Tue.Jul 05, 2022

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Learn Everything about MapReduce Architecture & its Components

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction MapReduce is part of the Apache Hadoop ecosystem, a framework that develops large-scale data processing. Other components of Apache Hadoop include Hadoop Distributed File System (HDFS), Yarn, and Apache Pig. This component develops large-scale data processing using scattered and compatible algorithms in the […].

IT 396
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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

1. What is business analytics? Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Research firm Gartner defines business analytics as “solutions used to build analysis models and simulations to create scenarios, understand realities, and predict future states.”.

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Trending Sources

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Outliers and Overfitting when Machine Learning Models can’t Reason

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Datasets are to machine learning models what experiences are to human beings. Have you ever witnessed a strange occurrence? What exactly do you consider to be strange? What constitutes an odd event? Is it based on comparisons with uncommon circumstances or things that […].

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Data Preparation in R Cheatsheet

KDnuggets

Leverage the powerful data wrangling tools in R’s dplyr to clean and prepare your data.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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Managing SQL Database on Google Cloud

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction This article shows how you can create and manage a Cloud SQL Database on Google Cloud Platform and further connect that database to any web application. This tutorial shows how you can join that database with a Django Application. By the end […]. The post Managing SQL Database on Google Cloud appeared first on Analytics Vidhya.

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Location AI: The Next Generation of Geospatial Analysis

DataRobot Blog

Real world problems are multidimensional and multifaceted. Location data is a key dimension whose volume and availability has grown exponentially in the last decade. At the confluence of cloud computing, geospatial data analytics, and machine learning we are able to unlock new patterns and meaning within geospatial data structures that help improve business decision-making, performance, and operational efficiency.

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Domain-Driven Development, Part 1

TDAN

Bounded Contexts / Ubiquitous Language My new book, Data Model Storytelling,[i] contains a section describing some of the most significant challenges data modelers and other Data professionals face. One of these challenges is the increasing popularity of an approach to application development called Domain-Driven Development (DDD). Like most of its predecessors, including Agile development and […].

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Create Smart Contract Using Solidity Programming

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Blockchain is a decentralized, distributed public ledger that lets us collaborate and coordinate the members that do not trust each other to make a secure transaction. Many of you understand blockchain as a bitcoin, but bitcoin is a cryptocurrency that takes the help […].

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All About Decentralized Cybersecurity

TDAN

As an IT professional, you’re probably used to the constant treadmill of new ideas, technologies, and concepts that you need to know to stay on top of your game. In that vein, allow us to flag for you an important new way to think about keeping IT systems secure: Decentralized Cybersecurity. Read on for a […].

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Guide to the Intuitive Confusion Matrix

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to Confusion Matrix In a situation where we want to make discrete predictions, we often wish to assess the quality of our model beyond simple metrics like the model’s accuracy, especially if we have many classes. Oftentimes, we turn to plots of confusion […].

Metrics 362
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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

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Digital twin helps NTT Indycar deliver better race experience to fans

CIO Business Intelligence

When Marcus Ericsson, driving for Chip Ganassi Racing, won the Indianapolis 500 in May, it was in a car equipped with more than 140 sensors streaming data and predictive analytic insights, not only to the racing team but to fans at the Brickyard and around the world. NTT, which partners with Penske Entertainment for the NTT Indycar Series, including the Indy 500 race, collected an estimated 8 billion data points through the sensors on Ericsson’s car and that of his 32 competitors.

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Analysis of Imbalanced Datasets – Sample Size vs Accuracy

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to Imbalanced Datasets The accuracy achieved by many of the machine learning models using traditional statistical algorithms increases by just around 2% or so when the size of the training dataset is increased from 20% to 80%. But what about the classification algorithms […].

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The 7 Steps for an Analytics-led Digital Transformation

Teradata

In the current age of AI, all digital transformations must be analytics-led. Learn the 7 steps needed to realize the promise of an analytics-led digital transformation.

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Machine Learning Aided Differentiation of Real and Fake News

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Since the dawn of this millennium, technology has seen rapid advancement. This has led to the introduction of many news channels across different media viz. electronic including online and television, and print media. An increase in the number of platforms and channels has […].

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Developing an Open Standard for Analytics Tracking

KDnuggets

Striving for a new generic way to structure analytics data, so models built on one data set can be deployed and run on another.

Analytics 109
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The hidden history of Db2

IBM Big Data Hub

In today’s world of complex data architectures and emerging technologies, databases can sometimes be undervalued and unrecognized. The fact is that databases are truly the engine driving better outcomes for businesses — they’re running your cloud-native apps, generating returns on your investments in AI, and the backbone supporting your data fabric strategy.

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What It Takes to Be a Winner in Tech

CIO Business Intelligence

Claire Blythe, VP, global tech and operations at GfK (the AI-powered intelligence platform revolutionizing real-time access to critical knowledge), won Role Model of the Year at Computing ’s recent Women in Tech Excellence awards. We ask for her secrets to success in technology leadership, and how women can rapidly advance their careers in the field.

IT 93
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Linear Regression for Data Science

KDnuggets

In this article, we discuss the importance of linear regression in data science and machine learning.

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Driving Business Impact for PMs

Speaker: Jon Harmer, Product Manager for Google Cloud

Move from feature factory to customer outcomes and drive impact in your business! This session will provide you with a comprehensive set of tools to help you develop impactful products by shifting from output-based thinking to outcome-based thinking. You will deepen your understanding of your customers and their needs as well as identifying and de-risking the different kinds of hypotheses built into your roadmap.

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4 stories all CIOs should be able to tell

CIO Business Intelligence

Master storyteller Doug Keeley was a featured speaker at a large national sales meeting some years ago when he noticed how miserable everyone was feeling. “Morale was horrible,” he recalls. “There was a new leader taking over, and her opening keynote had bombed. Everyone thought this CEO was cold and lacking empathy.”. The only way to turn it around, Keeley was convinced, was to get the CEO back on stage for a more personal conversation.

Finance 90
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How to Measure Dataset Similarity: Understanding the Impact of Drift on ML Models

Dataiku

Measuring similarity between two datasets is critical in many ML fields, such as detecting dataset shift and evaluating its impact on a model’s performance. This article describes various datasets’ similarity measures and how they can be leveraged for distribution shift detection and model performance drop.

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Digital transformation never stops at IBM’s semiconductor plant in Québec

CIO Business Intelligence

Technological innovation is at the heart of IBM Bromont. Founded in 1972 to meet the needs of the Canadian computer market, the plant has evolved over the years to climb the hierarchy of the computer behemoth – setting itself apart from competitors who have fled North America to Asian countries in the last decades. Today, IBM assembles and tests its semiconductor solutions in the quaint town of Bromont, an hour from Montréal, and provides services to clients – notably in the telecommunications i

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What is Quantum Computing good for?

CONTACT Software

When it comes to quantum computing (QC), after the quite real breakthroughs in hardware and some spectacular announcements under titles like “Quantum Supremacy“, the usual hype cycle has developed with a phase of vague and exaggerated expectations. I would like to briefly outline here why the enormous effort is being made in this area and … Continue reading "What is Quantum Computing good for?".

IT 52
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Reimagined: Building Products with Generative AI

“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.

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À l’usine de semi-conducteurs d’IBM au Québec, la transformation numérique est permanente

CIO Business Intelligence

L’innovation technologique est au cœur d’IBM Bromont. Fondée en 1972 pour répondre aux besoins du marché canadien en ordinateurs, l’usine a évolué au fil des ans pour grimper les échelons de la hiérarchie du colosse informatique – se démarquant de l’ensemble de ses concurrents qui ont tous fui l’Amérique du Nord vers l’Asie dans les dernières décennies.

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Data Professional Introspective: Data Provider Management – Part 1

TDAN

Why Your Organization Suffers This series of columns addresses an essential function that many organizations neglect, an overlooked set of processes to manage the lifecycle of data acquisition and maintenance. We’ll make the case for why this function is important, and we’ll define essential concepts and activities inherent in managing and optimizing acquired data– to […].

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4 new IT workforce realities

CIO Business Intelligence

Every day the headlines remind us just how fragile/broken the human supply chain is. At the height of the pandemic we discovered severe shortages of truck drivers, meat packers, and emergency room nurses. As we limp through the frustratingly elongated ramp toward a post-COVID world we are experiencing significant shortages of coders, butchers, bakers, pilots, waiters/waitresses, hospitality workers, cashiers and tax preparers/reviewers.

IT 87
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The Book Look: The Data Path Less Traveled

TDAN

When is an answer “good enough”? There are many areas of data science and AI where we need to be satisfied with an answer that is not perfect and yet still provides business value. The data scientist’s problems are often not solved with straightforward statistics and are instead much more complex. That’s where heuristics excel. […].

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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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What is a chief administrative officer? A strategic executive role for operations

CIO Business Intelligence

What is a CAO? A chief administrative officer (CAO) is a top-level executive responsible for overseeing the day-to-day operations of an organization and the company’s overall performance. CAOs are responsible for managing an organization’s finances as well as creating goals, policies, and procedures for the company to help it operate more efficiently and compliantly.

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Get People to Be Data Stewards

TDAN

Few organizations have all the technical and functional data stewards in place to handle the ever-increasing data-related questions and requests. Therefore, a search for new data stewards is probably always happening. This blog post will discuss how you can get data stewardship acceptance by an individual. In an organization where a data steward role does […].

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The four pillars of optimised enterprise computing

CIO Business Intelligence

The world has become far more complicated. For businesses, the need to balance employee safety, changed expectations about how and where we work, and the shifting threat landscape have transformed the very nature of how we use our computers. While users have always wanted safe, reliable and high performing PCs and notebooks, delivering this in the post-pandemic world poses an immense challenge.

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Safely Driving Infonomic Growth with Data Access Governance and Security

TDAN

As enterprises race to become data-driven businesses, a latent tension is intensifying: Is data the “new oil”? A “toxic asset”? Both? Whichever metaphor you would like to use, what is certain is that no organization will survive the twenty-first century without optimizing the use of its data assets. Similarly, cybersecurity, privacy, and compliance risks increasingly present huge […].

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Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity

Speaker: Nicholas Zeisler, CX Strategist & Fractional CXO

The first step in a successful Customer Experience endeavor (or for that matter, any business proposition) is to find out what’s wrong. If you can’t identify it, you can’t fix it! 💡 That’s where the Voice of the Customer (VoC) comes in. Today, far too many brands do VoC simply because that’s what they think they’re supposed to do; that’s what all their competitors do.