November, 2022

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What are Smart Contracts in Blockchain?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Source: Image by Gerd Altmann from Pixabay Smart contracts are blockchain-based computer programs that activate at predefined times. In most cases, they are used to eliminate the need for a third party during the execution of a contract, allowing all parties to […].

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7 enterprise data strategy trends

CIO Business Intelligence

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. As with just about everything in IT, a data strategy must evolve over time to keep pace with evolving technologies, customers, markets, business needs and practices, regulations, and a virtually endless number of other priorities.

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IBM Builds on Analytics and BI Foundation

David Menninger's Analyst Perspectives

In today’s data-driven world, organizations need real-time access to up-to-date, high-quality data and analysis to keep pace with changing market dynamics and make better strategic decisions. By mining meaningful insights from enterprise data quickly, they gain a competitive advantage in the market. Yet, organizations face a multitude of challenges when transitioning into an analytics-driven enterprise.

Analytics 278
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Systems Thinking and Data Science: a partnership or a competition?

Jen Stirrup

Information is pretty thin stuff, unless mixed with experience. – Clarence Day (1874–1935), American essayist. Why do organizations get stuck with their data? It is such a fundamental question. Often, this problem can be due to the organization concentrating solely on technology and data. However, organizations can be supported by a synergistic approach by integrating systems thinking with the data strategy and technical perspective.

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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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 Google Recommends You do Before Taking Their Machine Learning or Data Science Course

KDnuggets

First steps to learning data science & machine learning are the foundations.

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What to Look for in a Data-Savvy Fintech Marketing Agency

Smart Data Collective

Big data technology has changed the future of marketing in a multitude of ways. A growing number of organizations are leveraging big data to get higher ROIs from their organic and paid marketing campaigns. As a result, companies around the world spent over $52 billion on data-driven marketing solutions in 2021. The Fintech sector is among those most reliant on data-driven marketing.

Marketing 143

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Human and AI Partnerships Are Integral to the Future of Customer Experience

CIO Business Intelligence

The age-old debate on technology versus human capability remains inconclusive. But in this time of artificial intelligence (AI), analytics, and cloud, we’re seeing more opportunities to think of how humans and machines can come together as a team, rather than acting against each other. From diagnosing diseases and delivering effortless customer experiences to understanding human preferences and providing new customer insights, the human and AI partnership is evolving — and more in sync than ever

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Mind the Gap Between Data and Analytics

David Menninger's Analyst Perspectives

If you’ve ever been to London, you are probably familiar with the announcements on the London Underground to “mind the gap” between the trains and the platform. I suggest we also need to mind the gap between data and analytics. These worlds are often disconnected in organizations and, as a result, it limits their effectiveness and agility.

Analytics 335
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A Complete Guide To Finding The Product Metrics That Matter

datapine

Table of Contents. 1) What Are Product Metrics? 2) Types Of Product Metrics. 3) Product Metrics Examples You Can Use. 4) Product Metrics Framework. Managing to develop an effective product roadmap goes beyond a product manager’s (PM) vision or intuition, even if these aspects matter as well. In an increasingly data-driven business world, the product management field isn’t exempt from this need.

Metrics 141
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How Much Math Do You Need in Data Science?

KDnuggets

There exist so many great computational tools available for Data Scientists to perform their work. However, mathematical skills are still essential in data science and machine learning because these tools will only be black-boxes for which you will not be able to ask core analytical questions without a theoretical foundation.

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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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Why Big Data Is The Future Of Sales And Marketing

Smart Data Collective

Proper marketing and sales prospects play a huge role in improving the success rate of your business. The strategy can either be offline or digital. However, digital marketing has become the major focus of marketers across all industries, mainly due to how customers interact and engage with modern businesses. Seeing an opportunity and knowing how and when to take advantage of it defines the majority of where today’s marketers stand.

Big Data 141
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How does User Authentication work with FACEIO?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction FaceIO is a cross-browser framework for user facial recognition authentication. Any website can use a JavaScript snippet to implement it. As more and more daily tasks are managed electronically rather than with pen and paper or face-to-face, the demand for quick and […].

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Leaning into Retail’s Challenges with Digital Transformation

CIO Business Intelligence

Digital transformation initiatives have picked up in the retail sector in recent years as store chains compete for brand awareness and sales in a rapidly evolving market. By 2026, retailers’ global investments in digital transformation tools are expected to reach $388 billion , growing by 18% a year. That may sound like retail leaders are all in , ready to use new technology tools to extract maximum value out of their operations; ready to embrace change and grab the future by the horns.

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Cloud Computing Realities Part 3: Business Continuity

David Menninger's Analyst Perspectives

In my previous perspectives on cloud computing, I addressed some of the realities of cloud costs as well as hybrid and multi-cloud architectures. In the midst of the pandemic, my colleague, Mark Smith, authored a series of perspectives on considerations for business continuity in general, beginning with this look at some of the investments organizations must make to mitigate the risk of business disruptions.

Risk 289
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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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DataOps Observability: Taming the Chaos (Part 4)

DataKitchen

Part 4: Reviewing the Benefits. This is the final post in DataKitchen’s four-part series on DataOps Observability. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately.

Testing 130
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10 Amazing Machine Learning Visualizations You Should Know in 2023

KDnuggets

Yellowbrick for creating machine learning plots with less code.

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Data Analytics Solves Manufacturing Marketing Agency Challenges

Smart Data Collective

Data analytics is unquestionably one of the most disruptive technologies impacting the manufacturing sector. Manufacturers are projected to spend nearly $10 billion on analytics by the end of the year. Data analytics can solve many of the biggest challenges that manufacturers face. One of the most significant benefits of leveraging analytics in manufacturing is with marketing optimization and automation.

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Hierarchical Clustering in Machine Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Hierarchical clustering is one of the most famous clustering techniques used in unsupervised machine learning. K-means and hierarchical clustering are the two most popular and effective clustering algorithms. The working mechanism they apply in the backend allows them to provide such a […].

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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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Leveraging Content Management Software to Facilitate a Cloud-First Approach

CIO Business Intelligence

By Milan Shetti, CEO Rocket Software In today’s fast-paced digital business world, organizations have become highly adaptive and agile to keep up with the ever-evolving demands of consumers and the market. This has pushed many organizations to accelerate their digital transformation efforts in order to remain competitive and better serve their constituents — and there is no sign of slowing down.

Software 144
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Automation With A Human Touch: Balancing Agility And Standardization

Timo Elliott

Simon Jarke is the Head of Corporate Digital Business Innovation at Freudenberg, a family-owned global technology group headquartered in Germany and founded in 1849. He recently explained how the organization has taken advantage of the latest technology advances to give business people more agility and control over their processes, without sacrificing standardization and efficiency: “I think the key to success, especially in times of digital transformation, lies in the philosophy and pract

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DataOps Observability: Taming the Chaos (Part 3)

DataKitchen

Part 3: Considering the Elements of Data Journeys. This is the third post in DataKitchen’s four-part series on DataOps Observability. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately.

Testing 130
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Introduction to Pandas for Data Science

KDnuggets

The Pandas library is core to any Data Science work in Python. This introduction will walk you through the basics of data manipulating, and features many of Pandas important features.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

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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Is Artificial Intelligence Setting A New Standard For Web Design?

Smart Data Collective

Artificial intelligence is playing an important role in modern creative professions. There are a lot of reasons a growing number of companies are turning to AI technology. One poll showed that 61% of companies found that AI and machine learning were their best data investments. One of the industries that is evolving by adopting new AI tools in web design.

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Top Interview Questions on Voting Ensembles in Machine Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Voting ensembles are the ensemble machine learning technique, one of the top-performing models among all machine learning algorithms. As voting ensembles are the most used ensemble techniques, there are lots of interview questions related to this topic that are asked in data […].

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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

Decision support systems definition A decision support system (DSS) is an interactive information system that analyzes large volumes of data for informing business decisions. A DSS supports the management, operations, and planning levels of an organization in making better decisions by assessing the significance of uncertainties and the tradeoffs involved in making one decision over another.

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Scoring More Goals in Football with AI: Predicting the Likelihood of a Goal Based on On-the-Field Events

DataRobot Blog

Can artificial intelligence predict outcomes of a football (soccer) game? In a special project created to celebrate the world’s biggest football tournament, the DataRobot team set out to determine the likelihood of a team scoring a goal based on various on-the-field events. My Dad is a big football (soccer) fan. When I was growing up, he would take his three daughters to the home games of Maccabi Haifa, the leading football team in the Israeli league.

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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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Question: What is the difference between Data Quality and DataOps Observability?

DataKitchen

. Question: What is the difference between Data Quality and Observability in DataOps? Data Quality is static. It is the measure of data sets at any point in time. Data Observability is dynamic — it is the testing of data, integrated data, and tools acting upon data — as it is processed — that checks for flow rates and data errors.

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If I Had To Start Learning Data Science Again, How Would I Do It?

KDnuggets

While different ways to learn Data Science for the first time exist, the approach that works for you should be based on how you learn best. One powerful method is to evolve your learning from simple practice into complex foundations, as outlined in this learning path recommended by a physicist who turned into a Data Scientist.

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New AI Advances Increase User Reach with Advanced Targeting

Smart Data Collective

Artificial intelligence has upended the digital marketing profession. A growing number of marketers are using AI to optimize and automate marketing campaigns in fantastic ways. Jason Hall, Founder and CEO of FiveChannels described some of the phenomenal benefits of leveraging AI in digital marketing in a post in Forbes. Hall states that AI hasn’t removed the need for human input in marketing, but it has helped remove a lot of the monotonous tasks that humans used to participate in.

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How to Use DevOps Azure to Create CI and CD Pipelines?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction In this article, we will discuss DevOps, two phases of DevOps, its advantages, and why we need DevOps along with CI and CD Pipelines. Before DevOps, software development teams, quality assurance (QA) teams, security, and operations would test the code for several […].

Testing 398
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The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.