Smart Data Collective

AUGUST 25, 2020

Digital marketers can use data mining tools to assist them in a number of ways. Hadoop data mining technology can identify duplicate metadata content across different digital creatives, which might be causing search engine penalties, message saturation issues and other problems.

Data mining 137

Data mining Metadata Big Data ROI 137

Smart Data Collective

MARCH 28, 2022

Modern businesses that neglect to invest in big data are at a tremendous disadvantage in an evolving global economy. Smart companies realize that data mining serves many important purposes that cannot be overlooked. One of the most important benefits of data mining is gaining knowledge about customers.

Data mining 116

Data mining Customer Analytics Marketing Advertising 116

O'Reilly on Data

JANUARY 22, 2019

An exploration of three types of errors inherent in all financial models. At Hedged Capital , an AI-first financial trading and advisory firm, we use probabilistic models to trade the financial markets. All financial models are wrong. Clearly, a map will not be able to capture the richness of the terrain it models.

Modeling 198

Modeling Finance Uncertainty Data mining 198

Data Science 101

OCTOBER 31, 2019

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.

Data mining 77

Data mining KDD Data Science Forecasting 77

TDAN

AUGUST 17, 2021

If you are planning on using predictive algorithms, such as machine learning or data mining, in your business, then you should be aware that the amount of data collected can grow exponentially over time.

Predictive Modeling 115

Predictive Modeling Modeling Data mining Big Data 115

Jet Global

JUNE 5, 2019

So how does a leading-edge business find a way to marry their wealth of data with the opportunity to utilize it effectively via BI software? Let’s introduce the concept of data mining. Toiling Away in the Data Mines. Clustering helps to group data and recognize differences and similarities.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

KDnuggets

JUNE 15, 2022

14 Essential Git Commands for Data Scientists; A Structured Approach To Building a Machine Learning Model; How is Data Mining Different from Machine Learning?; Understanding Functions for Data Science; Top 18 Data Science Facebook Groups.

Machine Learning 110

Machine Learning Data mining Modeling Data Science 110

Rocket-Powered Data Science

JULY 6, 2021

2) MLOps became the expected norm in machine learning and data science projects. MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase.

Machine Learning 279

Machine Learning Data-driven Deep Learning IoT 279

CIO Business Intelligence

DECEMBER 20, 2024

Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). An organizations data architecture is the purview of data architects. Curate the data.

Data Architecture 122

Data Architecture Management Consulting Internet of Things 122

CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Business analytics is a subset of data analytics. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

Jen Stirrup

SEPTEMBER 30, 2021

They may also learn from evidence, but the data and the modelling fundamentally comes from humans in some way. Data Science – Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

Smarten

FEBRUARY 19, 2025

It must be based on historical data, facts and clear insight into trends and patterns in the market, the competition and customer buying behavior. Financial Services, Banks and Loan Businesses Predictive analytics provides support for credit risk and fraud mitigation and allows businesses to create scoring models for loan approval, etc.

Predictive Analytics 64

Predictive Analytics Analytics Predictive Modeling Forecasting 64

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 144

Data mining Data-driven Statistics OLAP 144

IBM Big Data Hub

AUGUST 15, 2022

Sometimes as data scientists, we are often so determined to build a perfect model that we can unintentionally include human bias into our models. Often the bias creeps in through training data and then is amplified and embedded in the model. Model risk management.

Data mining 60

Data mining Risk Modeling Risk Management 60

Smart Data Collective

NOVEMBER 1, 2020

Unlike supervised ML, we do not manage the unsupervised model. k-means Clustering – Document clustering, Data mining. In data mining, k-means clustering is used to classify observations into groups of related observations with no predefined relationships. DBSCAN Clustering – Market research, Data analysis.

Machine Learning 145

Machine Learning Data mining Visualization Statistics 145

Analytics Vidhya

DECEMBER 27, 2023

Introduction Data annotation plays a crucial role in the field of machine learning, enabling the development of accurate and reliable models. In this article, we will explore the various aspects of data annotation, including its importance, types, tools, and techniques.

Machine Learning 334

Machine Learning Modeling Analytics Data mining 334

datapine

NOVEMBER 27, 2019

Accordingly, predictive and prescriptive analytics are by far the most discussed business analytics trends among the BI professionals, especially since big data is becoming the main focus of analytics processes that are being leveraged not just by big enterprises, but small and medium-sized businesses alike.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Rocket-Powered Data Science

JULY 7, 2019

Autonomous Vehicles: Self-driving (guided without a human), informed by data streaming from many sensors (cameras, radar, LIDAR), and makes decisions and actions based on computer vision algorithms (ML and AI models for people, things, traffic signs,…). Examples: Cars, Trucks, Taxis. They cannot process language inputs generally.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Smart Data Collective

MAY 16, 2022

There are various types of data management systems available. These include, but are not limited to, database management systems, data mining software, decision support systems, knowledge management systems, data warehousing, and enterprise data warehouses. They are a part of the data management system.

Management 136

Management Data mining Data Warehouse Data Collection 136

Smart Data Collective

JUNE 15, 2021

Big data can play a very important role in solving these challenges. Pre-employment screening with data mining tools increases the quality of candidates. These organizations use data mining tools to find out everything that they can about the people they are screening. Let’s have a look at some facts.

Data-driven 134

Data-driven Data mining Cost-Benefit Big Data 134

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? Data analytics includes the tools and techniques used to perform data analysis.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Smart Data Collective

AUGUST 30, 2022

Analytics can use existing data to model scenarios where customers will respond to different prices. This article will walk you through 5 top B2B pricing models that you should consider when determining your own strategy. We will also talk about ways to incorporate data analytics into these models.

B2B 145

B2B Analytics Cost-Benefit Metrics 145

Smart Data Collective

MAY 3, 2021

Big data has played a huge role in the evolution of employment models. You should understand the changes wrought by big data and the impact that it is having on the gig economy. Let us take a look at some of the pros and cons of the world of gigs: #1 Unbridled liberty of choice with data mining.

Big Data 130

Big Data Data mining Cost-Benefit Insurance 130

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Financial services: Develop credit risk models. from 2022 to 2028.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

Smart Data Collective

NOVEMBER 12, 2021

We talked about the benefits of outsourcing IoT and other data science obligations. You should use big data to improve your outsourcing models by data mining pools of talented employees. Data-Driven Businesses Are Shifting More Towards Outsourcing Models. Global companies spent over $92.5 Here’s why.

Data-driven 128

Data-driven Cost-Benefit Data mining Big Data 128

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

Predictive Analytics 139

Predictive Analytics Analytics Predictive Modeling Data mining 139

Smart Data Collective

DECEMBER 19, 2021

Besides, it offers data model creation, systematized data sets, developable web services, ML-powered algorithms, versatile use of data mining and so many other very efficient functionalities that make it very flexible and productive to use for Data Preprocessing. Somewhat becomes slow in computation.

Optimization 141

Optimization Machine Learning Data mining Statistics 141

Smart Data Collective

NOVEMBER 11, 2021

We have frequently talked about the merits of using big data for B2C businesses. One of the reasons that we focus on these sectors is that there is so much data on consumers, which makes it easier to create a solid business model with big data. Set Goals and Develop a Strategy with Data Mining.

B2B 132

B2B Data mining Big Data Marketing 132

CIO Business Intelligence

JANUARY 20, 2023

BI focuses on descriptive analytics, data collection, data storage, knowledge management, and data analysis to evaluate past business data and better understand currently known information. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. They know how to assess data quality and understand data security, including row-level security and data sensitivity.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

datapine

SEPTEMBER 27, 2022

Some of these ‘structures’ may include putting all the information; for instance, a structure could be about cars, placing them into tables that consist of makes, models, year of manufacture, and color. With a MySQL dashboard builder , for example, you can connect all the data with a few clicks.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

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. 1989 to be exact. The details are below.

KDD 81

KDD Knowledge Discovery Data mining Data Science 81

Smart Data Collective

MARCH 2, 2023

Big data helps businesses address cash flow needs A growing number of companies use big data technology to improve their financing. They can use data mining tools to evaluate the average interest rate of different lenders. Therefore, data-driven pricing may be even more critical during a bad economy.

Big Data 105

Big Data Uncertainty Risk Data mining 105

Smart Data Collective

APRIL 19, 2022

Data mining technology has become very important for modern businesses. Companies use data mining technology for a variety of purposes. One of the most important is collecting revenue data to draft financial statements, forecast future sales and make decisions to address revenue shortfalls.

Sales 122

Sales Reporting Data mining Forecasting 122

Smart Data Collective

JUNE 23, 2022

Finally, if your company is paying for office space through renting, it may be worth adopting a hybrid working model and only using communal workspaces on the days you need to get together. Data analytics tools make it easier to take a deep dive into your finances. Data mining tools make it a lot easier to find government grants.

Analytics 128

Analytics Data mining Finance Insurance 128

Smart Data Collective

JUNE 14, 2022

The best way to do this is by generating a buyer persona or a model of your typical customer or client which helps you establish a clear way of promoting your services to the right people. Data analytics has made it easier to identify the best audience for your online business. Use Data Mining to Hone Your Content Creation Skills.

Big Data 122

Big Data Data mining Metrics Sales 122