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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The Executive Guide to Generative AI

Generative AI is taking the world by storm, but the questions that all CEOs, data leaders, and AI leaders are being asked are: What are we going to do about it, and what is our plan? The business and creative possibilities are practically limitless with generative AI. From productivity gains to finding new routes to revenue generation, generative AI is going to radically transform how we work.

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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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Data Management on Display at Informatica World 2019

David Menninger's Analyst Perspectives

This year, I attended Informatica World 2019, Informatica's annual user conference. The main focus this year was on the cloud with a heavy does of AI. Under that focus, Informatica's conference emphasized capabilities across six areas (all strong areas for Informatica): data integration, data management, data quality & governance, Master Data Management (MDM), data cataloging, and data security.

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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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Machine Learning Algorithm Cheatsheet

Data Science 101

The fine folks at Microsoft have put together an excellent Single Page Cheatsheet for Azure Machine Learning Algorithms. It is very helpful for Azure, but it is also helpful for understanding when and why to use a particular algorithm. Microsoft’s Azure Machine Learning Algorithm Cheat Sheet. Start in the large blue box, “What do you want to do?

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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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Predictive Tourism: The Merger Of Big Data In Travel Industry

Smart Data Collective

Data science has shifted the existing ether bringing in new marvelous opportunities to many industries. In line with these immense possibilities, comes rapid changes and challenges. And in this case, the travel and tourism industry is no exception here. Travel industry may not be the first to inculcate emerging technology for its benefit, but it sure is benefiting from it now.

Big Data 131
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From Hadoop to Data Lakehouse

Getting off of Hadoop is a critical objective for organizations, with data executives well aware of the significant benefits of doing so. The problem is, there are few options available that minimize the risk to the business during the migration process and that’s one of the reasons why many organizations are still using Hadoop today. By migrating to the data lakehouse, you can get immediate benefits from day one using Dremio’s phased migration approach.

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Humans-in-the-loop forecasting: integrating data science and business planning

The Unofficial Google Data Science Blog

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. ln this post he describes where and how having “humans in the loop” in forecasting makes sense, and reflects on past failures and successes that have led him to this perspective. Our team does a lot of forecasting.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Over the past decade, business intelligence has been revolutionized. Data exploded and became big. We all gained access to the cloud. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. Suddenly advanced analytics wasn’t just for the analysts. 2019 was a particularly major year for the business intelligence industry.

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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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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 256
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ERM Program Fundamentals for Success in the Banking Industry

Speaker: William Hord, Senior VP of Risk & Professional Services

Enterprise Risk Management (ERM) is critical for industry growth in today’s fast-paced and ever-changing risk landscape. When building your ERM program foundation, you need to answer questions like: Do we have robust board and management support? Do we understand and articulate our bank’s risk appetite and how that impacts our business units? How are we measuring and rating our risk impact, likelihood, and controls to mitigate our risk?

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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 363
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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. A complementary Domino project is available. Introduction.

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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 Governance 2.0: The CIO’s Guide to Collaborative Data Governance

erwin

In the data-driven era, CIO’s need a solid understanding of data governance 2.0 … Data governance (DG) is no longer about just compliance or relegated to the confines of IT. Today, data governance needs to be a ubiquitous part of your organization’s culture. As the CIO, your stakeholders include both IT and business users in collaborative relationships, which means data governance is not only your business, it’s everyone’s business.

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The B2B Sales Leader's Guide for Any Economic Environment

When economic headwinds pick up, sales leaders are the first to sound the alarm — and chart a new course. Longer sales cycles, larger buying committees, increased price pressure, and smaller teams can quickly combine to reduce your margin for error and increase the urgency to find a solution. To thrive in a challenging environment, sales teams need a rock-solid grasp of the fundamentals and the biggest force-multipliers they can get their hands on.

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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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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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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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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

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The Definitive Guide to Dashboard Design

Dashboard design can mean the difference between users excitedly embracing your product or ignoring it altogether. Great dashboards lead to richer user experiences and significant return on investment (ROI), while poorly designed dashboards distract users, suppress adoption, and can even tarnish your project or brand. That’s one of the many reasons we wrote The Definitive Guide to Dashboard Design—to help you avoid common pitfalls, including… Cramming too much onto one screen and expecting the u

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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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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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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 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 358
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Connect, Care, Convert: Secrets to Establishing Trust with Niche Markets and Turning Them Into Clients

Speaker: Lynnette Khalfani-Cox, The Money Coach®

Niche markets represent a huge opportunity for the financial services industry in America. From college students and women to communities of color and low-to-moderate-income households, niche populations have specialized financial needs – but they often underutilize many valuable financial products and services. How can you better connect with these consumers?

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Deep Reinforcement Learning

Domino Data Lab

This article provides an excerpt “Deep Reinforcement Learning” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The article includes an overview of reinforcement learning theory with focus on the deep Q-learning. It also covers using Keras to construct a deep Q-learning network that learns within a simulated video game environment.

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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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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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Online Banking Without Third-Party Cookies

Since the inception of cookies in 1994, advertisers and brands have come to depend on them as a tool to help websites remember users. Consumers have tolerated them as a necessary cost of doing business online, even as they’ve grown to loathe them. As the end of third-party cookies looms ever closer, some consumers are rejoicing in their demise while many advertisers and brands worry about how they’ll move forward without them.