week's guest. This week we are so excited to host Ahmed Elsamadisi from Narrator.ai. Ahmed is the co-founder and CEO of Narrator.ai, a startup that standardizes all data into a single format. He previously built out WeWork's data infrastructure and has also worked as an AI engineer at Raytheon. Not only that, he was also selected as one of Forbes' 30 under 30 this year. Ahmed chats with us about what it takes to be truly data driven, shares his learnings from WeWork in a high scale/competitive market, and what led him to create his own company, Narrator.ai.

In this episode of hitechies podcast we have Ahmed Elsamadisi He's currently the CEO of our data / ai startup  narrator.ai , a YC backed company that is trying to standardize all data analysis. Ahmed was honored as one of Forbes' 30 under 30 this year and has worked on missile defense algorithms for Raytheon.Ahmed started his career at Cornell's Autonomous Systems Laboratory focusing on human-robot interaction and Bayesian data fusion as well as building algorithms for autonomous cars. He then joined Raytheon to develop tactical AI algorithms for missile defense, four of which are still in use today by the US Military. Eventually, he moved on to Raytheon's Advanced Technology division to focus on building human exoskeletonsSponsor linkSafetyWing's Remote Health allows companies to offer equal benefits to the whole team, nomatter where they live or are located. Your team is global - their benefits should be global, too.Go to safetywing.com/remotehealth to learn more! Support the show (https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=BDL59C3CUWGXS&source=url)

Want to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. AbstractHosted by Al Martin, VP, IBM Expert Services Delivery, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.This week on Making Data Simple, we have Ahmed Elsamadisi. Ahmed started his career at Cornell’s Autonomous Systems Laboratory focusing on human-robot interaction and Bayesian data fusion as well as building algorithms for autonomous cars. He then joined Raytheon to develop tactical AI algorithms for missile defense, four of which are still in use today by the US Military. Eventually he moved on to Raytheon’s Advanced Technology division to focus on building human exoskeletons--like the Iron Man suit but made of rubber because it’s way more energy efficient and not a fictional concept ignoring proper scientific practices-- and algorithms for adaptive decision making.In 2015 Ahmed joined We Work, and over the next two years Ahmed built We Work’s standard data infrastructure and grew its data team from one to forty Data Engineers and Data Analysts.After implementing a single time series table data model at We Work and seeing the immediate results, Ahmed wanted to figure out a way to bring this new found knowledge to the world. Ahmed founded Narrator to allow startups to leverage this new approach, ask questions, understand customer behavior, and analyze data across all their systems from a simple Universal Data Model. Show Notes3:26 – Tell us about algorithms for autonomous cars6:26 – Anything you can say around missile defense?8:58 – Tell us about human exoskeletons13:18 – What kind of data were you using to make decisions around the Iron Man suit?16:02 – What did you learn at We Work?25:00 – How we answer a question in the world of Narrator32:24 – Does Narrator sit between the application and the database?33:28 – Walk us through a Use CaseWebsite: Narrator AI.comBooks: The Power of BadNever Split The DifferenceAhmed Elsamadisi - LinkedIn  Connect with the TeamProducer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter. 

A data-driven organization collects a wide variety of data to help in strategic decision-making. The cost of storing large amounts and variety of data has dropped dramatically in the last two decades, but too much unstructured data may not improve decision-making, and can even lead to “analysis paralysis.” Organizations react by extracting the most important, actionable data and placing it into a data warehouse, which has a predesigned structure meant to streamline the data in preparation for analysis. The key challenge with this approach is identifying what should be streamlined, and how to structure the data warehouse to focus on the most important, actionable items. This is especially important for organizations seeking to scale, as the necessary structure to generate the most relevant insights may change as the organization grows. Narrator is building data intelligence that uses a simple, proprietary Universal Data Model to help organizations streamline their data warehousing. Narrator is built on the belief that data tells the story of a system, and its platform empowers organizations to use those stories to make better decisions.Ahmed Elsamadisi is the founder and CEO of Narrator. Before founding Narrator, he spent several years working in data analysis and algorithm design for WeWork, Raytheon, and Cornell's Autonomous Systems Laboratory. He joins the show today to talk about how Narrator generates the most actionable insights from a data warehouse, why a Universal Data Model is so important when scaling, and what makes Narrator's approach to data analysis different.