April, 2022

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Is Quantum Computing the Future of Artificial Intelligence?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Source: Forbes.com Introduction It is not hidden from the audience that quantum computing is the future of data processing. Tech giants like IBM, Google, and Microsoft are all aggressively pursuing quantum computing technology for a good reason. The massive speedups and power savings of quantum […].

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10 Big Data Examples Showing The Great Value of Smart Analytics In Real Life At Restaurants, Bars, and Casinos

datapine

“You can have data without information, but you cannot have information without data.” – Daniel Keys Moran. When you think of big data, you usually think of applications related to banking, healthcare analytics , or manufacturing. After all, these are some pretty massive industries with many examples of big data analytics, and the rise of business intelligence software is answering what data management needs.

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The Next Wave of ‘Ops’ Advances on the Data Center

DataKitchen

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Data Scientist, Data Engineer & Other Data Careers, Explained

KDnuggets

In this article, we will have a look at five distinct data careers, and hopefully provide some advice on how to get one's feet wet in this convoluted field.

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Apache Airflow®: The Ultimate Guide to DAG Writing

Speaker: Tamara Fingerlin, Developer Advocate

In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!

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Don’t Fear Artificial Intelligence; Embrace it Through Data Governance

CIO Business Intelligence

As someone who is passionate about the transformative power of technology, it is fascinating to see intelligent computing – in all its various guises – bridge the schism between fantasy and reality. Organisations the world over are in the process of establishing where and how these advancements can add value and edge them closer to their goals. The excitement is palpable.

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7 Data Lineage Tool Tips For Preventing Human Error in Data Processing

Smart Data Collective

Errors in data entry might have serious effects if they are not discovered quickly. Human mistake is the most common cause of data entry errors. Since typical data entry errors may be minimized with the right steps, there are numerous data lineage tool strategies that a corporation can follow. The steps organizations can take to reduce mistakes in their firm for a smooth process of business activities will be discussed in this blog.

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A Complete Guide To Driving Digital Transformation In Marketing

datapine

Digital transformation is a broad term that is difficult to define precisely. Think of digital transformation as a way to future-proof a business. But, you can consider it a change in the business activities to prioritize your business’s digital presence. Various industries and departments use this phrase in different ways. For instance, when it comes to Human Resources, a digital transformation entails streamlining operations and digitizing personnel data.

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Dapper Data Podcast: DataKitchen and DataOps – Episode #54 w/ Chris Bergh

DataKitchen

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15 Python Coding Interview Questions You Must Know For Data Science

KDnuggets

Solving the Python coding interview questions is the best way to get ready for an interview. That’s why we’ll lead you through 15 examples and five concepts these questions cover.

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15 best data science bootcamps for boosting your career

CIO Business Intelligence

An education in data science can help you land a job as a data analyst , data engineer , data architect , or data scientist. The data science path you ultimately choose will depend on your skillset and interests, but each career path will require some level of programming, data visualization, statistics, and machine learning knowledge and skills. Data engineers and data architects spend more time dealing with code, databases, and complex queries, whereas data analysts and data scientists typical

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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What Artificial Intelligence can Help Businesses Manage Their Online Profiles

Smart Data Collective

A lot of factors go into building a business, but online reputation is a huge part of it. A lot of organizations don’t recognize the role that AI technology can play when it comes to business management, improving customer relationships and managing your business’s online profile. Customers tend to Google an organization prior to engaging with their services.

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Introduction to SQL for Data Engineering

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In this article, we will be looking for a very common yet very important topic i.e. SQL also pronounced as Ess-cue-ell. So this time I’ll be answering some of the factual questions about SQL which every beginner needs to know before getting […]. The post Introduction to SQL for Data Engineering appeared first on Analytics Vidhya.

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Telco 5G Returns Will Come from Enterprise Data Solutions

Cloudera

This blog post was written by Dean Bubley , industry analyst, as a guest author for Cloudera. . Communications service providers (CSPs) are rethinking their approach to enterprise services in the era of advanced wireless connectivity and 5G networks, as well as with the continuing maturity of fibre and Software-Defined Wide Area Network (SD-WAN) portfolios. .

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The 7 Myths of MLOps

Dataiku

MLOps is a term that is gaining a lot of traction, but definitions of the concept remain blurry and many misleading myths are circulating. In “The 7 Myths of MLOps,” a recent Dataiku Product Days session, we have aimed to set the record straight with some reality checks and myth-busting. This blog recaps the useful information revealed in the session.

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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 8 Basic Statistics Concepts for Data Science

KDnuggets

Understanding the fundamentals of statistics is a core capability for becoming a Data Scientist. Review these essential ideas that will be pervasive in your work and raise your expertise in the field.

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Top 8 customer data platforms

CIO Business Intelligence

The world of marketing is awash in data. The solution? Embrace a customer data platform. Or at least some companies say. A customer data platform (CDP) is a software system that pulls together data from a wide array of sources — such as websites, ecommerce and ad platforms, social media applications, retail software, and more — to create a centralized customer database, as well as detailed profiles of each customer.

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10 Important Ways Data Visualization Can Benefit Your Content Strategy

Smart Data Collective

Data visualization has become a major part of life for those looking to make use of the large swathes of data available in the modern world. As important as this data is, understanding and making use of that data is even more important. That’s where data visualization comes in. Data visualization is, to put it simply, converting hard data and lists of numbers or facts, into an easier to comprehend form.

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Object Detection Using Haar Cascade: OpenCV

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In this article, we will discuss how to implement a haar cascade for object detection in OpenCV. In the last article, we discussed real-time object classification, if you haven’t read it yet, the link is here. Source: Link Identifying a custom object […]. The post Object Detection Using Haar Cascade: OpenCV appeared first on Analytics Vidhya.

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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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Denodo Advancing Data Virtualization in the Cloud

David Menninger's Analyst Perspectives

Organizations have been using data virtualization to collect and integrate data from various sources, and in different formats, to create a single source of truth without redundancy or overlap, thus improving and accelerating decision-making giving them a competitive advantage in the market. Our research shows that data virtualization is popular in the big data world.

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Becoming an AI-first Organization

Cloudera

The term “AI-first” has received its share of attention lately, especially in the boardroom where strategies to gain a competitive advantage are always welcome. But before a company embarks on an AI-first strategy, it pays to understand what it is and how it will transform the organization. If you’re AI-first, that means you have figured out how to leverage artificial intelligence to boost organizational agility so you can continuously adapt operational processes to deliver the right business ou

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Machine Learning Books You Need To Read In 2022

KDnuggets

I have a list of Machine Learning books you need to read in 2022; beginner, intermediate, expert, and for everybody.

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7 secrets of successful digital transformations

CIO Business Intelligence

Organizations that continued full speed ahead with their digital transformation initiatives during the COVID-19 pandemic are able to ruminate on what went right and what they would have done differently, with the benefit of hindsight. Some of what they’ve gleaned comes as no surprise: A successful digital transformation requires executive buy-in, constant communication with business units, and of course, financial commitment.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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AI is Creating Powerful New Online Time Tracking Tools

Smart Data Collective

Artificial intelligence technology has been instrumental in driving many important changes in our daily lives. We use a ton of online tools and mobile apps that rely heavily on AI technology. How important has AI been in transforming mobile apps and online tools? One study from Gartner found that it increased 270% between 2015 and 2019. Online time tracking apps are among those that use AI technology to improve the customer experience and offer the best service.

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Building Vehicle Counter System Using OpenCV

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In this article, we are going to build a vehicle counter system using OpenCV in Python using the concept of Euclidean distance tracking and contours. In the last article, we talked about object detection in OpenCV using haar cascades, if you haven’t […]. The post Building Vehicle Counter System Using OpenCV appeared first on Analytics Vidhya.

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What is Model Risk and Why Does it Matter?

DataRobot Blog

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. When business decisions are made based on bad models, the consequences can be severe.

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Why It Is Worth Making Great Customer/Client Reporting

Juice Analytics

?????? Customer or client reporting is the healthy eating of business. It is often the last thing organizations want to do because it is hard to do well and reveals hard truths. But like eating well, it is among the most important, valuable things you can do to create alignment internally and externally. So why don’t more organizations make the effort to eat their greens?

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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 Determine the Best Fitting Data Distribution Using Python

KDnuggets

Approaches to data sampling, modeling, and analysis can vary based on the distribution of your data, and so determining the best fit theoretical distribution can be an essential step in your data exploration process.

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7 famous analytics and AI disasters

CIO Business Intelligence

In 2017, The Economist declared that data, rather than oil, had become the world’s most valuable resource. The refrain has been repeated ever since. Organizations across every industry have been and continue to invest heavily in data and analytics. But like oil, data and analytics have their dark side. According to CIO’s State of the CIO 2022 report, 35% of IT leaders say that data and business analytics will drive the most IT investment at their organization this year.

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What Are the Best Methods To Keep Online Data Safe?

Smart Data Collective

Although we’re only a few months into 2022, this year has already seen massive cyberattacks, huge ransomware payouts, and data breaches never witnessed before. On average, damages due to cyberattacks are growing by 15% per year, with a predicted total value of $10.5 trillion lost each year by 2025. Across the different formats of cybercrime, one continual contender is data breaches, with 60% of businesses that experience any form of data breach going out of business in the following six months.

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A Comprehensive Overview of Sentiment Analysis

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction We can clearly see that sentiment analysis is getting more and more popular as e-commerce, SaaS solutions, and digital technologies advance. We’ll go through how this works and look at some of the most common corporate applications. We’ll also discuss the analysis’ […].

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What Is Entity Resolution? How It Works & Why It Matters

Entity Resolution Sometimes referred to as data matching or fuzzy matching, entity resolution, is critical for data quality, analytics, graph visualization and AI. Learn what entity resolution is, why it matters, how it works and its benefits. Advanced entity resolution using AI is crucial because it efficiently and easily solves many of today’s data quality and analytics problems.