September, 2022

Enhancing Data Catalog with AI

David Menninger's Analyst Perspectives

Organizations are collecting data from multiple data sources and a variety of systems to enrich their analytics and business intelligence (BI). But collecting data is only half of the equation. As the data grows, it becomes challenging to find the right data at the right time.

Data Science Use Cases in Forensic Analytics


Recruitment, training, and skill development, staffing, rewards, and benefits are all part of the standards, as is time to recruitment, cost per recruitment, participation rate, retention rate, addition rate, exchange rate, time to start, and offer.


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How is Big Data Helping in the Development of Healthcare?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon.

How to Correctly Select a Sample From a Huge Dataset in Machine Learning


We explain how choosing a small, representative dataset from a large population can improve model training reliability. KDnuggets Republished Machine Learning

4 Key Steps to Data Transformation Success with Data Mesh

It’s tougher than ever to give your clients the data and insight they need, when they need it (and how they want it) – while addressing issues like security. Find out how data mesh architectures can help you meet these challenges and more.

The New Cybersecurity Motto: Trust is Not an Option


The discovery of the Log4j vulnerability in December 2021 is one of the more recent and prominent reminders of why cybersecurity teams need to implement a zero-trust security architecture. Not that they should need reminders.

Editorial Review of “Building Industrial Digital Twins”

Rocket-Powered Data Science

[link]. I was asked by the publisher to provide an editorial review of the book “Building Industrial Digital Twins: Design, develop, and deploy digital twin solutions for real-world industries using Azure Digital Twins“, by Shyam Varan Nath and Pieter van Schalkwyk.

More Trending

Top 4 Considerations for Designing a Data Product


A data product is a tool or an application that processes data in a statistical way to generate future results. These results are aimed at helping businesses/organizations make better future decisions.

Blockchain Technology and its Types

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Blockchain technology is a decentralized, distributed ledger that keeps a record of ownership of digital assets.

New Phocas feature integrates sales and operational drivers


Capturing non-financial data from sales and operational teams isn’t easy. It’s typically a manual, time-consuming process where data often becomes out of date by the time it’s published.

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IT enters the era of intelligent automation


Since the outset of the pandemic, organizations have been increasingly launching initiatives aimed at automating business processes, turning to technologies such as robotic process automation (RPA) in efforts to reduce costs, speed up tasks, and improve accuracy of core business operations.

Monetizing Analytics Features: Why Data Visualization Will Never Be Enough

Five years ago, data visualizations were a powerful way to differentiate a software application. Today, free visualizations seem to be everywhere. Two trends are forcing application providers to rethink how they offer analytics in their products.

5 Data Science Skills That Pay & 5 That Don’t


This article will go over the top 5 data science skills that pay you and 5 that don’t. KDnuggets Originals Data Science

Augmented Intelligence Reduces Dependency on AI/ML Skill Sets

David Menninger's Analyst Perspectives

Business intelligence has evolved. It now includes a spectrum of analytics , one of the most promising of which has been described as augmented intelligence.

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How do We Annotate an Image


Business-specific image annotation customized to your automation goals – let custom image annotation experts bring you the aid to functionalize your AI model. Cogito specializes in image annotation technology and image annotation deep learning services. Introduction.

Analysis of Australian Shark Attacks

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Recently I searched for an interesting dataset to learn something new. After searching for a long time, I got a dataset on Shark Attacks in Australia.

The 2023 Supply Chain Crystal Ball: Challenges and Solutions

Speaker: Olivia Montgomery, Associate Principal Supply Chain Analyst

Curious to know how your peers are navigating ongoing disruption? In this webinar, you’ll gain actionable insights from Olivia Montgomery as she walks us through Capterra’s extensive research on how businesses - notably small and midsize businesses - are addressing supply chain challenges in 2023.

What is Driver Based Planning?


The devil is always in the detail, especially when it’s budgeting time. When we’re in business planning mode we’re looking at what worked well and what didn’t, as well as projecting most likely and stretch scenarios to plan the next year of cash flow.

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Data storytelling: A key skill for data-driven decision-making


To be a truly data-driven enterprise , organizations today must go beyond merely analyzing data. Rather, business experts and IT leaders must transform relevant data into compelling stories that key stakeholders can readily comprehend — and leverage to make better business decisions.

SQL vs NoSQL: 7 Key Takeaways


People assume that NoSQL is a counterpart to SQL. Instead, it’s a different type of database designed for use-cases where SQL is not ideal. The differences between the two are many, although some are so crucial that they define both databases at their cores. KDnuggets Originals SQL

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Cloud Computing Realities Part 2: Hybrid and Multi-Cloud Architectures

David Menninger's Analyst Perspectives

In my first perspective on cloud computing realities , I covered some of the cost considerations associated with cloud computing and how the cloud costing model may be different enough from on-premises models that some organizations are taken by surprise. In this perspective.

5 Powerful Prescriptive Analytics Examples in Supply Chain

Prescriptive analytics is a type of advanced analytics that optimizes decision-making by providing a recommended action. Supply chain, with its complex planning questions, is typically an area where optimization technology is required. Read about 5 use cases.

Digitalization in Healthcare Industry- What’s New in 2022


The rapid evolution of digital innovations has ensured the modification of systems, interactions, and processes associated with the health and wellness industry.

Underlying Engineering Behind Alexa’s Contextual ASR

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Conventionally, an automatic speech recognition (ASR) system leverages a single statistical language model to rectify ambiguities, regardless of context.

AI Meets Data Access Governance

The Data Administration Newsletter

Data is the viral sensation crashing the data governance capacity. Use of data is disrupting industries, economies, even some government elections. Unlocking the secrets data holds is the number one challenge in every single company regardless of the size or industry.

What is employee experience? A vital factor for business success


Employee experience has become a key factor in defining your company’s overall success. Positive or negative, employee experience can significantly impact your company’s productivity, efficiency, and its ability to recruit and retain talent.

Intent Signal Data 101

Intent signal data helps B2B marketers engage with buyers sooner in the sales cycle. But there are many confusing terms used to describe intent data. Read this infographic to better understand three common areas of confusion.

More Performance Evaluation Metrics for Classification Problems You Should Know


When building and optimizing your classification model, measuring how accurately it predicts your expected outcome is crucial. However, this metric alone is never the entire story, as it can still offer misleading results.

A Year After: Has Blockchain Changed Advertising by 2022?

Smart Data Collective

Last decade made a pretty bold promise to digital advertising, which more than other industries suffers from insufficient transparency and a fraudulent environment.

Using AI for Smarter Construction


Artificial intelligence has become a game changer for businesses in the construction industry. Earlier this year we told you about how AI is already being used to make construction sites safer.

Top Blockchain Interview Questions

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Blockchain technology is a decentralized, distributed ledger that preserves a record of digital asset ownership. It is a means to save data and information in a secure digital format.

Modern Data Architecture for Embedded Analytics

Data has gone from a mere result of applications & processes to being crowned king. Picking the right avenue to data architecture depends on your organization’s needs. Development teams should build in stages, starting with a task that can be solved.

How to Avoid Burning Out if You Are a Data Scientist


This is a guest article from Eric Kahuha. Kahuha is an ambitious data scientist and an experienced technical writer. His work has been published in many blogs. He writes highly technical yet easy-to-understand content for beginners and experts in the tech field. Data Basics Featured

American Airlines takes flight with analytics transformation


In the wake of the COVID-19 pandemic, airlines have struggled with bad weather, fewer air traffic controllers, and a shortage of pilots, all leading to an unprecedented number of cancelations in 2022.

How to Select Rows and Columns in Pandas Using [ ],loc, iloc,at and.iat


Subset selection is one of the most frequently performed tasks while manipulating data. Pandas provides different ways to efficiently select subsets of data from your DataFrame. KDnuggets Originals Python


What Are the Most Serious Privacy Concerns Regarding Big Data?

Smart Data Collective

Given the growing importance of big data and the rising reliance of businesses on big data analytics to carry out their day-to-day operations, it is safe to say that big data has irrevocably altered the online world for anyone running a digital enterprise or an e-business.

A Deep Dive Into Supply Chain Strategy: Why Yours Isn't Working

Speaker: Michelle Meyer, Founder and CEO of MatterProviders

Michelle Meyer is here to walk you through the future of supply chain strategy, and why your current approach is probably not working. In this exclusive webinar, she will explore ways to develop and perfect your new supply chain design in this post-pandemic era of economic uncertainty.