nosql data warehouse

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How to overcome the cloud data warehouse data migration problem?

Cloud computing and data warehousing are a reasonable couple. Cloud storage can be scaled on demand, and the cloud can contribute a large number of servers to a specific task. The common function of Data Warehouse is the local data analysis tool, which is limited by calculation and storage resources, and is limited by

Reprinted: "boiled" Data Warehouse

Just a few days ago, a user participated in a job interview for an enterprise. He applied for the DBA of the company and was responsible for data analysis. This company successfully completed the process. Until the person in charge of the company. The owner only gave him an interview question: Let's talk about the differences between the database and the data warehouse

Comparison of the characteristics of nine large data warehouse schemes

Compare | data Comparison of the characteristics of nine large data warehouse schemes China Institute of Electronic Equipment Systems Engineering Wang Jiannu Lidompo Powerful companies such as IBM, Oracle, Sybase, CA, NCR, Informix, Microsoft, and SAS have launched their own data warehousing solutions (through acqui

Go: Oracle releases Big Data solutions with the latest NoSQL database

Label:Original source: http://www.searchdatabase.com.cn/showcontent_88247.htmHere are some excerpts:The latest big data innovations include: Oracle Big Data Discovery is a "visual Hadoop" and is an end-to-end product that is designed to discover, explore, transform, mine, and share with the insights of big numbers. Big data assets will be leveraged by more

SQL Server Data Warehouse concepts and building process

Basic concepts: 1. Multi-dimensional dataset: a multi-dimensional dataset is the main object in Online Analytical Processing (OLAP) and a technology that allows quick access to data in a data warehouse. A multi-dimensional dataset is a collection of data. It is usually constructed from a subset of a

Informix Data Warehouse Solution

According to the Informix Data Warehouse System implementation methodology, we can divide the data warehouse implementation into the following steps: 1. Business Demand Analysis Business Requirement analysis is the basis for data warehou

A NoSQL tutorial on massive data storage

Add by Zhj: The good series, the author introduced the NoSQL database, and focused on memcached and Redis, do not know whether there are other NoSQL database articlesA NoSQL tutorial on massive data storage-01 The basic theory of the -02-memcached of the NoSQL tutorial on ma

The construction and analysis of SQL Server Data Warehouse

server|sqlserver| data The construction and analysis of SQL Server Data Warehouse (i) 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

Monitoring Data Warehouse

In general, two monitored operational components in a data warehouse environment are the use of data and data stored in the Data warehouse. Monitoring data in a

NoSQL and Big Data

An overview of the data storage technologies available in big data projects, focusing on couchbase and ElasticSearch, showing how to use them, and how they differ, first understand the different technologies in the NoSQL world.NosqlThe relational database is the choice of the past and is almost the only choice for many developers and DBAs to apply to traditional

Data Warehouse logical Modeling

This article discusses two common methods in data warehouse model design. In the application environment of data warehouses, there are two types of load: one is to answer repetitive questions, and the other is to answer interactive questions. Dynamic query has obvious interactive features. This interaction process is often called

Five stages of the evolution of Dynamic Data Warehouse

Chief Technical Officer of--ncrteradata Division StephenbrobstJoerarey, chief consultant, strategic technology and systems company The most successful data warehouses are progressively developed in a gradual manner, each of which improves the business value of information. In recent years, data warehousing has evolved to support enterprise decisions and even new heights for enterprise partners and customers

Initial Data Warehouse (warehousing)-"Lift Your Veil"

Data Warehouse (Data warehousing)-"set off your Hijab" I'm here to say some of my beginner's understanding and views, I hope these can be as a simple introduction to those novice friends, but also want to play a good effect. When it comes to data warehousing, let's take a look at the background he's producing. Since Db

Use db_link to create a materialized view and synchronize data to a data warehouse

Number of materialized views synchronized 1. The purpose is to synchronize some data in the production database to the Data Warehouse. Considering the cost and convenience, the method of regularly refreshing the Materialized View Number of materialized views synchronized 1. The purpose is to synchronize some data in th

NoSQL, natural selection when data is large

table, usually according to the user to the table, will be the same user all the data are placed on the same machine, but if we create time to query, want to query all the users in the journal published today, then this will be invalidated. At this point you need to go to each of the sub-table query and then the query results are assembled. And the native SQL is not complete. When an index is unavailable, the aggregation operation is certainly not al

The difference between a database and a data warehouse

Label:In short, the database is a transaction-oriented design, the Data Warehouse is a theme-oriented design.Databases generally store online transaction data, and data warehouses typically store historical data.Database design is to avoid redundancy as far as possible, generally adopt the rule of conforming to the pat

SQL Server Data Warehouse Construction and Analysis

Instance construction process and analysis 1Now we will analyze and discuss it with a simple example.Ms SQL ServerData warehouse construction process. In fact, the construction of the Data Warehouse is quite complex. It combines the front-end technology of the data warehouse

Introduction to the DB2 data warehouse OLAP Service

IBM DB2 Data Warehouse Edition is a set of products that combine the strengths of DB2 Data servers and the robust business intelligence infrastructure from IBM. DB2 DWE integrates Core Components for warehouse management, data conversion,

Data Warehouse life cycle model

First, preface  Changes in the work content, resulting in a return to the Data Warehouse model architecture and design, so take a moment to compare the system Review Data Warehouse modeling and system building knowledge system, recorded, as a note it.Second, the model  No matter how

How Facebook's data warehouse expands to Pb

(Original article: ScalingtheFacebookdatawarehouseto300PB ?, This article is translated from the original article. Facebook's challenges in storage scalability in data warehouses are unique. Our Hive-based data warehouse stores more than Pb of data and is growing at a rate of TB per day. The number of

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