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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10 Power BI mistakes to avoid

CIO Business Intelligence

As a leading business intelligence tool, Power BI offers business users power and flexibility in dealing with data. The Microsoft tool provides everything from Excel integration to enterprise reporting and an increasing number of AI features that simplify getting deeper insights. In fact, the latest Forrester Wave report on augmented BI goes as far as to say “it is hard not to consider Power BI as your top choice for an enterprise BI platform.

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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.

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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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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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The Fundamentals of Exploratory Data Analysis

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Table of Contents Introduction About the Dataset Let’s Go 2D Scatter Plot 3D Scatter Plot Pair Plot Histogram Univariate Analysis using PDF CDF Mean, Variance, and Standard Deviation Median, Percentile, Quantile, IQR, MAD Box Plot Violin Plot Multivariate Probability Density Contour Plot Final Note […].

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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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6 Predictive Models Every Beginner Data Scientist Should Master

KDnuggets

Data Science models come with different flavors and techniques — luckily, most advanced models are based on a couple of fundamentals. Which models should you learn when you want to begin a career as Data Scientist? This post brings you 6 models that are widely used in the industry, either in standalone form or as a building block for other advanced techniques.

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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.

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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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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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8 Steps to Transformation at Speed & Scale – Your Guide to Deploying StratOps

📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.

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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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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 […].

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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.

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20 Best Examples of Charts and Graphs

Juice Analytics

We’ve collected these high-quality examples of charts and graphs to help you learn from the best. For each example, we point out some of the smart design decisions that make them effective in communicating the data. There is a lot of variety in styles and structures, but you may notice common elements across these well-designed data visualizations. For example, you’ll see… Thoughtful use of color; Few distracting elements that undermine the message; Labels and legends that highlight how to inter

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Marketing Operations in 2025: A New Framework for Success

Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

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How to Extract Tabular Data from Doc files Using Python?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Data is present everywhere. Any action we perform generates some or the other form of data. But this data might not be present in a structured form. A beginner starting with the data field is often trained for datasets in standard formats like […]. The post How to Extract Tabular Data from Doc files Using Python?

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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.

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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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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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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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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.

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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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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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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 Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.

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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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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.

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10 Tips to Visualize Data Like a Pro

Juice Analytics

Have you nailed all the data visualization basics? Stuff like… ?You know pie charts are bad except in certain specific use cases; ?You can spot chartjunk from a mile away; ?You confidently pick the right kind of chart based on what you want to emphasize in the data; ?You use just the right amount of color to bring meaning, but not so much as to distract; ?

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How to Create Stunning and Interactive Dashboards in Excel?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction I have been using Pandas with Python and Plotly to create some of the most stunning dashboards for my projects. In recent times, I have switched to learning Excel as it was a prerequisite in every company I had to apply to. I […]. The post How to Create Stunning and Interactive Dashboards in Excel?

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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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AI Adoption in the Enterprise 2021

O'Reilly on Data

During the first weeks of February, we asked recipients of our Data & AI Newsletter to participate in a survey on AI adoption in the enterprise. We were interested in answering two questions. First, we wanted to understand how the use of AI grew in the past year. We were also interested in the practice of AI: how developers work, what techniques and tools they use, what their concerns are, and what development practices are in place.

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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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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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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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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.