Label:In the absence of a real data warehouse database, all data warehouses are now just a relational database created based on the dimension model, but the Data Warehouse database itself has some differences, such as the unique features of an OLTP database, such as the most
Partitioning a relational data warehouse
The following sections will briefly explain the concept of a relational data warehouse, the benefits of partitioning a relational data warehouse, and the benefits of migrating to
Tags: blog http ar os using SP strong data onOriginal: (original) Big Data era: a summary of knowledge points based on Microsoft Case Database Data Mining (Microsoft Clustering algorithm)This article is mainly to continue the previous Mi
support the development of data warehousing and business intelligence for nearly 20 years, where Inmon advocates a top-down architecture, with different OLTP data focused on themes, integrated, volatile, and time-changing structures for later analysis; And the data can be drilled to the finest layer, or rolled up to the summary layer; The
Reprint: http://www.cnblogs.com/zhijianliutang/p/4009829.htmlThis article is mainly to continue the previous Microsoft Decision tree Analysis algorithm, the use of another analysis algorithm for the target customer group mining, the same use of Microsoft case data for a brief summary.Application Scenario IntroductionIn the previous article, we used the
the discrete or continuous value, can only predict the value of two yuan, such as: buy/Not buy, yes/No, will/not wait, Khan. Quite accord with the Chinese taiji figure in the easy classics. There are only two states can be explained, is the so-called: Tai Chi Sheng Two, two instrument four-phase, four-phase health gossip ... So the simplest is the most easy to use, but also the fastest.Pull away, specific algorithm details can refer to Microsoft Offi
algorithm, the previous article we have introduced, when we face a bunch of data and to be based on a certain purpose to the data mining, feel that we do not know or choose the appropriate algorithm in DM, At this point we apply the Microsoft Neural Network analysis algorithm, and when we analyze the rules with the Microsoft
In the data warehouse project, ETL is undoubtedly the most tedious, time-consuming, and unstable. If the data source and target are both oracle and meet certain conditions, you can use
In the data warehouse project, ETL is undoubtedly the most tedious, time-consuming, and un
Bayesian network. For more information about selecting meaningful properties and how to score and arrange those properties, see Feature Selection (Data mining).A common problem in data mining models is that the model is too sensitive to subtle differences in training data, which is known as over-fitting or over-training. Overfitting models cannot be generalized
Backup | Data 1: Data Warehouse schema Backup
Including the database architecture and OLAP architecture;
The database includes a dimension table, fact table, and other temporary or control class tables whose structure is generated by generating SQL scripts.
Note: Its primary key, index and so on are to be generated;
The OLAP schema is saved by default in the "C:\
Recently, Microsoft Research Asia through the GitHub platform open source map data Query Language LIKQ (language-integrated knowledge query). LIKQ is a data query language that can be used for child graph and path query based on distributed large-scale graph data processing engine graph engine. It allows developers to
In the data warehouse project, ETL is undoubtedly the most tedious, time-consuming, and unstable. If the data source and target are both Oracle and meet certain conditions, you can use the oracle tablespace to improve ETL efficiency.To use a tablespace, the following conditions must be met:The source and target databases must both be larger than 8i;Ø for versions
Tags: sqlAzure Documentation:https://docs.azure.cn/zh-cn/#pivot =productspanel=databasesSQL Data Warehouse Documentation:https://docs.azure.cn/zh-cn/sql-data-warehouse/Learn how to use SQL Data Warehouse, which combines SQL Server
, according to the user purchase, add shopping cart sequence records, according to product priority for the best product recommendationIn fact, the algorithm is similar to the clustering algorithm, but compared with the algorithm, it is more granular, and then the order of the cases in clustering is excavated.Technical preparation(1) Microsoft Case Data Warehouse
data, and creating predictions. The simple point is to find out the same kind of attributes.Microsoft Naive Bayes: The Microsoft Naive Bayes algorithm is a Bayesian theorem-based classification algorithm provided by Microsoft SQL Server Analysis Services that can be used for predictive modeling.These algorithms are supported by a number of underlying algorithms,
Avenue to Jane data processing tools-microsoft Power Query
Farewell to complex Excel functions, Excel VBA programming, let everything return to simplicity and function.
What kind of crowd fits such a tool:
1, cashier, accounting, statistics, warehouse management, data analysis and other
Services, analytics services, and Reporting Services, which you will see when you install SQL Server.
The Data Engine service is what we typically refer to as tables, views, and stored procedures when referring to the services involved.
Integration services are used to toss data, usually in the transfer of data from the business library to the
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