Sample Portfolio of Data Visualizations
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The document showcases a portfolio of data visualizations created by Andrei Pandre using tools like Tableau, QlikView, and Spotfire. It includes a variety of projects such as federal deficit timelines, sales dashboards, and visual analytics for HR data, along with links to demos and additional resources. Andrei also highlights different visualization techniques, including heatmaps, motion charts, and time series analyses.
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A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and PrivacyLessons Learned from Developing Secure AI Workflows.pdf
Lessons Learned from Developing Secure AI Workflows.pdfPriyanka Aash
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Lessons Learned from Developing Secure AI WorkflowsQuantum AI: Where Impossible Becomes Probable
Quantum AI: Where Impossible Becomes ProbableSaikat Basu
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Imagine combining the "brains" of Artificial Intelligence (AI) with the "super muscles" of Quantum Computing. That's Quantum AI!
It's a new field that uses the mind-bending rules of quantum physics to make AI even more powerful.Mastering AI Workflows with FME by Mark Doring
Mastering AI Workflows with FME by Mark DoringSafe Software
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Harness the full potential of AI with FME: From creating high-quality training data to optimizing models and utilizing results, FME supports every step of your AI workflow. Seamlessly integrate a wide range of models, including those for data enhancement, forecasting, image and object recognition, and large language models. Customize AI models to meet your exact needs with FMEs powerful tools for training, optimization, and seamless integrationOpenPOWER Foundation & Open-Source Core Innovations
OpenPOWER Foundation & Open-Source Core InnovationsIBM
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penPOWER offers a fully open, royalty-free CPU architecture for custom chip design.
It enables both lightweight FPGA cores (like Microwatt) and high-performance processors (like POWER10).
Developers have full access to source code, specs, and tools for end-to-end chip creation.
It supports AI, HPC, cloud, and embedded workloads with proven performance.
Backed by a global community, it fosters innovation, education, and collaboration."Scaling in space and time with Temporal", Andriy Lupa.pdf
"Scaling in space and time with Temporal", Andriy Lupa.pdfFwdays
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Design patterns like Event Sourcing and Event Streaming have long become standards for building real-time analytics systems. However, when the system load becomes nonlinear with fast and often unpredictable spikes, it's crucial to respond quickly in order not to lose real-time operating itself.
In this talk, Ill share my experience implementing and using a tool like Temporal.io. We'll explore the evolution of our system for maintaining real-time report generation and discuss how we use Temporal both for short-lived pipelines and long-running background tasks." How to survive with 1 billion vectors and not sell a kidney: our low-cost c...
" How to survive with 1 billion vectors and not sell a kidney: our low-cost c...Fwdays
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Let's talk about our history. How we started the project with a small vector database of less than 2 million records. Later, we received a request for +100 million records, then another +100... And so gradually we reached almost 1 billion. Standard tools were quickly running out of steam - we were running into performance, index size, and very limited resources. After a long series of trials and errors, we built our own low-cost cluster, which today stably processes thousands of queries to more than 1B vectors.Wenn alles versagt - IBM Tape sch端tzt, was z辰hlt! Und besonders mit dem neust...
Wenn alles versagt - IBM Tape sch端tzt, was z辰hlt! Und besonders mit dem neust...Josef Weingand
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IBM LTO10GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdf
GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdfPriyanka Aash
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GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing NowCurietech AI in action - Accelerate MuleSoft development
Curietech AI in action - Accelerate MuleSoft developmentshyamraj55
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CurieTech AI in Action Accelerate MuleSoft Development
Overview:
This presentation demonstrates how CurieTech AIs purpose-built agents empower MuleSoft developers to create integration workflows faster, more accurately, and with less manual effort
linkedin.com
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Key Highlights:
Dedicated AI agents for every stage: Coding, Testing (MUnit), Documentation, Code Review, and Migration
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DataWeave automation: Generate mappings from tables or samples95%+ complete within minutes
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Integration flow generation: Auto-create Mule flows based on specificationsspeeds up boilerplate development
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Efficient code reviews: Gain intelligent feedback on flows, patterns, and error handling
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curietech.ai
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Test & documentation automation: Auto-generate MUnit test cases, sample data, and detailed docs from code
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curietech.ai
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medium.com
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Why Now?
Achieve 10 productivity gains, slashing development time from hours to minutes
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Maintain high accuracy with code quality matching or exceeding manual efforts
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Ideal for developers, architects, and teams wanting to scale MuleSoft projects with AI efficiency
Conclusion:
CurieTech AI transforms MuleSoft development into an AI-accelerated workflowletting you focus on innovation, not repetition.Raman Bhaumik - Passionate Tech Enthusiast
Raman Bhaumik - Passionate Tech EnthusiastRaman Bhaumik
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A Junior Software Developer with a flair for innovation, Raman Bhaumik excels in delivering scalable web solutions. With three years of experience and a solid foundation in Java, Python, JavaScript, and SQL, she has streamlined task tracking by 20% and improved application stability.You are not excused! How to avoid security blind spots on the way to production
You are not excused! How to avoid security blind spots on the way to productionMichele Leroux Bustamante
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We live in an ever evolving landscape for cyber threats creating security risk for your production systems. Mitigating these risks requires participation throughout all stages from development through production delivery - and by every role including architects, developers QA and DevOps engineers, product owners and leadership. No one is excused! This session will cover examples of common mistakes or missed opportunities that can lead to vulnerabilities in production - and ways to do better throughout the development lifecycle.10 Key Challenges for AI within the EU Data Protection Framework.pdf
10 Key Challenges for AI within the EU Data Protection Framework.pdfPriyanka Aash
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10 Key Challenges for AI within the EU Data Protection FrameworkEIS-Webinar-Engineering-Retail-Infrastructure-06-16-2025.pdf
EIS-Webinar-Engineering-Retail-Infrastructure-06-16-2025.pdfEarley Information Science
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As AI reshapes expectations in retail and B2B commerce, organizations are recognizing a critical reality: meaningful AI outcomes depend on well-structured, adaptable infrastructure. In this session, Seth Earley is joined by Phil Ryan - AI strategist, search technologist, and founder of Glass Leopard Technologies - for a candid conversation on what it truly means to engineer systems for scale, agility, and intelligence.
Phil draws on more than two decades of experience leading search and AI initiatives for enterprise organizations. Together, he and Seth explore the challenges businesses face when legacy architectures limit personalization, agility, and real-time decisioning - and what needs to change to support agentic technologies and next-best-action capabilities.
Key themes from the webinar include:
Composability as a prerequisite for AI油- Why modular, loosely coupled systems are essential for adapting to rapid innovation and evolving business needs
Search and relevance as foundational to AI油- How techniques honed-in enterprise search have laid the groundwork for more responsive and intelligent customer experiences
From MDM and CDP to agentic systems油- How data platforms are evolving to support richer customer context and dynamic orchestration
Engineering for business alignment油- Why successful AI programs require architectural decisions grounded in measurable outcomes
The conversation is practical and forward-looking, connecting deep technical understanding with real-world business needs. Whether youre modernizing your commerce stack or exploring how AI can enhance product discovery, personalization, or customer journeys, this session provides a clear-eyed view of the capabilities, constraints, and priorities that matter most.Cracking the Code - Unveiling Synergies Between Open Source Security and AI.pdf
Cracking the Code - Unveiling Synergies Between Open Source Security and AI.pdfPriyanka Aash
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Cracking the Code - Unveiling Synergies Between Open Source Security and AIYou are not excused! How to avoid security blind spots on the way to production
You are not excused! How to avoid security blind spots on the way to productionMichele Leroux Bustamante
油
Ad
Sample Portfolio of Data Visualizations
- 1. Sample Portfolio of Data Visualizations Andrei Pandre Tools: Tableau, Qlikview, Spotfire, Omniscope, Google Charts Andreis Blog: http://apandre.wordpress.com/
- 2. 40-years long timeline of Federal Deficit, Revenue and Spending (Google Charts, triple combo (Area + Line Charts + Column Chart)
- 3. Incidents by Cause, Location, Category and Severity (Tableau)
- 4. Attempt to Visualize 20 Colors with 2-Dimensional Charts (Tableau)
- 6. HR Dashboard for Visual Analytics of Payrises by Performance, Salary, Seniority and Location (Omniscope)
- 7. Agile SDLC Software Development Life Cycle for Data Visualization Iterative Waterfall integrated with Scrum
- 8. Visualization of 20 Clusters for 100 million Sales transactions (Spotfire)
- 9. Visualization of Weekly Sales of Retail Giant discovered 3 Clusters: 2 very different Retail Chains and all other stores (Tableau)
- 10. Heatmap for Servers CPU hourly usage (Tableau)
- 11. Visualization of Trends for website Visitors (hourly, daily, weekly, monthly), using Sparklines, MicroColumn Charts and Radar Chart (Qlikview)
- 13. Visualization of Time Series of Weekly Sales (for 3+ years) for retail giant, showing repeating patterns Outliers much large sales during 2 Weeks of: Thanksgiving Day and Christmas (Tableau)
- 14. Near Realtimeline Visualization of the simultaneous Background Tasks on Tableau Server (Tableau)
- 16. Motion Chart (5dimensional Bubble Chart), showing dynamically population of multiple countries by population size, income, fertility, year (Qlikview)
- 17. Google Motion Chart (6-dimensional Bubble Chart), showing dynamically population of multiple countries by population Size, Income, Life Expectancy, Fertility, Year
- 18. Visio Diagram, showing typical Server Infrastructure for Data Visualization: Application Servers, DB, DW, ETL and File Servers, Analytical and Monitoring Servers, Routers, Switches and Load Balancers
- 19. Counties of USA, colored by their average ZIP Code (Tableau)
- 20. 2009 Population by ZIP Code (Tableau)
- 21. Links to Downloadable Data Visualization Demos ( Qlikview, Tableau, Spotfire) Qlikview Demo application, showing the Motion Chart, similar to Hans Rosling Demo: https://sites.google.com/site/pandre/files/MotionChart.qvw?attredirects=0&d=1 Interactive Visual Drill-Down Demo (each Chart as Filter) with Qlikview: https://sites.google.com/site/pandre/files/DrillDown.qvw?attredirects=0&d=1 Visualization of AdventureWorks data from Microsoft (using Qlikview): https://sites.google.com/site/pandre/files/SalesAW.qvw?attredirects=0&d=1 Sales Demo with Qlikview: https://sites.google.com/site/pandre/files/SalesApp11.qvw?attredirects=0&d=1 Andreis Tableau Public Profile with multiple online and Downloadable Demos with Tableau: http://public.tableausoftware.com/profile/andrei5435#/ Visualization of AdventureWorks data from Microsoft (using Spotfire): https://spotfire.cloud.tibco.com/private/ViewAnalysis.aspx?file=/users/a9p/Public/aw&w aid=e902e6a62d2f1f134216b-2311469709b58b