Analytics Vidhya

APRIL 19, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction Data mining is the process of finding interesting patterns. The post Proximity measures in Data Mining and Machine Learning appeared first on Analytics Vidhya.

Data mining 167

Data mining Measurement Machine Learning Publishing 167

Phocas

MAY 5, 2021

To solve the company’s reporting and data mining needs, it deployed Phocas Software. Colony Tire and Service and Atlantic Tire Distributors is a leading provider of tires and services in North Carolina, South Carolina and Virginia.

Data mining 153

Data mining Executive BI Software Reporting 153

Smart Data Collective

OCTOBER 2, 2020

Data mining has led to a number of important applications. One of the biggest ways that brands use data mining is with web scraping. Towards Data Science has talked about the role of using data mining tools with web scraping.

Data mining 73

Data mining Data Processing Testing Data Science 73

Data Science 101

OCTOBER 31, 2019

Today we are generating data more than ever before. Over the last two years, 90 percent of the data in the world was generated. This data alone does not make any sense unless it’s identified to be related in some pattern. Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Machine learning provides the technical basis for data mining.

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Data mining KDD Knowledge Discovery Forecasting 65

Smart Data Collective

NOVEMBER 18, 2020

The Data Scientist profession today is often considered to be one of the most promising and lucrative. The Bureau of Labor Statistics estimates that the number of data scientists will increase from 32,700 to 37,700 between 2019 and 2029. What is Data Science?

Data mining 97

Data mining Data Science Informatics Statistics 97

Smart Data Collective

MARCH 18, 2020

Big data is changing the direction of small and medium sized businesses. They can use big data for many purposes. However, the value of their big data strategies will vary considerably. Using big data to get a better understanding of your customers is important.

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Data mining Sales Data Strategy ROI 93

Smart Data Collective

FEBRUARY 15, 2021

Data mining serves many essential purposes in numerous applications. Last April, we talked about ways that social data can be useful in business. However, social data can serve even more important purposes, especially for public policy makers, GMOs and leading nonprofits.

Data mining 61

Data mining Statistics IT Big Data 61

DataFloq

OCTOBER 23, 2019

Data mining, a process that involves identifying patterns and anomalies in large data sets, is widespread among many of today’s companies. Experts predict the big data market will reach $103 billion in revenue by 2027, far exceeding 2019's predicted $49 billion. One of the main reasons why data mining is so pervasive is the wide variety of applications it has. But data mining is proving to be an effective way to combat fraud. Big Data

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Data mining Modeling Reporting Marketing 173

Smart Data Collective

SEPTEMBER 4, 2020

Data mining in Search Engine Optimization is a new concept and has gained importance in the digital marketing field. It can be understood as a process that can be used for extracting useful information from a large amount of data. In other words, data mining is a process that can be used by companies for converting raw data into useful data with the help of a software. What is Data Mining? How Data Mining is Changing SEO?

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Data mining Optimization Marketing Data Processing 54

Smart Data Collective

AUGUST 25, 2020

Before the turn of the century, the reliance on data technology was little more than nonexistent. Web developers utilized data to some capacity as well, but marketers rarely considered doing so. Big data has become critical to the evolution of digital marketing.

Data mining 85

Data mining Metadata Marketing Snapshot 85

DataFloq

MARCH 28, 2019

Companies receive information in the form of digital data or content, more commonly in the shape of performance and user metrics. The entire operation that involves collecting data, processing it and then putting it to use is called business intelligence. But even when teams are not actively working with data, it’s still collected and stored. To make use of this data it must be processed and analyzed, often referred to as “mining.”. Big Data

Data mining 216

Data mining Data Warehouse Metrics Business Intelligence 216

TreehouseTechGroup

JULY 22, 2020

Data mining for business analytics is the process of extracting valuable information from a vast amount of available corporate or consumer data. Businesses are generating huge amounts of data from various applications, IT systems, and databases. This data may be stored on.

Data mining 52

Data mining Business Analytics Analytics IT 52

TDAN

NOVEMBER 17, 2020

There is a great deal of talk in our industry about the importance of having common, standard data semantics and language and the value this brings. However, I think one of the greatest obstacles in achieving this is what I call data ‘mine’ing.

Data mining 72

Data mining Metadata Data Governance Business Intelligence 72

Jet Global

JUNE 5, 2019

The path to doing so begins with the quality and volume of data they are able to collect. Data drives everything in the business world, from manufacturing to supply chain logistics to retail sales to customer experience to post-sale marketing and beyond, data holds the secrets to making processes more efficient, production costs cheaper, profit margins higher and marketing campaigns more effective. Let’s introduce the concept of data mining.

Data mining 63

Data mining Business Intelligence OLAP Key Performance Indicator 63

Analytics Vidhya

MAY 5, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. In this blog post, we will learn how to pull data. The post How to use APIs to gather data and conduct data analysis (Google and IBB API) appeared first on Analytics Vidhya.

Publishing 197

Publishing Data Science Data mining Analytics 197

Analytics Vidhya

APRIL 23, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Advanced Data Mining Libraries Python AutoScraper AutoScraper Library blogathon web scrapingIntroduction Web Scraping is a method or art to get.

Publishing 197

Publishing Data Science Data mining Analytics 197

Analytics Vidhya

MAY 4, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Advanced Data Mining Libraries Python Unstructured Data AutoScraper AutoScraper Library blogathonBefore going ahead, lets we take a brief discussion on.

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Publishing Data Science Data mining Analytics 157

Analytics Vidhya

APRIL 26, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Advanced Data Mining Project Python Technique Beautifulsoup blogathon Exception HandlingOverview A Basic introduction to web scraping. Brief knowledge of.

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Publishing Data Science Data mining Analytics 165

Analytics Vidhya

DECEMBER 15, 2020

This article was published as a part of the Data Science Blogathon. Data Mining Intermediate Libraries blogathon cypress java web scraping“In this rushing world, Don’t Do hard work, it’s better to do. The post Web Scraping Using Cypress Tool!

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Publishing Data Science Data mining Analytics 238

Analytics Vidhya

OCTOBER 1, 2020

Beginner Data Exploration Data Mining Machine Learning feature engineering hackathons machine learningOverview Feature engineering techniques are a must know concept for machine learning professionals Here are 7 feature engineering techniques you can start using right.

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Machine Learning Data mining Analytics 261

Analytics Vidhya

APRIL 29, 2020

Classification Data Engineering Data Mining Python Advanced Python machine learning model deployment Model deployment text classification Twitter API

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Machine Learning Modeling Data mining Analytics 282

Analytics Vidhya

MARCH 3, 2020

Honestly, most data. Data Mining Intermediate Libraries Python Structured Data data exploration feature engineering pandas

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Data mining Analytics Structured Data 276

Analytics Vidhya

JANUARY 14, 2021

ArticleVideos I will admit, AWS Data Wrangler has become my go-to package for developing extract, transform, and load (ETL) data pipelines and other day-to-day. The post Using AWS Data Wrangler with AWS Glue Job 2.0 Data Mining Intermediate AWS Gkue AWS Glue Job 2.0

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Data mining Analytics 170

Analytics Vidhya

JANUARY 14, 2021

The post Use R To Pull Energy Data From The Department of Energy’s EIA API appeared first on Analytics Vidhya. Data Mining Information Security Intermediate RArticleVideos Note: I have written a Python version of this article, you can access that article here.

Data mining 165

Data mining Analytics 165

Analytics Vidhya

MAY 31, 2020

Overview Feature engineering is a key aspect in acing data science hackathons Learn how to perform feature engineering here as we walk through a. The post Want to Ace Data Science Hackathons? Beginner Data Engineering Data Mining Machine Learning Python datahack feature engineering feature importance pythonThis Feature Engineering Guide is for you appeared first on Analytics Vidhya.

Data Science 216

Data Science Data mining Analytics Machine Learning 216

Analytics Vidhya

JUNE 7, 2020

Overview SQL is a mandatory language every analyst and data science professional should know Learn about the basics of SQL here, including how to. Beginner Data Mining Database Programming Python SQL Structured Data database RDBMs sql analytics sql data sql data science sql for beginners sql sqlite SQLiteThe post SQL for Beginners and Analysts – Get Started with SQL using Python appeared first on Analytics Vidhya.

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Data mining Structured Data Data Science Analytics 219

KDnuggets

DECEMBER 24, 2019

2019 Dec Tutorials, Overviews Apriori Association Rules Data Mining PythonThis article is about Market Basket Analysis & the Apriori algorithm that works behind it.

Marketing 110

Marketing Data mining IT 110

Analytics Vidhya

FEBRUARY 2, 2021

ArticleVideos This article was published as a part of the Data Science Blogathon. Data Mining Intermediate Project Structured Data Technique blogathon Web Scraping UiPathThe World is rapidly moving towards AI, So it’s better to. The post Web Scraping Using RPA Tool UiPath! appeared first on Analytics Vidhya.

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Publishing Data Science Analytics Data mining 128

Rocket-Powered Data Science

MAY 20, 2020

In 2019, I was listed as the #1 Top Data Science Blogger to Follow on Twitter. And then there’s this — not a blog, but a link to my 2013 TedX talk: “ Big Data, Small World.” Rocket-Powered Data Science (the website that you are now reading). Big Data Data Science Internet of Things Machine Learning Artificial Intelligence Data Literacy Data MiningI have written articles in many places.

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Data Science Internet of Things Data mining Machine Learning 170

Forrester - Business Intelligence

OCTOBER 5, 2020

They say data is the new oil. They say data is the new currency. They say data is the key competitive differentiator. All true. But reality is sobering: Only 7% of firms report advanced, insights-driven practices.

Enterprise 70

Enterprise Reporting Analytics Data mining 70

Smart Data Collective

OCTOBER 20, 2020

Data analytics is at the forefront of the modern marketing movement. Companies need to use big data technology to effectively identify their target audience and reliably reach them. Big data should be leveraged to execute any GTM campaign.

Marketing 103

Marketing Data Analytics Analytics Data-driven 103

Rocket-Powered Data Science

DECEMBER 16, 2018

In a related post we discussed the Cold Start Problem in Data Science — how do you start to build a model when you have either no training data or no clear choice of model parameters. An example of a cold start problem is k -Means Clustering, where the number of clusters k in the data set is not known in advance, and the locations of those clusters in feature space ( i.e., the cluster means) are not known either. What data do we have?

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Machine Learning Metrics Modeling Optimization 200

Rocket-Powered Data Science

DECEMBER 15, 2018

Specifically, the availability and application of labeled data (things past) for the labeling of previously unseen data (things future) is fundamental to supervised machine learning. Without labels (diagnoses, classes, known outcomes) in past data, then how do we make progress in labeling (explaining) future data? kNN ( k-Nearest Neighbors ), which is a supervised learning technique in which the data set itself becomes the model.

Modeling 150

Modeling Optimization Data mining Metrics 150

Forrester's Customer Insights

OCTOBER 22, 2019

It’s T minus two weeks to Forrester’s 2nd Data Strategy & Insights Forum in Austin, TX. Over 300 data and analytics leaders will gather to share, learn and get inspired! For those of you who have already registered and planning to attend, you answered one key question during the registration process: What is your top […].

Strategy 32

Strategy Analytics B2B Customer Analytics 32

Decision Management Solutions

FEBRUARY 19, 2020

These different elements will lend themselves to different kinds of technology for automation – some will be rules based, some might use data mining, some might need machine learning algorithms. Focus instead on capturing data about how well the current approach is working and on regular, weekly updates to your decision-making. Automating decisions about transactions lets them be handled in real-time, providing better customer service.

Risk 56

Risk Testing Technology Data mining 56

Srividya Sridharan

OCTOBER 16, 2013

Customer insights professionals have many customer analytics methods (sub's reqd) to choose from today to perform behavioral customer analysis, and new techniques emerge as the complexity of customer data increases. Analysis of customer data involves the use of data-mining and statistical methods that span descriptive and predictive analytics. customer analytics customer insights customer intelligence data mining predictive analytics

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Statistics Data mining Predictive Analytics Customer Analytics 40

Decision Management Solutions

JULY 8, 2020

To meet a reporting need, an organization must present some or all of the data it has gathered in a report to some internal or external body. The organization that produces the report is only required to provide that data in report form. The start by looking at their data.

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Reporting ROI Key Performance Indicator Metrics 94

Rocket-Powered Data Science

APRIL 25, 2019

A few years ago, I generated a list of places to receive data science training. Learn the what, why, and how of Data Science and Machine Learning here. Big Data Data Science Machine Learning Products Training Analytics Data MiningThat list has become a bit stale. So, I have updated the list, adding some new opportunities, keeping many of the previous ones, and removing the obsolete ones.

Data Science 33

Data Science Deep Learning Statistics Data-driven 33

Data Science 101

DECEMBER 11, 2019

This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). Every year they host an excellent and influential conference focusing on many areas of data science. Honestly, KDD has been promoting data science way before data science was even cool.

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KDD Knowledge Discovery Data mining Statistics 72

Ms SQL Girl

JUNE 10, 2015

Chapter 3 Selecting the Data Architecture that Fits Your Organization. Chapter 4 Searching and Combining Data with Power Query. Chapter 6 Discovering and Analyzing Data with Power Pivot. Chapter 9 Discovering Knowledge with Data Mining. Chapter 12 Visualizing Your Data Interactively with Power View. Chapter 13 Exploring Geographic and Temporal Data with Power Map.

Visualization 40

Visualization Data Architecture Consulting Operational Reporting 40

Ms SQL Girl

JUNE 10, 2015

Chapter 3 Selecting the Data Architecture that Fits Your Organization. Chapter 4 Searching and Combining Data with Power Query. Chapter 6 Discovering and Analyzing Data with Power Pivot. Chapter 9 Discovering Knowledge with Data Mining. Chapter 12 Visualizing Your Data Interactively with Power View. Chapter 13 Exploring Geographic and Temporal Data with Power Map.

Visualization 40

Visualization Data Architecture Consulting Operational Reporting 40

Decision Management Solutions

DECEMBER 12, 2018

They had some great predictions and suggested priorities around the ethics of analytics, the value of data and the use of AI in fraud and cybersecurity. As they quote in the paper: According to the Rexer Data Science Survey, barely 10 to 15% of companies “almost always” deploy results and another 50% only deploy “often.” This lets business owners get used to analytics and data-driven decisioning and manages technology risk at the same time. Citizen Data Scientists.

Data Science 40

Data Science Machine Learning Data-driven Publishing 40

Data Virtualization

JANUARY 8, 2020

According to CIO magazine, the first chief data officer (CDO) was employed at Capital One in 2002, and since then the role has become widespread, driven by the recent explosion of big data. Business analysis big data Chief Data Officer data assets Data Governance Data Lakes Data Mining data virtualization Data Warehouse; Denodo Platform digital transformation ETL ETL Processes Gartner hadoop Logical Data Warehouse

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Data Warehouse Digital Transformation Data mining Data Lake 12