Sat.Mar 19, 2022 - Fri.Mar 25, 2022

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Get to Know About Modern Data Governance

Analytics Vidhya

Introduction Given the world’s growing user base across devices and applications in recent years, we have seen a huge surge in not just the volume of data we are collecting but also in the number and variety of sources. The pandemic has certainly accelerated this trend even more and having high quality and consistency […]. The post Get to Know About Modern Data Governance appeared first on Analytics Vidhya.

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Working Across the Aisle in Analytics: Involving IT and LOB

David Menninger's Analyst Perspectives

For years, maybe decades, we have heard about the struggles between IT and line-of-business functions. In this perspective, we will look at some of the data from our Analytics and Data Benchmark Research about the roles of IT and line-of-business teams in analytics and data processes. We will also look at some of the disconnects between these two groups.

Analytics 287
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What Is The Difference Between Business Intelligence And Analytics?

datapine

Table of Contents. 1) What Is Business Intelligence And Analytics? 2) BI vs BA As Seen Through Football. 3) BI And BA Main Differences. 4) How Do BI And BA Apply To Business? 5) BI And BA Use-Case Scenarios. 6) BI And BA Examples. If someone puts you on the spot, could you tell him/her what the difference between business intelligence and analytics is?

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WTF is a Tensor?!?

KDnuggets

A tensor is a container which can house data in N dimensions, along with its linear operations, though there is nuance in what tensors technically are and what we refer to as tensors in practice.

IT 160
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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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Operating on the Pandas DataFrame in Python

Analytics Vidhya

Overview DataFrame in Python Performing Data Cleaning Operations on the Pandas DataFrame Introduction Undoubtedly, a DataFrame in python is the most important structure used to store the data because it is used in all practical cases to store our given data set which we will be using for creating our models. It is defined under […]. The post Operating on the Pandas DataFrame in Python appeared first on Analytics Vidhya.

Modeling 379
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Engineering a Successful New Car: Starting a New F1 Season with McLaren Racing

DataRobot Blog

The 2022 season ignited a world of changes for McLaren Racing and Formula 1 with the biggest reengineering in modern F1 history. Each team now has a budget cap, and significant rule changes have been introduced, altering strategies and adding excitement for the fans. Another change that we’re thrilled about is that DataRobot is one of McLaren’s newest partners.

More Trending

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A Guide On How To Become A Data Scientist (Step By Step Approach)

KDnuggets

Becoming a Data Scientists is an exciting path, but you cannot learn data science within one year or six months—instead, it’s a lifetime process that you have to follow with proper dedication and hard work. To guide your journey, the skills outlined here are the first you must acquire to become a data scientist.

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Keyword Extraction Methods from Documents in NLP

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Keyword extraction is commonly used to extract key information from a series of paragraphs or documents. Keyword extraction is an automated method of extracting the most relevant words and phrases from text input. It is a text analysis method that involves automatically extracting […].

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Big Data Makes Smart Buildings the Norm in the 21st Century

Smart Data Collective

You have probably heard a lot talk about the Internet of Things (IoT). It is one of the biggest trends driven by big data. It is popular because billions of devices will be connected in the future. The IoT sector is predicted to generate over £7.5 trillion across the world. In fact, McKinsey Global predicts homes, offices, worksites, retail settings, and factories to generate around £3.55 trillion by the end of 2025.

Big Data 138
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Modernizing the mainframe for the digital era

CIO Business Intelligence

Sonny Sonnenstein is not a mainframe guy. “I’m a banking technologist,” says the CIO for retail, business, and digital banking at M&T Bank. But it is safe to say that Sonnenstein understands something about investment risk and when it’s time to double down on a strong hand. He’s doing just that on the bank’s IBM Z system mainframes, for which the bank has written some 10 million lines of code over the years.

Strategy 144
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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 Range of NLP Applications in the Real World: A Different Solution To Each Problem

KDnuggets

Most companies look at it like it’s one big technology, and assume the vendors’ offerings might differ in product quality and price but ultimately be largely the same. Truth is, NLP is not one thing; it’s not one tool, but rather a toolbox.

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A Hands-on Introduction to Reinforcement Learning with Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Dear readers, In this blog, we will get introduced to reinforcement learning and also implement a simple example of the same in Python. It will be a basic code to demonstrate the working of an RL algorithm. Brief exposure to object-oriented programming in Python, […]. The post A Hands-on Introduction to Reinforcement Learning with Python appeared first on Analytics Vidhya.

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AI Advances Lead To Improvements in E-Signatures

Smart Data Collective

With the advancement of digital technology, electronic signatures (e-signatures) have gained massive acceptance in the business world, where artificial intelligence (AI) further leads its improvements. What Are E-Signatures? E-signatures, or the digitized or scanned version of handwritten signatures, improve business processes, allowing fast signing and approval of documents.

IoT 127
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Nvidia speeds AI, climate modeling

CIO Business Intelligence

It’s been years since developers found that Nvidia’s main product, the GPU, was useful not just for rendering video games but also for high-performance computing of the kind used in 3D modeling, weather forecasting, or the training of AI models—and it’s on enterprise applications such as those that CEO Jensen Huang will focus his attention at the company’s GTC 2022 conference this week.

Modeling 144
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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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GitHub Copilot Open Source Alternatives

KDnuggets

GitHub's Copilot code generation tool is currently only available via approved request. Here are 4 Copilot alternatives that you can use in your programming today.

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Decision Tree Machine Learning Algorithm Using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In this article, we are going to learn about Decision Tree Machine Learning algorithm. We will build a Machine learning model using a decision tree algorithm and we use a news dataset for this. Nowadays fake news spread is like wildfire and this […]. The post Decision Tree Machine Learning Algorithm Using Python appeared first on Analytics Vidhya.

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The Telecommunications Service Provider Journey – From Telco to Techco

Cloudera

Earlier this month, the multi-national carrier MTN announced a rebranding, and along with its logo refresh, announced that it was moving to focus on being a technology provider. The new look, “aligns with our evolution from a telecommunications company to a technology company,” said Nompilo Morafo, Chief Corporate Affairs officer at the company. Across APAC too, telcos are looking at the shift to becoming technology companies, and last week’s TMForum Leadership Summit “ The Tech Driven Telco ” s

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Google’s Contact Center AI Platform aims to optimize customer service

CIO Business Intelligence

In a bid to help enterprises optimize customer service, Google Cloud is extending its Contact Center AI (CCAI) service with the ability to integrate with CRM (customer relationship management) applications in order to provide real-time insights and data analytics. The extended service will be called the Contact Center AI (CCAI) Platform and is scheduled for general availability in August.

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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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Linear vs Logistic Regression: A Succinct Explanation

KDnuggets

Linear Regression and Logistic Regression are two well-used Machine Learning Algorithms that both branch off from Supervised Learning. Linear Regression is used to solve Regression problems whereas Logistic Regression is used to solve Classification problems. Read more here.

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Women Leaders in Data Science: Top 10 Influentials from the Industry

Analytics Vidhya

Introduction The thriving industry of Data Science is continuously evolving with the technological advancements in Machine Learning and Artificial intelligence. This has opened up whole new avenues for Data Scientists worldwide. Professionals who can handle Big Data and have the necessary knowledge required for understanding, analysing and processing data are in high demand in the […].

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Is It Possible to Fully Protect Your Data Nowadays?

Smart Data Collective

Keeping your data safe now is more challenging than ever. We keep a lot of our data on hackable devices, such as mobile phones and computers. One weak password or a phishing attack on our emails is enough to breach and expose our information and have it land in the wrong hands. We also give a lot of our information away to various companies and services we use online.

IT 125
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What is a data scientist? A key data analytics role and a lucrative career

CIO Business Intelligence

What is a data scientist? Data scientists are analytical data experts who use data science to discover insights from massive amounts of structured and unstructured data to help shape or meet specific business needs and goals. Data scientists are becoming increasingly important in business, as organizations rely more heavily on data analytics to drive decision-making and lean on automation and machine learning as core components of their IT strategies.

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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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The Most Popular Intro to Programming Course From Harvard is Free!

KDnuggets

CS50's Introduction to Computer Science has the highest enrollment on Harvard's campus. and is free to anyone interested in taking it!

IT 158
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Introductory Note to Image Classification Using Fast ai

Analytics Vidhya

Introduction Training a Deep Learning model from scratch can be a tedious task. You have to find the right training weights, get the optimal learning rates, find the best hyperparameters and the architecture that will best suit your data and model. Put it along with not having enough quality data to train and the computational […]. The post Introductory Note to Image Classification Using Fast ai appeared first on Analytics Vidhya.

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5 Data Mining Tips to Leverage the Benefits of Surveys

Smart Data Collective

Advancements in technology have allowed it to store and collect databases in many fields. If we count the number of data on the web, it is probably a number that we have never heard of. However, it’s all about the quality and not the quantity when collecting data. Moreover, some companies are sitting on loads of consumer data and don’t know what to do with it.

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7 traits of indispensable IT leaders

CIO Business Intelligence

There’s no better type of job security than indispensability. Once an IT leader is regarded as essential by his or her employer, recognition rises, colleagues begin listening, project doors swing open, and salaries and benefits skyrocket. Achieving indispensability isn’t as challenging as it may sound. It can be easily acquired by embracing several common traits that have been proven to transform mere mortals into IT heroes.

IT 133
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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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Why Are So Many Data Scientists Quitting Their Jobs?

KDnuggets

After speaking to co-workers in the data industry who like me, had left their jobs at a very early stage in their career, I’ve come to realize that there are two main reasons the data science field has such a high employee attrition rate.

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Dog Breed Classification Using a Stacked Pre-Trained Model

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. An end-to-end guide on dog breed classification using stacked pre-trained CNN models […]. The post Dog Breed Classification Using a Stacked Pre-Trained Model appeared first on Analytics Vidhya.

Modeling 303
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How Machine Learning is Used in Smart Home Automation

Smart Data Collective

Smart home automation has become quite popular in recent years, moving from a luxury for the rich to a staple in many homes. The most popular smart home devices are speakers and thermostats, but a growing number of people are adopting other smart devices like door locks and security cameras. Residential smart home automation has become a massive industry, and it’s not hard to implement.

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6 steps for getting troubled projects back on track

CIO Business Intelligence

Delays are common in project management, regardless of what sector you’re working in. But once a project has fallen behind, what can you do as a project manager to get your wayward project back on track? It’s often easier said than done, but it’s important not to panic; calm heads always prevail, as they say. But still, time is of the essence when a project is falling behind, so it is vital to not delay taking action; otherwise, your organization will be susceptible to potentially very costly co

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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.