etl data warehouse concepts

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Big Data Warehouse Collection

Big Data Current major trends (self-understanding)file system, deployment, various streams and open source tools-------ETL Development (BI project)----Data statistical analysis------data Mining, machine learning Image from the analysisfirst, about KAKFA Kafka relatedKafka, a distributed messaging system developed by Li

Sqlserver bi-data warehouse design (2)

project is very simple, because it is a simplified version. This is a sales analysis software for the items used in the game. It includes several concepts, such as game, sales department, item, transaction amount, number of transactions, and publication singular. What we need to do is to use games, departments, and items to achieve cross-analysis of transaction amounts, transactions, and other data. In ou

Step by step bi-Data Warehouse Design

This is because the project has not really started, but it has been in contact with Bi for more than half a year. I have prepared for the past few days. Create a simplified Bi project. On the one hand, I will give a reference to my friends who are just getting started with Bi, and on the other In this regard, we also prepare for the project we are about to start, so that we can take some projects into account. . I also hope to provide some suggestions and experience for Bi researchers. Becau

How to build a data warehouse in SQL Server

"Guide" This article describes how to build a simple data warehouse in SQL Server and analyze related issues. Basic concepts: 1. Cubes: Cubes are the primary object in online analytical processing (OLAP) and are a technology that allows fast access to data in a data

Dimension table, fact table, Data Warehouse, BI ...

In the past, the dimension tables, fact tables, data analysis, BI and other concepts have some ambiguity. These days of study finally let these have some clues:A dimension represents the amount of data you want to analyze , such as when you analyze a product's sales, you can choose to analyze it by category , or by region . Such a press. The analysis forms a dim

Data Mining: Concepts and technologies

discusses mining networks, complex data types, and important application fields.Data Mining: Concepts and technology (3rd) is a reference book that must be read by all teachers, researchers, developers, and users in the field of data mining and knowledge discovery, it is an excellent teaching material suitable for data

"Reading notes-data mining concepts and technologies" data warehousing and online analytical processing (OLAP)

Before we saw the data and the preprocessing of the data, where was the data after processing? Put it in a place called "Data Warehouse".Basic concepts of data warehousing: Def

Data Warehousing Concepts (ii)-ODS

historical data in DW for medium and long-term planning Can solve the enterprise's Cosco decision-making needs Inability to meet real-time enterprise monitoring and real-time business needs Iv. Common Terminology ETL (Extract Transform Load) such as IBM Datastage, Informatic PowerCenter DM (data Mart) market A

An hour to understand data mining ⑤ data mining steps and common clustering, decision tree, and CRISP-DM concepts

: Some of the data in the database is incomplete (some of the attributes that are of interest are missing attribute values), are noisy (contain incorrect attribute values), and are inconsistent (the same information is represented differently), so data cleanup is required, complete, correct, Consistent data is stored in the D

"Data Mining concepts and technologies" reading notes-Introduction to Chapter I.

pattern representing knowledge, based on a measure of interest) Knowledge representation (using visualization and knowledge presentation techniques to provide users with knowledge of mining) 1.3 What types of data can be mined Database data Data Warehouse Dat

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