2019

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Why Data Driven Decision Making is Your Path To Business Success

datapine

We read about it everywhere. The term ‘big data’ alone has become something of a buzzword in recent times – and for good reason. By leveraging the wealth of digital insights available at your fingertips and embracing the power of business intelligence , it’s possible to make more informed decisions that will lead to commercial growth, evolution, and an increased bottom line.

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Why a data scientist is not a data engineer

O'Reilly on Data

Or, why science and engineering are still different disciplines. "A scientist can discover a new star, but he cannot make one. He would have to ask an engineer to do it for him.". –Gordon Lindsay Glegg, The Design of Design (1969). A few months ago, I wrote about the differences between data engineers and data scientists. I talked about their skills and common starting points.

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An Exhaustive Guide to Detecting and Fighting Neural Fake News using NLP

Analytics Vidhya

Overview Neural fake news (fake news generated by AI) can be a huge issue for our society This article discusses different Natural Language Processing. The post An Exhaustive Guide to Detecting and Fighting Neural Fake News using NLP appeared first on Analytics Vidhya.

Analytics 393
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What is a business intelligence analyst? A role for driving business value with data

CIO Business Intelligence

Business intelligence (BI) analysts transform data into insights that drive business value. Through use of data analytics, data visualization and data modeling techniques and technologies, BI analysts can identify trends that can help other departments, managers and executives make business decisions to modernize and improve processes in the organization.

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Launching LLM-Based Products: From Concept to Cash in 90 Days

Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage

Christophe Louvion, Chief Product & Technology Officer of NRC Health, is here to take us through how he guided his company's recent experience of getting from concept to launch and sales of products within 90 days. In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.

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Open Source Projects by Google, Uber and Facebook for Data Science and AI

KDnuggets

Open source is becoming the standard for sharing and improving technology. Some of the largest organizations in the world namely: Google, Facebook and Uber are open sourcing their own technologies that they use in their workflow to the public.

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Enterprise Architecture Tools and the Changing Role of the Enterprise Architect

erwin

Enterprise architecture tools are becoming more important than ever. The International Enterprise Architecture Institute (IEAI) defines enterprise architecture (EA) as “the analysis and documentation of an enterprise in its current and future states from an integrated strategy, business and technology perspective.”. In the era of data-driven business, such perspective is critical.

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“If you are explaining, you are losing”

Juice Analytics

The title comes from Ronald Reagan, sometimes known as “The Great Communicator.” If he knew anything, he knew that simplicity was foundational when reaching a broad audience. That doesn’t stop people from finding ways to overcomplicate their data visualizations. Take this example from The Data Viz Catalogue. It is called a Radial Bar Chart. Radial Bar Chart.

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7 Ways To Use Big Data To Your Advantage On Social Media

Smart Data Collective

Businesses can use big data in many capacities, but those who use it for social media are at a huge advantage. It enables you as a social media marketer to get a closer look at your customer base, understand what drives purchasing decisions , and encourage consumers to pull the trigger. Using big data to augment your social media strategy provides a wealth of opportunities simply because social media is such an integral part of people’s lives.

Big Data 111
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5 Types of AI to Propel Your Business

ScienceSoft

Explore five different types of artificial intelligence (AI) – analytic, interactive, text, visual and functional – and get inspired by real-life business examples of AI in action.

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Data Science Cheat Sheet for Business Leaders

DataCamp

This cheat sheet guides you through the basics of how data science can help your business, including building your data science team and the common steps in the data science workflow.

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Data Modeling for Direct Mail: Boosting Multi-Channel Reach and Response

Speaker: Jesse Simms, VP at Giant Partners

This new, thought-provoking webinar will explore how even incremental efforts and investments in your data can have a tremendous impact on your direct mail and multi-channel marketing campaign results! Industry expert Jesse Simms, VP at Giant Partners, will share real-life case studies and best practices from client direct mail and digital campaigns where data modeling strategies pinpointed audience members, increasing their propensity to respond – and buy.

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Top 14 Must-Read Data Science Books You Need On Your Desk

datapine

“Big data is at the foundation of all the megatrends that are happening.” – Chris Lynch, big data expert. We live in a world saturated with data. At present, around 2.7 Zettabytes of data are floating around in our digital universe, just waiting to be analyzed and explored, according to AnalyticsWeek. By gaining the ability to understand, quantify, and leverage the power of online data analysis to your advantage, you will gain a wealth of invaluable insights that will help your business flourish

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The road to Software 2.0

O'Reilly on Data

Roughly a year ago, we wrote “ What machine learning means for software development.” In that article, we talked about Andrej Karpathy’s concept of Software 2.0. Karpathy argues that we’re at the beginning of a profound change in the way software is developed. Up until now, we’ve built systems by carefully and painstakingly telling systems exactly what to do, instruction by instruction.

Software 263
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5 Key Reasons Why Data Scientists Are Quitting their Jobs

Analytics Vidhya

Introduction The stock of a data scientist is at an all-time high right now. There aren’t too many professions out there that can rival. The post 5 Key Reasons Why Data Scientists Are Quitting their Jobs appeared first on Analytics Vidhya.

Analytics 389
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How Salesforce’s Tableau acquisition will impact IT

CIO Business Intelligence

Salesforce.com’s $15.7 billion bid for Tableau Software has many organizations wondering how the proposed acquisition will impact their operations. According to industry analysts, it all depends on how your enterprise makes use of their respective platforms. Users of Salesforce’s CRM platform have all subscribed to its software-as-a-service (SaaS) model, putting their data in the cloud — but the company is only beginning to respond to the demand for sophisticated tools to analyze that data. [ De

IT 111
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How To Speak The Language Of Financial Success In Product Management

Speaker: Jamie Bernard

Success in product management goes beyond delivering great features - it’s about achieving measurable financial outcomes that resonate across the organization. By connecting your product’s journey with the company’s financial success, you’ll ensure that every feature, release, and innovation contributes to the bottom line, driving both customer satisfaction and business growth.

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10 Free Top Notch Machine Learning Courses

KDnuggets

Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.

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5G Roadmap: Preparing Your Enterprise Architecture

erwin

Why planning your 5G roadmap requires significant input from enterprise architects. 5G is coming and bringing with it the promise to transform any industry. And while the focus has been on the benefits to consumers, the effects on the enterprise are far- reaching. Few examples of emerging technology have the potential to disrupt and downright revolutionize certain markets and processes than 5G.

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IADSS Talk – Who can be a Data Scientist?

Data Science 101

Initiative for Analytics and Data Science Standards (IADSS) is an organization working to develop standards around the roles in data science. They did a large survey earlier this year and they are starting to role out some of their results. Below is a video with some early results. Great Stuff! Data Science 101 is proud to be an IADSS Digital Community Partner.

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Machine Learning Product Management: Lessons Learned

Domino Data Lab

This Domino Data Science Field Note covers Pete Skomoroch ’s recent Strata London talk. It focuses on his ML product management insights and lessons learned. If you are interested in hearing more practical insights on ML or AI product management, then consider attending Pete’s upcoming session at Rev. Machine Learning Projects are Hard: Shifting from a Deterministic Process to a Probabilistic One.

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Provide Real Value in Your Applications with Data and Analytics

The complexity of financial data, the need for real-time insight, and the demand for user-friendly visualizations can seem daunting when it comes to analytics - but there is an easier way. With Logi Symphony, we aim to turn these challenges into opportunities. Our platform empowers you to seamlessly integrate advanced data analytics, generative AI, data visualization, and pixel-perfect reporting into your applications, transforming raw data into actionable insights.

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Is Big Data Creating A Competitive Edge For Small Businesses?

Smart Data Collective

Big data is transforming the daily realities of running a business. Companies can use big data to handle certain tasks more quickly and cost-effectively than ever. Vince Campisi, CIO of GE Software, Ash Gupta, an executive with American Express, and many other companies use big data to get a competitive advantage. Of course, big data also raises some new challenges.

Big Data 109
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3 Awesome Visualization Techniques for every dataset

MLWhiz

Visualizations are awesome. However, a good visualization is annoyingly hard to make. Moreover, it takes time and effort when it comes to present these visualizations to a bigger audience. We all know how to make Bar-Plots, Scatter Plots, and Histograms, yet we don’t pay much attention to beautify them. This hurts us?-?our credibility with peers and managers.

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Demystifying Automated Analytics, AI in BI and AutoML

DataRobot Blog

by Jen Underwood. So many buzzwords, so much confusion. Automated analytics, artificial intelligence (AI)-driven BI, and automated machine learning (AutoML), aren’t these terms describing the exact same thing? NO. Although these technologies may. Read More.

Analytics 111
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An Introduction To Data Dashboards: Meaning, Definition & Industry Examples

datapine

“It is a capital mistake to theorize before one has data.”– Arthur Conan Doyle. Data is all around us. According to the EMC Digital Universe study, by 2020, around 40 trillion megabytes – or 40 zettabytes – will exist in our digital landscape. That’s an unfathomable amount of information. Data has changed our lives in many ways, helping to improve the processes, initiatives, and innovations of organizations across sectors through the power of insight.

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Entity Resolution: Your Guide to Deciding Whether to Build It or Buy It

Adding high-quality entity resolution capabilities to enterprise applications, services, data fabrics or data pipelines can be daunting and expensive. Organizations often invest millions of dollars and years of effort to achieve subpar results. This guide will walk you through the requirements and challenges of implementing entity resolution. By the end, you'll understand what to look for, the most common mistakes and pitfalls to avoid, and your options.

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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

How companies in Europe are preparing for and adopting AI and ML technologies. In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. In practice this means developing a coherent strategy for integrating artificial intelligence (AI), big data, and cloud components, and specifically investing in foundational technologies needed to sustain the sensible use of da

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5 Weird and Hilarious Uses of Data Science

Analytics Vidhya

Introduction “Ripley’s Believe or Not” features some of the weirdest and most bizarre facts from around the world. How about creating our own Ripley’s. The post 5 Weird and Hilarious Uses of Data Science appeared first on Analytics Vidhya.

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7 Fundamental Steps to Complete a Data Project

Dataiku

It's hard to know where to start once you’ve decided that yes, you want to dive into the fascinating world of data and AI. Just looking at all the technologies you have to understand and all the tools you’re supposed to master is enough to make your dizzy.

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Data Science Curriculum Roadmap

KDnuggets

What follows is a set of broad recommendations, and it will inevitably require a lot of adjustments in each implementation. Given that caveat, here are our curriculum recommendations.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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The Design Thinking Process: Five Stages to Solving Business Problems

erwin

The design thinking process is a method of encouraging and improving creative problem-solving. The design thinking process is by no means new. John Edward Arnold, a professor of mechanical engineering and business administration, was one of the first to discuss the concept in as early as the 1950s. But the wave of digital and data-driven business has created new opportunities for the design thinking process to be applied.

Testing 111
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Cloud Data Science News – Beta #4

Data Science 101

In the United States, it is a holiday week, so the news is pretty limited from many of the big cloud providers. Luckily, Amazon has come through with a flurry of machine learning announcements. Amazon is holding their annual re:Invent Conference next week, so maybe these announcements are precursors to some bigger news next week. We will have to wait and see.

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Friends of Juice: Jessica Walker

Juice Analytics

Juice wouldn’t be the successful company that it is today without our friends who have championed our mission and expanded our network. We have identified several of Juice’s closest friends and advocates and we want to introduce them to you! Meet Jessica Walker, the CEO of Care Sherpa! For over 14 years, Jessica has been consulting with health care organizations and providers to support patient and employee engagement strategies with demonstrated financial and quality improvement impact.

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4 Data Goldmines Your Company Should Not Ignore

Smart Data Collective

In an earlier age, perhaps as little as a decade ago, businesses had to rely on intuition and educated guesses to guide their spending. The situation was famously captured by John Wanamaker, who said, “Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.” Today, data is everywhere. Phones track our locations and our social media usage.

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The Key to Sustainable Energy Optimization: A Data-Driven Approach for Manufacturing

Speaker: Kevin Kai Wong, President of Emergent Energy Solutions

In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. ♻️ Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets. 📊 Join us for a practical webinar hosted by Kevin Kai Wong of Emergent Ene