Gradient Dimension Conversion and Its Implementation
Author: Chen Li
In SQL Server 2005, Bi (Business Intelligence) module functions are greatly enhanced. An important module is called SQL Server Integrated Services (SSIS), which is the SQL Server database integration service, its main function is to extract, convert, and load data from the business database or OLTP database (extract-transform-load, ETL) to the data warehouse ), th
physical model of the Data Warehouse.2. Basic concepts of fact tables and dimension tablesSimply speaking, the dimension table is the angle (dimension) in which you observe the object, and the fact table is what you want to focus on.For example, to analyze the sales of products, you can choose to analyze by product category, or by time, such as the press. The an
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 dimension. The previous example can have two dimensions: type and region. In addition, each dimension can have sub-dimensions (called attributes), such as attributes t
results. Second, the difference between the middle level and the grade of the dimensionWhen defining dimensions in OLAP , layers (Hierarchy) and levels are two confusingconcepts. Simply put, a layer is a classification of dimension members, which is the inclusion relationship between dimension members or dimension member properties. A
What is a fact (fact) dimension relationshipDevelopers who have developed SSAS cube should know that there is a type of fact relationship in Cube's dimension usage, as shown in:The fact dimension relationship is just like the description in the red box above, which refers to a table even if the fact table is a dimension
0x00 Preface
The following content, is the author in the study and work of some summary, of which the concept of most of the content from the book, the practical content mostly from their own work and personal understanding. Due to the lack of qualifications, there will inevitably be many mistakes, I hope to criticize. Overview
The Data warehouse contains a lot of content, which can include architecture, modeling, and methodologies. For specific work, it can include the following: A data archit
Beginners Guide to learn Dimension Reduction techniquesintroduction
Brevity is the soul of wit
This powerful quote by William Shakespeare applies well to techniques used in data Science Analytics as well. Intrigued? Allow me to prove it using a short story.In could ', we conducted a data Hackathon (a Data science competition) in DELHI-NCR, India.Register for Data Hackathon 3.0–the Battle of survivalWe gave participants the challenge to
VC Dimension (
Vapnik-Chervonenkis dimension) Is an important indicator of function set learning performance defined by statistical learning theory to study the speed and promotion of consistent convergence in the learning process. The traditional definition is: For an indicator function set, if H samples exist, functions in the function set can be separated by all possible forms of K power of 2, the functi
Original: SSAS Series--"02" Multidimensional Data (Dimension object)1. What is dimension? In mathematics, it is called a parameter, which is the number of independent space-time coordinates in physics. 0-Dimensional is a point, 1-dimensional is a line, 2-dimensional is a long and wide (or curved) area, 3-dimensional is 2-dimensional plus the height to form the volume surface. In physics, Time is the fourth
Instance description 1:Slowly changing dimensions. For example, if you register a csdn account with the address, phone number, and other information you fill in, your address will change, but it will change once in a long time. This is a Slow Changing Dimension. See type1, type2, and type3.Type1-full coverage, keep the latest data (keep most recent values in target)Type2-full history (keep a full history of changes in the target)Type3-keep the latest
name calculation can be used to generate descriptive Dimension member names, define other user hierarchies, or specify the names of "(all)" members, to improve user-friendly features of the dimension. You can specify the "all"-level Member names of the Attribute Hierarchy based on the "all"-level Member names of each user hierarchy. In tasks under this topic, a user hierarchy is defined in the "product"
Explanation 1:
Fact tables are data tables combined by a certain field of analysis.The latitude table is a combination of analysis indicators in this field.
Interpretation 2:
To put it simply;A fact table is a transaction table.A dimension table is a basic table.Used to explain the specific content of the keyword latitude in a fact table.
Explanation 3:
Fact data tableThe central table in the data warehouse architecture, which contains the d
Original: http://blog.csdn.net/keith0812/article/details/8901113The support vector machine method is based on the VC dimension Theory of statistical learning theory and the minimum principle of structural risk.Structured riskStructured risk = empirical risk + confidence riskEmpirical risk = error of the classifier on a given sampleConfidence risk = Error of the result that the classifier classifies on unknown textConfidence Risk Factors:The number of
In the article "using calculated members to achieve the daily average", we achieved the average of the balance by establishing a calculation member, so as to guarantee the dimension of the bus structure! The disadvantage of this method, of course, is that many computational members need to be set up, and the efficiency of the calculated members is poor.
In this section, we use the custom rollup method of the dimen
Tags: MySQL Time dimension table Data WarehouseGenerate a Time dimension table in MySQLUsing the MySQL common date function to generate time dimension tables is the most efficient, simplest, and requires no other tools to support. The resulting results are shown for example:# time Spanset @d0 = "2012-01-01"; SET @d1 = "2012-12-31"; SET @date = date_sub (@d0, Inte
When we create dimensions in SSAs, it is sometimes possible that one dimension needs to use multiple table fields as dimension attributes, so there is bound to be an association between the multiple tables, but remember that the correlation between the dimension tables and only one cannot have multiple, let's look at an example.Now we have created a
The support vector machine method is based on the VC dimension Theory of statistical learning theory and the minimum structure risk principle.Confidence risk: The classifier classifies the unknown sample and obtains the error. Experiential risk: A well-trained classifier that re-classifies the training samples. That is, sample error structure risk: Confidence risk + empirical risk structure risk minimization is a strategy proposed to prevent overfitti
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Bi Data Warehouse product database storage
A typical example is to compare a logical business to a cube. The product dimension, time dimension, and location dimension are different coordinate axes, and the intersection of coordinate axes is a specific fact. That is to say, a fact table is an intersection of m
The primary key in a dimension table usually has two choices: the Natural key (Natural key), which is already present in the business system, usually a character-type marker with a certain business meaning, which uniquely flags each of the dimension tablesRecording. Like whatOrganization's code, abbreviations, time tags, and so on. The other is the surrogate key (surrogate key), which is usuallyA numeric va
Abstract
Yes
With the development of computers and the increasing number of data islands in information systems, how to use the data is a problem facing every enterprise.ETLYesexponential Data Extraction(Extract), Data Conversion(Transform)And Data Loading(Loading)And plays a key role in the application of data warehouse.ETLUse these data islands to form a data warehouse,It is an extremely important part in building a data warehouse. Slow change dimen
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