2019

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How Do You Define Unfair Bias in AI?

DataRobot

Art is subjective and everyone has their own opinion about it. When I saw the expressionist painting Blue Poles , by Jackson Pollock, I was reminded of the famous quote by Rudyard Kipling, “It’s clever, but is it Art?” Pollock’s piece looks like paint messily spilled onto a drop sheet protecting the floor. The debate of what constitutes art has a long history that will probably never be settled, there is no definitive definition of art.

IT 107
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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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Waterfall to Agile: A Necessary Mindset Shift For Business Analysts

BA Learnings

I tend to describe the agile approach as a way of working; A targeted way of working that allows us to make changes, respond to customers’ needs and manage uncertainty with minimal delays, and without needing to wade through “red tape”. Agile manifesto encourages: - Customer collaboration over contract negotiation - Individuals and interactions over processes and tools - Responding to change over following a plan - Working software over full documentation This does not however imply that the agi

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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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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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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 400
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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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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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Introduce Children to Machine Learning

Data Science 101

It is Computer Science Education Week and in 2019 Machine Learning and Artificial Intelligence are two of the most popular and influential topics in technology. That is why I was so excited when Code.org launched a training specifically aimed at the topics. It is called AI for Oceans and it is geared for children (or really anyone, I had fun with it and so did my children).

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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 110
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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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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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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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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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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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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 262
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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

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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 394
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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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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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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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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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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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Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity

Speaker: Nicholas Zeisler, CX Strategist & Fractional CXO

The first step in a successful Customer Experience endeavor (or for that matter, any business proposition) is to find out what’s wrong. If you can’t identify it, you can’t fix it! 💡 That’s where the Voice of the Customer (VoC) comes in. Today, far too many brands do VoC simply because that’s what they think they’re supposed to do; that’s what all their competitors do.

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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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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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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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Monetizing Analytics Features

Think your customers will pay more for data visualizations in your application? Five years ago, they may have. But today, dashboards and visualizations have become table stakes. Turning analytics into a source of revenue means integrating advanced features in unique, hard-to-steal ways. Download this white paper to discover which features will differentiate your application and maximize the ROI of your analytics.

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8 Ways to Fine-tune your SQL Queries (for production databases)

Sisense

In organizations that operate without a data warehouse or separate analytical database for reporting, the only source of the latest and up-to-date data may be in the live production database. When querying a production database, optimization is key. An inefficient query may pose a burden on the production database’s resources, and cause slow performance or loss of service for other users if the query contains errors.

Sales 111
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10 Best and Free Machine Learning Courses, Online

KDnuggets

Getting ready to leap into the world of Data Science? Consider these top machine learning courses curated by experts to help you learn and thrive in this exciting field.

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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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How to Stay Competitive in the Evolving State of Martech

Marketing technology is essential for B2B marketers to stay competitive in a rapidly changing digital landscape — and with 53% of marketers experiencing legacy technology issues and limitations, they’re researching innovations to expand and refine their technology stacks. To help practitioners keep up with the rapidly evolving martech landscape, this special report will discuss: How practitioners are integrating technologies and systems to encourage information-sharing between departments and pr