Amardeep Singh, MBA

Hi all! Priyanka Mehrotra Mehrotra and I are working furiously on finishing the People Analytics Tech (PAT) study, and we have come across a data point that is befuddling and would love your thoughts.   ​Some context: We are looking at how vendors are enabling their employees to ethically and safely develop AI. We divided the vendors into those that use both traditional ML and Gen AI and those that only use traditional ML in their solution. Generally speaking, a higher percentage of those vendors who use both types of AI tend to use more approaches more frequently. A GLARING difference, though, is with ethical frameworks. As you can see, those who use traditional ML only are much more likely to say they use them compared to the other group. My thinking is that possibly ethical frameworks take more time to develop, and so the other vendors haven't yet. But... those vendors are also using traditional ML (in addition to Gen AI), so if they had a framework before, it should still be there. ​What do you think? (BTW, the webinar is next Thursday, September 12, where we will unveil the findings from this year's study!)

58

19 Comments

📊 #DataLiteracy Resources 📊 💡 I recently published a #Gartner research note on data literacy skill gaps in product marketing, but the ability to read, write and communicate data in context is a universal skillset and can benefit every type of business professional. Many of the clients I speak to struggle to mature from a “gut feel” culture to one that is data-driven. ❓ Don't know where to start? Take a data literacy assessment to establish a baseline understanding of data literacy. Complete this assessment by using a FREE service from, for example, the "Data Literacy Project" (https://lnkd.in/eP3RB8CN), or a paid service from a training vendor, to identify and address gaps and areas of weakness. If you're a Gartner client, check out these additional data literacy resources: ➡ #ProductMarketing: https://lnkd.in/emSgurKN ➡ #DemandGeneration: https://lnkd.in/eqHwDbJb ➡ #CX Pros: https://lnkd.in/e5Crk4Vu ➡ Selecting a data literacy provider: https://lnkd.in/eDK73Q9x For help designing an in-house data literacy training program, schedule an inquiry with a Gartner data and analytics expert. #DecisionMaking #DataAnalysis #Storytelling #B2BMarketing

24

Some interesting PoV coming out of the Analytics Unite'24 conference. Wanted to share some interesting learnings as i interacted with Industry peers and friends but first - Big Shout & Thanks to all the organizers @CGT , EnsembleIQ, Industry friends and colleagues who came out to share their stories and experiences, helping us all, be able to build a better tomorrow! Look out for some interesting interviews over the next few weeks!! EP1 - Thanks to Anthony Park and Emily Faherty for their PoV on " Supply Chain in the complex OmniCommerce world and how GenAi can & should augment" #GenAi #Course5i #CPGAnalytics #RetailAnalytics Course5i Manish Srivastava Ashley Ramirez Nikhil Kapur Jasmeet Sraw Anees Merchant Nitesh Jain

148

1 Comment

Elevate Your Tableau Dashboards with Canada's Top Experts Who Do You Trust to Maximize Your BI Potential? 🇨🇦 In these challenging economic times, companies are streamlining their workforce, including their BI teams. With fewer BI specialists available, maintaining and developing high-quality Tableau reporting solutions can be a daunting task. But who do you trust to elevate your current reporting base to the maximum level? Look no further than Smart Analytics Zone, home to Canada’s most experienced Tableau experts. Why Choose Smart Analytics Zone? 🔹 Best-in-Class Dashboards: We deliver superior Tableau dashboards tailored to your business needs, transforming raw data into actionable insights. 🔹 Top Canadian Talent: Our team comprises the most experienced Tableau professionals in Canada, ensuring exceptional quality and expertise. 🔹 Comprehensive Support: From initial development to ongoing maintenance, our support specialists ensure your Tableau BI environment remains robust and effective. Our Services Include: 🔹 Custom Dashboard Development: Tailored solutions designed to provide interactive and visually engaging analytics. 🔹 Proactive Maintenance: Regular health checks and performance optimization to keep your dashboards running smoothly. 🔹 Issue Resolution: Quick and efficient troubleshooting to minimize downtime and keep your BI environment operational. 🔹 Documentation and Training: Detailed documentation and comprehensive training for your team, empowering them to handle future updates and changes. Benefits to Your Company: 🔹 Expertise: Trust in the top Tableau specialists in Canada to deliver high-quality BI solutions. 🔹 Reliability: With Analytics Zone, you can be confident that your Tableau environment is in expert hands. 🔹 Scalability: Flexible support packages tailored to your specific needs, ensuring you have the right level of assistance as your business evolves. Partner with Smart Analytics Zone to Secure Your BI Future: In times of economic uncertainty, having a trusted partner for your BI needs is crucial. Let Smart Analytics Zone provide the expert support and peace of mind you need to focus on what matters most—driving your business forward. Ready to elevate your Tableau dashboards and maximize your reporting capabilities? Let’s connect and explore how we can help. #DataVisualization #Tableau #BusinessIntelligence #BI #AnalyticsZone #Canada #TopExperts #SupportServices #FutureProofBI

1

Understanding the difference between perception and perspective helps an analyst build better analytics. Perception refers to how we interpret sensory information, influenced by our senses, experiences, and biases. It's subjective and can vary among individuals. Perspective, on the other hand, is a broader view that considers various factors, including perceptions, knowledge, context, and goals. It's more objective and holistic. For an analyst, understanding this difference is crucial. Perception affects how data is interpreted, potentially leading to biased conclusions. Perspective helps analysts consider multiple viewpoints, avoid tunnel vision, and make informed, unbiased decisions. It enables them to see the bigger picture, identify patterns, and provide valuable insights for decision-making. #analyst #analytics #perception #perspective #decisionmaking #knowledge

4

In today's data-driven world, data annotation is the key to unlocking business potential. At Evalueserve, we transform raw data into actionable insights, powering AI and GenAI solutions. Data annotation is essential for: - AI Learning: Provides the foundation for accurate AI models. - Model Accuracy: Ensures precise predictions and decisions. - Diverse Applications: Powers image recognition, NLP, chatbots, and more. - Continuous Learning: Keeps AI models updated and relevant. Our mind+machine™ approach combines generative AI with human expertise to deliver tailored data annotation solutions. In my blog, we've explored the critical importance of data annotation, its diverse use cases, and how Evalueserve's innovative solutions are leading the way by enhancing decision-making, improving customer experience, and increasing productivity. Let's turn raw data into business gold together! https://lnkd.in/g4xqRWiE #DataAnnotation #AI #MachineLearning #BusinessIntelligence #Evalueserve #Innovation #DataScience #CustomerExperience

36

6 Comments

If I had a magic wand 🎇, I would wave it and teach everyone the #softskills required to be a persuasive people manager. But I don't have a magic wand. 🚫🎇 We pitch ourselves daily and in every meeting, whether we mean to or not. I recommend that all quantitative and technical people take a persuasive communication class and a psychology class to learn how to understand people's body language (facial expressions, micro-expressions, gestures) and persuasion techniques. It will help you tell your data story. ▶ It will help you narrate like a performer. 🎤 It will help you be successful and create a win-win-win. ✅ ☑ ✔ Ben Parker Parker B Associates #upskilling #persuasivecommunication #leadership https://lnkd.in/eWuww2Yq

9

It was a great pleasure to talk at Celonis Day India 2024 (unfortunately remote). I talked about "Object-Centric Process Mining: Disentangling the Fabric of Real Processes To Enable Predictive and Generative AI". The main takeaway is that one cannot expect ChatGPT to tell something meaning about our processes if you do not provide it with data on objects and events, and process models. #OCPM helps you to disentangle the Spaghetti and prepare it for AI. India is an important process mining market and hosts 1500+ shared service centers of global companies. An interesting statistic: My Coursera #ProcessMining course had over 170.000 participants. When looking at the recent statistics showing the ranking of countries, the top five are (1) India, (2) the USA, (3) Germany, (4) the Netherlands, and (5) Brazil. See https://lnkd.in/eUJyuMgX for the program. #ObjectCentricProcessMining #GenAI #ProcessMining #ProcessIntelligence #BPM #LLM

166

📊 People analytics is more than just numbers—it's about understanding the story behind the data. While metrics and insights can inform decision-making, it's essential to approach them with empathy and an awareness of context. 👨‍🔧 Every data point represents an individual’s experience, and without considering the human element, the solutions we create can miss the mark. By digging deeper into the "why" behind the trends and listening to the people involved, we can craft strategies that truly resonate and drive meaningful change. 🌱 As we leverage analytics to shape better workplaces, let’s remember: empathy isn’t just a nice-to-have, it’s the key to unlocking real, impactful insights. . . . . . #PeopleAnalytics #Empathy #EmployeeExperience #DataDrivenHR #InclusiveWorkplaces

6

3 Comments

"Love is not scientific. It's not mathematical. Its not exactly rational". I read this in a book just now and it got me thinking, people in love should not work in analytics and experimentation. Primal instincts are unreliable when it comes to understanding human behaviour in the form of data points. So whilst babies might understand love, I doubt they'll be able to understand linear regression, and if that is the bar for people in love, I doubt they'll be able to either. So if you really want to succeed in this field, leave matters of the heart to people who aren't carrying the analytical burden of entire organisations on their shoulders, like the marketing team... or babies. They'll never understand the weight we carry and we can't afford to be irrational. The only thing you should love is your analytics stack and your data engineering team. They are like the cupids of the analytics world. As for the author who is trying to "make sense of this apparent contradiction", his inability to see that there is no contradiction has got me questioning his authority as an author. If love was scientific, mathematical and rational then I'm pretty certain a baby would not know what it is. The fact that it's not is probably the reason why a baby understands it. Maybe he should have said love is complex... yet simple enough that a baby understands it. Then he would have found the contradiction he was looking for.

5

9 Comments

This is the power of networking on LinkedIn - It's an incredible platform for knowledge sharing and opportunities. Today I had a chance to connect with Sivanagaraju G., An individual with 14 years of diverse & immense experience Across Analytics and Business Intelligence. In the short conversation we had, We were able to talk about BI, Data Analytics and also the idea of a potential collaboration to share knowledge about Business Intelligence with the broader community. But for me, That was NOT the highlight of this connect. The main highlight was the fact that He was interested in connecting with me After coming across my podcast and content, And being willing to help contribute to the same. This is something that has rarely happened with me Since I started creating content & launched my podcast last year. That's simply the by-product of being willing to share. You don't necessarily need to have a super huge following or be an expert content creator to experience such surprises All you need is to come forward and share your ideas, thoughts, experiences and knowledge. And who knows! What might come knocking on the door. P.S We did discuss a potential session on understanding about Business Intelligence as we've come across many interested in understanding about this domain. If you have any questions you'd like to have answered, feel free to share to across soon.

5

-> For quality driven approaches and getting the facts right, we would need to focus on "what respondents are thinking", not just on the statistical analysis of respondent surveys with Q&A or create a summary of respondent's narratives? It is possible by applying #SymbolicAI Sing Koo : "When the quality of the conversation matters, sampling people for questions on subjects will not tell the truth about the audience. Human criticism towards a subject has no boundary. By binding a human mind with a question on a subject will not get the truth. History up to now has been relying on traditional ways of asking questions. Other examples, such as Net Prompter Score (NPS) question being used to measure customer loyalty and satisfaction, have failed in similar ways. When businesses fail to understand the truth on customer preference, advertising money is wasted. All this is about to change for the better if we apply logic to understand the audience by allowing them to speak their mind on a subject, and then apply Natural Language Understanding (NLU) with Abstractive Symbolic Logic to reduce the response into High Level Abstractions before applying statistical analysis. The way Abstractive Symbolic Logic works is to reverse the response into what the respondent is thinking instead of boxing the respondent to rate a question on the subject. Similar attempts by other NLU algorithms that use Word Frequency to determine keywords in conjunction with Sentiment Analysis will not produce reliable results because it fails to pin point the ideas from the respondent, instead, it introduces bias and incorrect interpretations. The process of reverse engineering is in some ways similar to the application of Abstractive Symbolic with Natural Language to reverse responses to respondent's thinking.  #symbolicai #elaineai #sitefocus A simple example with sample extracts : Utilized this to understand what the author was thinking by analyzing this article: https://lnkd.in/gnNVzem9 ->America's $175 Trillion Problem: The true state of the global financial system ( DOLLAR, DEBT )  top ( DOLLAR, DEBT, EMPIRE )  top (Read more)  topPeacetime debt approaching WW2. . True debt of 175T, more than any empire in history.

8

3 Comments

𝗧𝗵𝗲 𝗴𝗲𝗻𝗲𝗿𝗮𝗹𝗶𝘀𝘁 𝘀𝘂𝗽𝗲𝗿𝗽𝗼𝘄𝗲𝗿: 𝗗𝗮𝘆 𝟯 𝗼𝗳 𝟱. Translator, collaborator, and 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗼𝗿! Many data nerds 🤓 have non-linear career journeys. In a career detour? 🚧 That's okay - it'll help you 𝗰𝗼𝗻𝗻𝗲𝗰𝘁 𝘁𝗵𝗲 𝗱𝗼𝘁𝘀! Read on... ⬇   Khayyam Wakil says "Generalists possess a unique superpower: the ability to connect the dots between seemingly disparate fields and concepts. Armed with a diverse knowledge base spanning multiple domains, they can see patterns and parallels that specialists, immersed in the depths of their own area of expertise, often miss. This bird’s-eye view allows generalists to transplant ideas from one field to another, leading to novel solutions and fresh perspectives."   Here's 3 tips I've found helpful to connect the dots (in data):   𝟭. 𝗟𝗼𝗼𝗸 𝗳𝗼𝗿 𝘀𝗶𝗺𝗶𝗹𝗮𝗿𝗶𝘁𝗶𝗲𝘀. Having analyzed data about surgery cases to car parts to pasta sauce, I can tell you how they're different. But am also able to see unique ways they're similar that 20 year veterans in the industry miss. Don't let your career detour lock you into any given industry.   𝟮. 𝗕𝗿𝗲𝗮𝗸 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝗱𝗼𝘄𝗻. Data that looks dissimilar on the surface can look familiar when you break it into parts. If you're interviewing for a role in an unfamiliar industry, don't be afraid to draw comparisons to data you're familiar with to show your critical thinking ability.   𝟯. 𝗕𝗲 𝗮 𝘀𝗽𝗼𝗻𝗴𝗲. There are no shortcuts. If you really want to connect the dots, you need to learn the data. I love the Suits pilot when Harvey asked Mike how he passed the bar... His response? I learned it. I never said your non-linear career journey would be easy, did I? Here's Khayyam Wakil's full 21-minute read: https://lnkd.in/gP4DUUHQ Missed day 1 or 2? Day 1 (Translator): https://lnkd.in/g-DGc9CR Day 2 (Collaborator): https://lnkd.in/gxhxfD6M #generalists #data #careers

17

4 Comments

Statistical significance, confidence intervals, and p-values are fundamental concepts in statistical analysis, each serving distinct but interconnected roles in understanding and interpreting data. This article provides an intuitive explanation of these concepts using an example from pharmacovigilance. #statistics #dataanalaysis #learning https://lnkd.in/gvhuwPG2

40

3 Comments

After five years in a large company, I was eager to do something different. I have decided to venture into a nimbler and futuristic company (Tredence: www.tredence.com) Similar to the digital transformation a few years ago, I expect that the technology market will undergo a significant shift. This shift in AI and data will create a new category of services, much like the digital revolution did a decade ago. In simple terms, we are approaching a crucial turning point. As with any turn, the smaller, more agile entities will navigate quickly, while the larger ones will eventually catch up if they can maneuver the turn effectively. . I anticipate that Tredence will be at the forefront of creating this new category. It's not clear what will this be called or what shape will it take? In my mind, AI/data Services, primarily comprising three key components: - Data Preparation: Ensuring data is ready for analysis and utilization. - Model Development: Creating and training models, leveraging this data. - Model Industrialization: Scaling and integrating models into business processes. These services are poised to deliver disruptive advantages in terms of increased revenue, newer market, and hyper cost efficiency for their adopters. However, undertaking this transformation comes with inherent risks. Therefore, executing it responsibly with appropriate oversight will be paramount. We are building Tredence for this transformative shift. #tredence #AI #Data #Transformation

890

156 Comments

Check out Spark Decks Positive Behavior Guidance book, deck, and series! Book: https://lnkd.in/gPP58WXn Deck: https://lnkd.in/g9D5_e4P Series: https://lnkd.in/gcpY2yzE What other positive behavior guidance resources do you love?

9

Defining the Boundaries: Advancing Data Science Integration and Strategic Response in Non-Technical Sectors Council Post: Roundtable Discussion on Navigating the Gen AI Adoption Cycle-Organisation’s Strategic positioning Post by Yogananda Domlur Seetharama (Yog Seetharama), Director of Data Science at Walmart Global Tech Read the complete roundtable article here: https://lnkd.in/gSX9yHxR #AIM #AI #GenAI #LeadersCouncil #CouncilPost

4

Defining the Boundaries: Advancing Data Science Integration and Strategic Response in Non-Technical Sectors Council Post: Roundtable Discussion on Navigating the Gen AI Adoption Cycle-Organisation’s Strategic positioning Post by Yogananda Domlur Seetharama (Yog Seetharama), Director of Data Science at Walmart Global Tech Read the complete roundtable article here: https://lnkd.in/gSX9yHxR #AIM #AI #GenAI #LeadersCouncil #CouncilPost

7

Role of Data and Enterprise Leaders! Strategy Formulation Data and enterprise leaders are a powerful duo when it comes to strategy formulation. Data leaders bring insights and analytics to the table, while enterprise leaders ensure that these insights align with the broader business goals. Together, they create data-driven strategies that enhance competitiveness and growth. #DataStrategy #Leadership #DigitalTransformation Execution and Governance Seamless execution and governance are critical for any organization. Enterprise leaders focus on the big picture—budgets, resources, and structures. Data leaders ensure the right frameworks, governance, and compliance are in place for effective data utilization. The result? Execution with precision and purpose. #DataGovernance #ExecutionExcellence #BusinessLeadership Driving Operational Efficiency Data is at the heart of operational efficiency. Data leaders use automation, predictive analytics, and optimization techniques to streamline operations. Meanwhile, enterprise leaders focus on integrating these solutions across the organization, improving workflows, reducing costs, and increasing productivity. #OperationalEfficiency #AI #BusinessOptimization Innovation and Competitive Advantage Innovation is the lifeblood of business growth. When data leaders and enterprise leaders collaborate, they unlock the power of advanced analytics and AI to drive competitive advantage. Data leaders focus on the tech, enterprise leaders bring the vision—and together, they make innovation happen. #Innovation #AI #BusinessTransformation Post 5: Empowering Decision-Making Faster, smarter decisions come from the synergy between data and enterprise leadership. Data leaders provide real-time, actionable insights, empowering enterprise leaders to make data-driven decisions that keep the business agile and responsive to market changes. #DataDriven #DecisionMaking #AgileBusiness

10