Sat.Nov 06, 2021 - Fri.Nov 12, 2021

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What Makes a Metric a KPI?

David Menninger's Analyst Perspectives

How does your organization define and display its metrics? I believe many organizations are not defining and displaying metrics in a way that benefits them most. If an organization goes through the trouble of measuring and reporting on a metric, the analysis ought to include all the information needed to evaluate that metric effectively. A number, by itself, does not provide any indication of whether the result is good or bad.

Metrics 328
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Study of Regularization Techniques of Linear Models and Its Roles

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction to Regularization During the Machine Learning model building, the Regularization Techniques is an unavoidable and important step to improve the model prediction and reduce errors. This is also called the Shrinkage method. Which we use to add the penalty term to control the complex […].

Modeling 349
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How to Build & Govern Trusted AI Systems: People

DataRobot

This is a three part blog series in partnership with Amazon Web Services describing the essential components to build, govern, and trust AI systems: People, Process, and Technology. All are required for trusted AI , technology systems that align to our individual, corporate and societal ideals. This first post is focused on making people across organizations successful with building and implementing AI you can trust.

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The Benefits and Drawbacks of DataOps in Practice

DataKitchen

The post The Benefits and Drawbacks of DataOps in Practice first appeared on DataKitchen.

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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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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Top Business Intelligence Features To Boost Your Business Performance

datapine

Table of Contents. 1) Benefits Of Business Intelligence Software. 2) Top Business Intelligence Features. a) Data Connectors Features. b) Analytics Features. c) Dashboard Features. d) Reporting Features. For a few years now, Business Intelligence (BI) has helped companies to collect, analyze, monitor, and present their data in an efficient way to extract actionable insights that will ensure sustainable growth.

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A Guide to Automated Deep/Machine Learning for Natural Language Processing: Text Prediction

Analytics Vidhya

This article was published as a part of the Data Science Blogathon This article starts by discussing the fundamentals of Natural Language Processing (NLP) and later demonstrates using Automated Machine Learning (AutoML) to build models to predict the sentiment of text data. Other applications of NLP are for translation, speech recognition, chatbot, etc.

More Trending

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The Four Pillars of a Data Fluent Organization

Juice Analytics

When it comes to using data, many organizations are reminiscent of the famous poem “Rime of the Ancient Mariner”: “Water, water, every where, Nor any drop to drink”. Data is everywhere, but it seldom seems to quench the thirst for smarter decisions. (As a side-note, this poem originated the phrase “albatross around your neck” — which is how a lot of CIOs and CTOs feel with both the data and expectations.

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25 Github Repositories Every Python Developer Should Know

KDnuggets

Check out these repositories to help you improve your data science skills.

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Neural Network for Regression with Tensorflow

Analytics Vidhya

This article was published as a part of the Data Science Blogathon In this article, I am going to build multiple neural network models to solve a regression problem. Before we start working on the model, I would like to give a brief overview of what we will touch on and what steps we will follow. […]. The post Neural Network for Regression with Tensorflow appeared first on Analytics Vidhya.

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How to Use Audience Data to Inform Marketing Programs & Campaigns

Smart Data Collective

According to the 2021 CMO Spend Survey by Gartner, budget allocation for marketing analytics failed to make the top 3 in priority falling behind digital commerce, marketing operations and brand strategy. While I understand that selling products, cutting costs and delivering brand strategy is important for long term business results, the lack of priority in using data troubles me.

Marketing 140
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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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#ClouderaLife Spotlight: Paul Wooding, Senior Regional Sales Director

Cloudera

On November 11 th we celebrate Veterans and Armistice Day honoring those who have served in the military. To commemorate this special occasion, we spotlighted two Clouderans who have served in the military both in the United States and the United Kingdom. In case you missed our first installment check out this Blog about William Daily. In this second installment, I sat down with Clouderan Paul Wooding who served in the British Army.

Sales 108
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Dream Come True: Building websites by thinking about them

KDnuggets

From the mind to the computer, make websites using your imagination!

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A Tool for Investor – The Art of Web Scraping

Analytics Vidhya

This article was published as a part of the Data Science Blogathon INTRODUCTION Investing is an important part of one’s life because Investing helps in making the present and future safety, it allows you to grow financially. Also, investing is a process of compounding profits. Investing money at the right place and right time helps in increasing […].

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3 Strategies Employed by the Leading Enterprise Cybersecurity Platforms

Smart Data Collective

Much has changed since the time when organizations only knew of antiviruses and simple firewalls as the tools, they need to protect their computers. To address newer challenges, security providers have developed new technologies and strategies to combat evolving threats. Stephanie Benoit-Kurtz, Lead Area Faculty Chair for the University of Phoenix’s Cybersecurity Programs, offers a good summary of the changes security organizations should anticipate , especially in the time of the pandemic.

Strategy 139
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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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Methodology & Functionality in Differing Data Science Roles

Dataiku

In this Banana Data Podcast episode " Methodology & Functionality in Differing Data Science Roles," our hosts share the rundown on data science roles, so you will no longer be in the dark for behind the scenes data science happenings. Speaking with a Dataiku solutions engineer, listeners get special insights on how the roles of data science and engineering teams contribute at a broader organizational level.

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Deep Learning on your phone: PyTorch C++ API for use on Mobile Platforms

KDnuggets

The PyTorch Deep Learning framework has a C++ API for use on mobile platforms. This article shows an end-to-end demo of how to write a simple C++ application with Deep Learning capabilities using the PyTorch C++ API such that the same code can be built for use on mobile platforms (both Android and iOS).

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How To Use Python To Analyse Fitness Tracker Market: Step By Step EDA

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Image Source: Author Introduction to Fitness Tracker Market With the advancements in the IT domain, wearable devices have been in great demand in the recent past. A wearable device is simply a device that can be worn by the user and this device is […]. The post How To Use Python To Analyse Fitness Tracker Market: Step By Step EDA appeared first on Analytics Vidhya.

Marketing 389
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Car and Mobile Companies Use Big Data to Reduce Distracted Driving

Smart Data Collective

The average consumer is unaware of the phenomenal benefits that big data provides. One of the biggest benefits of big data is that it can help improve driver safety. Data analytics technology is becoming more useful when it comes to stopping traffic accidents. A lot of companies are sharing data to help make roads and vehicles safer, as well as helping drivers make better driving decisions on the road.

Big Data 138
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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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Defining Simplicity for Enterprise Software as “a 10 Year Old Can Demo it”

Cloudera

Arjun (my son) sat next to me at my desk. He was a bit nervous but we had practiced 3 times before he was ‘on stage’ in front of hundreds of people and the zoom meeting turned to him. My ten year old began to demonstrate how to deploy an Operational Database in AWS, showcasing how auto-scaling worked and how to set up replication. All of the sales team and my colleagues were quite impressed with him, and I am very proud of him.

Software 103
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7 Top Open Source Datasets to Train Natural Language Processing (NLP) & Text Models

KDnuggets

With a lot of excitement and research around NLP, there are growing opportunities to apply these technologies to real-world scenarios. It's not trivial to become familiar with NLP and these open-source data sets can help you increase your skills.

Modeling 123
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Optimizing Pokemon Team using Python’s PuLP Library

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Hey all, I am sure you must have played pokemon games at some point in time and must have hated the issue of creating an optimal and balanced team to gain an advantage. What if I say one can do this by having […]. The post Optimizing Pokemon Team using Python’s PuLP Library appeared first on Analytics Vidhya.

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Data Analytics is Crucial for Businesses Preparing for Financial Disasters

Smart Data Collective

Data analytics has become a very important aspect of any modern business’s operating strategy. One of the most important ways to utilize big data is with financial management. The financial analytics market is projected to be worth $114 billion within the next two years. This is a testament to the amazing benefits it provides for companies in all sectors.

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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.

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Metadata Management Best Practices: How to Plan Your Metadata Management Program

Octopai

Metadata has been defined as the who, what, where, when, why, and how of data. Without the context given by metadata, data is just a bunch of numbers and letters. And unless you love numbers and letters for their own sake, that’s not all that valuable. But going on a rampage to define, categorize, and otherwise metadata-ize your data doesn’t necessarily give you the key to the value in your data.

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The Ultimate Guide To Different Word Embedding Techniques In NLP

KDnuggets

A machine can only understand numbers. As a result, converting text to numbers, called embedding text, is an actively researched topic. In this article, we review different word embedding techniques for converting text into vectors.

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Autocorrect Feature using NLP in Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Getting Started With… Natural Language Processing (NLP) is the field of artificial intelligence that relates lingual to Computer Science. I am assuming that you have understood the basic concepts of NLP. So we will move ahead. There are Some NLP applications as follows: […].

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Small Companies Use Analytics to Save Big On Business Insurance

Smart Data Collective

Big data technology has been a huge gamechanger in the insurance sector. More insurance are using big data to assist with the underwriting process. They have discovered that data analytics has made the underwriting process a lot easier. They are getting a better understanding of risk and choosing rates for their policyholders. However, insurance companies aren’t the only ones affected by big data.

Insurance 130
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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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How Many Organizations Are Led by “Data People”?

Dataiku

In our previous article on building a strong data culture , we outlined an ambitious agenda for change — recognize how the company makes decisions and what needs to be changed, embed business translators and data product managers into the organization, and build an ideas factory instead of becoming too attached to early experiments or models.

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The Common Misconceptions About Machine Learning

KDnuggets

Beginners in the field can often have many misconceptions about machine learning that sometimes can be a make-it-or-break-it moment for the individual switching careers or starting fresh. This article clearly describes the ground truth realities about learning new ML skills and eventually working professionally as a machine learning engineer.

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Getting started with Microsoft Power BI

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Table of contents Introduction What is Microsoft Power BI? Microsoft Power BI Concepts Data sources in Microsoft Power BI Import Excel Data to Microsoft Power BI Query Editor Inbuilt visuals Conclusion Introduction There is so much data collected in businesses and industries today. […].

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What’s the Difference Between Data Conversion and Data Migration?

Smart Data Collective

These days, almost every organization relies on huge quantities of data to run day-to-day operations. There are times when projects may require you to convert or migrate data , depending on whether it’s moving from one system to another or from several databases into one. The terms “ database conversion ” and “database migration” are often used interchangeably, but they are two different processes that play a big role in an organization’s software implementation.

Testing 129
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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.