2021

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Tech workers warned they were going to quit. Now, the problem is spiralling out of control

DataKitchen

The post Tech workers warned they were going to quit. Now, the problem is spiralling out of control first appeared on DataKitchen.

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5 hot new IT jobs — and why they just might stick

DataKitchen

The post 5 hot new IT jobs — and why they just might stick first appeared on DataKitchen.

IT 356
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Data-driven 2021: Predictions for a new year in data, analytics and AI

DataKitchen

The post Data-driven 2021: Predictions for a new year in data, analytics and AI first appeared on DataKitchen.

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Pokemon Prediction using Random Forest

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Overview This Pokemon will analyze the pokemon dataset and predict whether the Pokemon is legendary based on the features provided. We will discuss everything from scratch; we will go from CSV to model building with line by line explanation of code. Let’s get started. Image […].

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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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Misleading Statistics Examples – Discover The Potential For Misuse of Statistics & Data In The Digital Age

datapine

Table of Contents. 1) What Is A Misleading Statistic? 2) Are Statistics Reliable? 3) Misleading Statistics Examples In Real Life. 4) How Can Statistics Be Misleading. 5) How To Avoid & Identify The Misuse Of Statistics? Statistical analyses have historically been a stalwart of the high-tech and advanced business industries, and today they are more important than ever.

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2021 Data/AI Salary Survey

O'Reilly on Data

In June 2021, we asked the recipients of our Data & AI Newsletter to respond to a survey about compensation. The results gave us insight into what our subscribers are paid, where they’re located, what industries they work for, what their concerns are, and what sorts of career development opportunities they’re pursuing. While it’s sadly premature to say that the survey took place at the end of the COVID-19 pandemic (though we can all hope), it took place at a time when restrictions were loose

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Isn’t it time community speakers were all treated reasonably and equally by organizers?

Jen Stirrup

TL; DR Yes. Let me tell you about the second-worst conference experience I’ve ever had as a speaker. The worst experience happened a few years ago and it is at the foot of the post so you will have to read down – note, it does have a trigger warning. Speakers from diverse backgrounds want equality not preferential treatment. Let me explain a scenario and let me make it clear that I’m not asking for preferential treatment.

IT 145
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Anima Anandkumar: What’s in the Future for AI?

DataRobot

Anima Anandkumar joined Ben Taylor, Chief AI Evangelist at DataRobot, on the More Intelligent Tomorrow podcast to discuss the future direction of AI technology and its possible enhancement by the addition of more human capabilities. Bren Professor of Technology at California Institute of Technology (CalTech), Anima joined Nvidia three years ago as the Director of Machine Learning Research.

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3 Practices to Help Build a Strong Data Culture

Dataiku

Let’s be frank — creating a lasting data culture in your company isn’t going to happen overnight. No technology you install or datasets you gather will do that for you. You need time and, as we’ve seen across pop culture, it usually takes a new idea or innovation (or an old idea packaged as new) to change culture. This change usually falls on data leaders to drive because they have a unique perspective across data, technology, and the organization.

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The Role of Model Governance in Machine Learning and Artificial Intelligence

Domino Data Lab

In the world of machine learning (ML) and artificial intelligence (AI), governance is a lifelong pursuit. All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards. As such, model governance needs to be applied to each model for as long as it’s being used.

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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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Converting Big Data into Actionable Intelligence

TDAN

In today’s world, access to data is no longer a problem. There are such huge volumes of data generated in real-time that several businesses don’t know what to do with all of it. Unless big data is converted to actionable insights, there is nothing much an enterprise can do. And outdated data models no longer […].

Big Data 145
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How to Utilize Artificial Intelligence in Your eCommerce SEO Strategy

Smart Data Collective

If you have not lived under a rock for several years, you have undoubtedly heard about artificial intelligence (AI). However, how might artificial intelligence be used in e-commerce operations? Artificial intelligence (AI) is starting to fill every facet of our daily lives. For example, self-checkout cash registers, airport security checks, and other automated processes all use artificial intelligence to some degree.

Strategy 143
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A Developer’s Guide to Creating Bad Power BI Projects – Part 1

Paul Turley

It occurred to me that we have put so much effort into promoting best practices and proper design that there is far less information about how to create bad reports and data models. In that light, the purpose of this article is to talk about what to do if you want things to go poorly and make sure your projects fail - if not immediately, then sometime in the future - and if not for you then for whoever inherits the work that you have done.

Modeling 145
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Intent Classification with Convolutional Neural Networks

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Text classification is a machine-learning approach that groups text into pre-defined categories. It is an integral tool in Natural Language Processing (NLP) used for varied tasks like spam and non-spam email classification, sentiment analysis of movie reviews, detection of hate speech in social […].

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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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What Mature Data Infrastructure Looks Like

DataCamp

Unlocking the value of data in an organization starts with having the right data infrastructure and tooling foundations. Here’s a look at the current state and future trends of data infrastructure.

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The Next Generation of AI

O'Reilly on Data

Programs like AlphaZero and GPT-3 are massive accomplishments: they represent years of sustained work solving a difficult problem. But these problems are squarely within the domain of traditional AI. Playing Chess and Go or building ever-better language models have been AI projects for decades. The following projects have a different flavor: In February, PLOS Genetics published an article by researchers who are using GANs (Generative Adversarial Networks) to create artificial human genomes.

Modeling 363
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Building a solid data team

KDnuggets

How do you put together a solid data science team when it comes to developing data-driven products? A variety of roles are available to consider, so which ones do you need and which are most crucial?

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Turning the page

Cloudera

Today marks the beginning of an exciting new chapter for Cloudera. Cloudera will become a private company with the flexibility and resources to accelerate product innovation, cloud transformation and customer growth. Cloudera will benefit from the operating capabilities, capital support and expertise of Clayton, Dubilier & Rice (CD&R) and KKR – two of the most experienced and successful global investment firms in the world recognized for supporting the growth strategies of the businesses

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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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Humans and AI: Bargaining Power

DataRobot

I have a confession to make—I’m a back-seat driver! When sitting in a taxi, I can’t help but grumble when the ride isn’t smooth, or the driver chooses the slowest lane of traffic. I have to fight the urge to take control. When it comes to shopping, I passively accept what is offered for sale. But my wife, who grew up in Asia where haggling is part of the culture, is different.

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Medical Data and Advanced Robotics: Saving Lives, Improving Care

Sisense

Blog. Imagine a future where a wide range of surgeries, no matter how complex, could be conducted remotely, a future where a patient in dire need of help could access the most highly regarded specialists in any area of medicine regardless of where on the globe that person may be. In 2019, Dr. Ryan Madder from Spectrum Health performed a series of simulated remote percutaneous coronary interventions (PCIs) via a control station outside of Boston.

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Data Science Tools: Understanding the Multiverse

Domino Data Lab

In the multiverse of data science, the tool options continue to expand and evolve. While there are certainly engineers and scientists who may be entrenched in one camp or another (the R camp vs. Python, for example, or SAS vs. MATLAB), there has been a growing trend towards dispersion of data science tools. As new team members with varying backgrounds are added, as new sources of data are made available from different platforms, or new deliverables are required from stakeholders, allegiance to a

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How to Win New Business with External Data

TDAN

Increasingly, external data (alternative data, public data, open data – call it what you want) is being called the “secret sauce” of driving advanced analytics, developing machine learning and AI capabilities, enriching existing models, and delivering unrealized insights to every part of your organization. The difficulty in connecting to this data is top of mind for […].

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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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Data Strategy: The Missing Link in Your Digital Transformation Plan

Smart Data Collective

On the surface, digital transformation is a simple process. You take a business activity that is old and ineffective/inefficient and re-energize it with new technology. This could be moving your spreadsheets to cloud software or even going so far as to move up from paper to digital. There is nothing inherently wrong with this process, but the way digital transformation is deployed often misses powerful opportunities ripe for the taking.

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Drill-through from Power BI to Paginated Report – Report Recipe #4

Paul Turley

Navigation between reports is the hallmark of an interactive reporting solution, enabling the ability to drill-through and see relevant details and contextual filtered information in a target report.

Reporting 145
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Building an End- to-End Data Science App with Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. [link] Overview In this article, we will detail the need for data scientists to quickly develop a Data Science App, with the objective of presenting to their users and customers, the results of Machine Learning experiments. We have detailed a roadmap for the […]. The post Building an End- to-End Data Science App with Python appeared first on Analytics Vidhya.

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The How-To Guide for Cleaning and Preparing Data for Analysis

Juice Analytics

Tidying up your data is part science, part art, and all work. If you’re lucky, you’ll get your hands on some perfectly formatting data ( Slack does a nice job, for example). But more often than not, you’ll need to do some data cleaning before it is ready for analysis. Survey data is a particularly common clean-up challenge, but even pulling data from Google Analytics will require some clean-up.

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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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Where Programming, Ops, AI, and the Cloud are Headed in 2021

O'Reilly on Data

In this report, we look at the data generated by the O’Reilly online learning platform to discern trends in the technology industry—trends technology leaders need to follow. But what are “trends”? All too often, trends degenerate into horse races over languages and platforms. Look at all the angst heating up social media when TIOBE or RedMonk releases their reports on language rankings.

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Why Machine Learning Engineers are Replacing Data Scientists

KDnuggets

The hiring run for data scientists continues along at a strong clip around the world. But, there are other emerging roles that are demonstrating key value to organizations that you should consider based on your existing or desired skill sets.

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Our Top Data and Analytics Predicts for 2021

Andrew White

Predicts 2021: Data and Analytics Leaders Are Poised for Success but Risk an Uncertain Future : By 2023, 50% of chief digital officers in enterprises without a chief data officer (CDO) will need to become the de facto CDO to succeed. By 2024, widespread adoption of cloud will raise the CFO’s influence over the chief data officer’s (CDO) decisions due to explicit linkage of workloads to cost , bringing disruption to the CDO role.

Analytics 144
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Humans and AI: Organizational Change

DataRobot

According to McKinsey, “Research shows that 70 percent of complex, large-scale change programs don’t reach their stated goals. Common pitfalls include a lack of employee engagement, inadequate management support, poor or nonexistent cross-functional collaboration, and a lack of accountability.”. Last year I was doing some spring cleaning and looking for space in my home office for a digital piano.

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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.