Sat.Jan 29, 2022 - Fri.Feb 04, 2022

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Introduction to AdaBoost for Absolute Beginners

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. AdaBoost stands for Adaptive Boosting. It is a statistical classification algorithm. It is an algorithm that forms a committee of weak classifiers. It boosts the performance of machine learning algorithms. It helps you form a committee of weak classifiers by combining them into a single strong […].

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The 2022 Market Agenda for Analytics: Enabling Actions and Effective Insights

David Menninger's Analyst Perspectives

Ventana Research recently announced its 2022 Market Agenda for Analytics , continuing the guidance we have offered for nearly two decades to help organizations derive optimal value from technology investments in order to improve business outcomes.

Marketing 285
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How to Successfully Deploy Data Science Projects

KDnuggets

This guide will provide detailed insight into the steps you can take to successfully manage your data science projects.

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KPIs vs Metrics: Understanding The Differences With Tips & Examples

datapine

Table of Contents. 1) What Are KPIs? 2) What Are Metrics? 3) KPIs vs Metrics: Main Differences. 4) Tips For KPI & Metrics Tracking. Performance tracking has never been easier. With the rise of modern self-service BI tools , everyone can monitor relevant performance indicators in a matter of seconds. But this is not without problems. Having the ability to analyze your data fast and efficiently doesn’t always mean you are doing it correctly.

Metrics 189
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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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Interactive Tweet Sentiment Visualization

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction With the advent of social media, a lot of data has been generated and is being generated. This data corresponds to either the opinion of people on political matters, on products they use, or on the services they use from companies. Mining this […]. The post Interactive Tweet Sentiment Visualization appeared first on Analytics Vidhya.

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The Digital Technology Market Agenda for 2022: Innovation for Business Resilience

David Menninger's Analyst Perspectives

I’m proud to share Ventana Research’s 2022 Market Agenda for Digital Technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that increase workforce effectiveness and organizational agility, ensuring ongoing operations during any type of disruption.

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5 Ways Where Data-Driven Analytics Reshaped The Software Industry

Smart Data Collective

Thanks to the rapid digital transformation , the software industry is one of the fastest-growing industries globally. Data analytics helps to determine the success of the business. Although the COVID-19 pandemic harmed several businesses, the software industry didn’t suffer much of a collapse. Digital technology has helped almost every industry.

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Implementing Logistic Regression from Scratch using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction on Logistic Regression If you are here, you are already introduced to the concept of logistic regression and probably have had your hands dirty working on different datasets. The scikitlearn’s LogisticRegression is by far the best tool to use for any logistic regression […].

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When to Use Paginated Reports vs Interactive Power BI reports

Paul Turley

Technology evolves, the industry changes and the way businesses use technology changes. The road that has brought us to the current state of reporting capabilities in the Microsoft data platform has been long and winding. Ten years ago, we were using SQL Server Reporting Services (SSRS) to create interactive, dashboard-like reports scorecard reports.

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How to Write SQL in Native Python

KDnuggets

If the idea of being able to link with SQL databases and define, manipulate, and query using Python sounds appealing, check out the SQLModel library.

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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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The 7 Stages of Data Projects

Juice Analytics

Why do data projects take so long? It’s exhausting — finding data, cleaning data, identifying problems in the data, creating presentations, hitting resistance.on and on. I’ve seen the struggle up close for over 15 years. It is my belief that the challenges of analytics have less to do with technology limitations and more to do with people challenges.

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Privacy-Preserving in Machine Learning (PPML)

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Overview Machine learning (ML) has a lot of potential for increasing productivity. However, the quality of the data for training ML models should be excellent to provide good results. Any ML algorithm provides excellent performance only when there is huge and perfect data fed […].

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How to Plan for Your Next Dashboard [Lea Pica’s Present Beyond Measure Podcast]

Depict Data Studio

You’ve been asked to make a dashboard—now what?! Dashboard is a tricky term; it means different things to different people. In this article, you’ll learn how to: choose between various dashboard types (static or interactive, single or series); and deal with common dashboard challenges. Lea Pica’s Present Beyond Measure Podcast. I recently had the chance to be on the Present Beyond Measure podcast, hosted by Lea Pica.

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Top Benefits of Using Docker for Data Science

Smart Data Collective

Docker is one of the two most popular DevOps platforms for data scientists. There are over nine million Docker accounts and the number of developers using Docker is growing 30% a year. There are a lot of compelling reasons that Docker is becoming very valuable for data scientists and developers. One of the reasons is that the configuration and user interface is so intuitive and convenient.

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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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If data is the new oil, ISO 20022 is the new gasoline

IBM Big Data Hub

The phrase ‘data is the new oil’ has been widely used in the last number of years, but in an unrefined state, it has limited use. ISO 20022 is refined and provides the necessary structure to efficiently drive multiple engines in a bank. Background on ISO 20022. ISO 20022 was first introduced in 2004 to provide more standardization and deliver richer information for Financial Services transactions.

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Statistical Inference Using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Hey folks! Data science is an emerging technology in the corporate society and it mainly deals with the data. Applying statistical analysis to data and getting insights from it is our main objective. A company wil store millions of records for analysis. A […]. The post Statistical Inference Using Python appeared first on Analytics Vidhya.

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Culture Eats Technology For Breakfast

Timo Elliott

A quick Friday reminder that we have to focus on what’s important, despite all the daily complexities and challenges of technology!… All too often I see projects failing not because the technologies aren’t working, but because not enough attention has been paid to the people being displaced. For example, several years ago an executive dashboard project was very nearly derailed by one of the executive assistants.

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Several IIoT Solutions That Help Your Business

Smart Data Collective

For the first time, the Internet of Things (IoT) appeared in 1999. The basis of this concept is data transmission between devices that allows them to gather, process, and analyze information using special equipment and software. In other words, the IoT system means connecting things (equipment) to the Internet for improving the quality of people’s life.

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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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Data Science Programming Languages and When To Use Them

KDnuggets

Read this guide through the most common data science programming languages and when to use them in data science.

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Deploy your ML model as a Web Service in Microsoft Azure Cloud

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. This article will provide you with a hands-on implementation on how to deploy an ML model in the Azure cloud. If you are new to Azure machine learning, I would recommend you to go through the Microsoft documentation that has been provided in the […]. The post Deploy your ML model as a Web Service in Microsoft Azure Cloud appeared first on Analytics Vidhya.

Modeling 330
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The Most Unique Snowflake

Cloudera

Okay, I admit, the title is a little click-batey, but it does hold some truth! I spent the holidays up in the mountains, and if you live in the northern hemisphere like me, you know that means that I spent the holidays either celebrating or cursing the snow. When I was a kid, during this time of year we would always do an art project making snowflakes.

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Data Analytics Helps Optimize Subscriber-Based Business Models

Smart Data Collective

The subscription market enjoys immense popularity. The one-time purchase method isn’t considered to be efficient within specific niches. Therefore, the subscription business model is changing how customers pay for the service they receive. The concept includes paying a small fee over the time of the relationship between the company and the customer.

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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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Artificial Intelligence and the Metaverse

KDnuggets

For those of you who don’t know, Artificial intelligence (AI) is the ability of a computer or a computer-controlled robot to perform tasks that are usually done by humans as they require human intelligence. Metaverse’s AI research and usage include content analysis, supervised speech processing, computer vision, and much more. .

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R Programming Concepts Made Easy!

Analytics Vidhya

Overview How is Type Casting done in R? Discussing about the Date datatype in R Understanding the concept of Encoding in R Introduction While the majority of the concepts remain somewhat similar across the various tools and technologies that we learn for data science, there are few concepts special to a particular tool or a […]. The post R Programming Concepts Made Easy!

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What Do We Talk About, When We Talk About Data?

Dataiku

Some people don’t engage with others on data and AI because they perceive a barrier between how they work with data and how they could work with data — call it an unrequited dream of something better. Others simply don’t think data and AI are relevant to their work at all, as neither appear in their job title. And sometimes even when people work on data and AI together, collaboration can be challenging because they use data for different things, and so they look at it in different ways.

IT 110
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Becoming an Intelligent, Sustainable Enterprise with SAP

Timo Elliott

Here’s my new overview of SAP, our customers, and technology explaining how SAP solutions can help you become an intelligent, sustainable enterprise — and full of real-world examples of organizations like yours who have already taken the plunge. And if you’d rather not listen to all that, here’s a full transcript: Enabling your success. Hello Everyone!

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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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Classifying Long Text Documents Using BERT

KDnuggets

Transformer based language models such as BERT are really good at understanding the semantic context because they were designed specifically for that purpose. BERT outperforms all NLP baselines, but as we say in the scientific community, “no free lunch”. How can we use BERT to classify long text documents?

Modeling 110
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Top 10 AI and Data Science Trends in 2022

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. In this article, we shall discuss the upcoming innovations in the field of artificial intelligence, big data, machine learning and overall, Data Science Trends in 2022. Times change, technology improves and our lives get better. Deep learning, natural language processing, and computer vision are examples […].

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Understanding the Principles of Data-Driven SEO in Web Design

Smart Data Collective

The intersection of different forms of technology is becoming more crucial for the future of marketing. One of the biggest changes is the combination of big data and search engine marketing. Search engine optimization has become a crucial form of marketing over the past 20 years. In addition to providing a steady stream of Internet traffic, SEO also converts very well.

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All Models Are Wrong, Some Are Useful… But Do We Know Which Ones?

Dataiku

From choosing AI projects that matter to building the models to deliver these projects, organizations often struggle to achieve real impact. At 2021’s Data Innovation Summit, I discussed what is standing in their way or, rather, what it is that they might be doing wrong.

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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.