Data Mining, Data Warehouse and Database

Intro to Rapidminer: A No-Code Development Platform for Data Mining (with Case Study)

Analytics Vidhya

OCTOBER 4, 2021

This article was published as a part of the Data Science Blogathon Image 1 What is data mining? Data mining is the process of finding interesting patterns and knowledge from large amounts of data. This analysis […]. This analysis […].

Data Mining

Data Mining Data Mining Data Mining Data Warehouse

Data Mining vs Data Warehousing: 8 Critical Differences

Analytics Vidhya

MAY 29, 2023

The two pillars of data analytics include data mining and warehousing. They are essential for data collection, management, storage, and analysis. Both are associated with data usage but differ from each other.

Data Mining

Data Mining Data Mining Data Mining Analytics

Data mining

Dataconomy

MARCH 4, 2025

Data mining is a fascinating field that blends statistical techniques, machine learning, and database systems to reveal insights hidden within vast amounts of data. Businesses across various sectors are leveraging data mining to gain a competitive edge, improve decision-making, and optimize operations.

Data Mining

Data Mining Data Mining Data Mining Decision Trees

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Automation, Evolved: Your New Playbook For Smarter Knowledge Work

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Exploring the fundamentals of online transaction processing databases

Dataconomy

APRIL 27, 2023

What is an online transaction processing database (OLTP)? OLTP is the backbone of modern data processing, a critical component in managing large volumes of transactions quickly and efficiently. This approach allows businesses to efficiently manage large amounts of data and leverage it to their advantage in a highly competitive market.

Database

Database Data Scientist Data Mining Data Mining

How Will The Cloud Impact Data Warehousing Technologies?

Smart Data Collective

APRIL 8, 2020

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale.

Data Warehouse

Data Warehouse Big Data Big Data Big Data Analytics

Steps Companies Should Take to Come Up Data Management Processes

Smart Data Collective

MAY 16, 2022

Data Management is considered to be a core function of any organization. Data management software helps in reducing the cost of maintaining the data by helping in the management and maintenance of the data stored in the database. There are various types of data management systems available.

Data Warehouse

Data Warehouse Data Mining Data Mining Data Mining

Exploring the Power of Data Warehouse Functionality

Pickl AI

JUNE 11, 2024

Summary: A data warehouse is a central information hub that stores and organizes vast amounts of data from different sources within an organization. Unlike operational databases focused on daily tasks, data warehouses are designed for analysis, enabling historical trend exploration and informed decision-making.

Data Warehouse

Data Warehouse ETL Data Mining Data Mining

What is Data Integration in Data Mining with Example?

Pickl AI

JUNE 28, 2023

What is Data Mining? In today’s data-driven world, organizations collect vast amounts of data from various sources. But, this data is often stored in disparate systems and formats. Here comes the role of Data Mining. Here comes the role of Data Mining.

Data Mining

Data Mining Data Mining Data Mining ETL

Tackling AI’s data challenges with IBM databases on AWS

IBM Journey to AI blog

MARCH 14, 2024

The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage. Also, traditional database management tasks, including backups, upgrades and routine maintenance drain valuable time and resources, hindering innovation.

AWS

AWS Database ETL AI

What is Data Pipeline? A Detailed Explanation

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Pipeline

Data Pipeline Data Warehouse ETL Data Lakes

A Few Proven Suggestions for Handling Large Data Sets

Smart Data Collective

SEPTEMBER 26, 2021

Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. The raw data can be fed into a database or data warehouse. An analyst can examine the data using business intelligence tools to derive useful information. .

Database

Database Data Visualization Big Data Big Data

15 must-try open source BI software for enhanced data insights

Dataconomy

MAY 10, 2023

Open-source business intelligence (OSBI) is commonly defined as useful business data that is not traded using traditional software licensing agreements. This is one alternative for businesses that want to aggregate more data from data-mining processes without buying fee-based products.

Business Intelligence

Business Intelligence Business Intelligence Power BI Data Analysis

5 Benefits of BigQuery for Marketers

ODSC - Open Data Science

FEBRUARY 8, 2023

Common databases appear unable to cope with the immense increase in data volumes. This is where the BigQuery data warehouse comes into play. BigQuery operation principles Business intelligence projects presume collecting information from different sources into one database.

Database

Database Data Science Big Data Big Data

Self-Service BI vs Traditional BI: What’s Next?

Alation

MARCH 29, 2022

In the 1970s, data was confined to mainframes and primitive databases. Reports required a formal request of the few who could access that data. The 1980s ushered in the antithesis of this version of computing — personal computing and distributed database management — but also introduced duplicated data and enterprise data silos.

Business Intelligence

Business Intelligence Business Intelligence Data Silos Citizen Data Scientist

Data science vs data analytics: Unpacking the differences

IBM Journey to AI blog

SEPTEMBER 19, 2023

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

Data Science

Data Science Analytics Analytics Data Scientist

What Are Business Intelligence Tools

Pickl AI

JANUARY 15, 2025

These tools enable organizations to convert raw data into actionable insights through various means such as reporting, analytics, data visualization, and performance management. Data Processing: Cleaning and organizing data for analysis.

Business Intelligence

Business Intelligence Business Intelligence Power BI Data Visualization

What Does a Data Engineering Job Involve in 2024?

ODSC - Open Data Science

JANUARY 30, 2024

This involves extracting data from various sources, transforming it into a usable format, and loading it into data warehouses or other storage systems. Think of it as building plumbing for data to flow smoothly throughout the organization. This might involve setting up databases, data lakes, and streaming platforms.

Data Engineer

Data Engineer Data Engineering Data Engineering Data Engineering

From zero to BI hero: Launching your business intelligence career

Dataconomy

MARCH 24, 2023

BI involves using data mining, reporting, and querying techniques to identify key business metrics and KPIs that can help companies make informed decisions. A career path in BI can be a lucrative and rewarding choice for those with interest in data analysis and problem-solving. What is business intelligence?

Business Intelligence

Business Intelligence Business Intelligence Data Analysis Data Analysis

From zero to BI hero: Launching your business intelligence career

Dataconomy

MARCH 24, 2023

BI involves using data mining, reporting, and querying techniques to identify key business metrics and KPIs that can help companies make informed decisions. A career path in BI can be a lucrative and rewarding choice for those with interest in data analysis and problem-solving. What is business intelligence?

Business Intelligence

Business Intelligence Business Intelligence Data Analysis Data Analysis

Benefits of Learning Tableau for Data Analysts

Pickl AI

MAY 7, 2024

Their tasks encompass: Data Collection and Extraction Identify relevant data sources and gather data from various internal and external systems Extract, transform, and load data into a centralized data warehouse or analytics platform Data Cleaning and Preparation Cleanse and standardize data to ensure accuracy, consistency, and completeness.

Data Analyst

Data Analyst Tableau Data Science Data Analysis

Data Science Current

Intro to Rapidminer: A No-Code Development Platform for Data Mining (with Case Study)

Data Mining vs Data Warehousing: 8 Critical Differences

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Data mining

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Exploring the fundamentals of online transaction processing databases

How Will The Cloud Impact Data Warehousing Technologies?

Steps Companies Should Take to Come Up Data Management Processes

Exploring the Power of Data Warehouse Functionality

What is Data Integration in Data Mining with Example?

Tackling AI’s data challenges with IBM databases on AWS

What is Data Pipeline? A Detailed Explanation

A Few Proven Suggestions for Handling Large Data Sets

15 must-try open source BI software for enhanced data insights

5 Benefits of BigQuery for Marketers

Self-Service BI vs Traditional BI: What’s Next?

Data science vs data analytics: Unpacking the differences

What Are Business Intelligence Tools

What Does a Data Engineering Job Involve in 2024?

From zero to BI hero: Launching your business intelligence career

From zero to BI hero: Launching your business intelligence career

Benefits of Learning Tableau for Data Analysts

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