unstructured data warehouse

Ho, August See a colleague on the desktop there is a Data Warehouse Toolbox Third edition, this blog simply discusses the Data Warehouse modeling general process and modeling methods (mainly practical experience and network data integration) First describe the application

://en.wikipedia.org/wiki/Data_warehouse In computing, a Data Warehouse (DW or DWH), also known as an enterprise Data Warehouse (EDW), is a system used for reporting and data analysis, and are considered a core component of business Intellig ence. [1] DWs is central

Top 10 best practices for building a large Relational Data Warehouse Writer:Stuart ozer, Prem Mehra, and Kevin Cox Technical ReviewPerson:Lubor Kollar, Thomas kejser, Denny Lee, Jimmy may, Michael Redman, and Sanjay Mishra Building a large relational data warehouse is a complex task. This article describes some design

Auto House Data Platform architectureInternet Enterprise Data Warehouse construction is to use the bottom-up approach, or top-down approach. If you are an architect in the data division, how do you plan a data warehouse? At the 20

(r.id.lv_chatlist);) Use this methodLv.setonitemclicklistener (New Adapterview.onitemclicklistener () {@Overridepublic void Onitemclick (adapterviewYour code of executionIntent Intent = new Intent (getactivity (), chatactivity.class);Intent.putextra ("Account", mlist.get (position). GetName ());Intent.putextra ("icon", mlist.get (position). GetIcon ());StartActivity (Intent);}});You can handle the Click event. The position here is the first item of the list you clicked. In this way, th

Data Warehouse data volume is generally very large, we need to back up every day? This point I still do not understand, just feel that the data warehouse at the very least from the production library flow of data does not need to

Common meanspartitions, hash-join, Data Warehouse functions, materialized views, bitmap indexes, etc. are common in the Data Warehouse technology,while the tips listed below are the most commonly used optimization tools/techniques in the project, the Green background highlight part belongs to unconventional means, the

Model design of Data WarehouseA. Data Modeling MethodologyThe design of the Data warehouse model follows the design principle of "top-down and gradual refinement".The design of the model is divided into three stages:1, conceptual modelThe scope and use of the business, from the height of the abstract summary, that is,

With the advent of data warehousing equipment (Warehouse appliance), the potential of business intelligence and advanced analytics applications has been stimulated, and many enterprises will use the advantages of data warehousing technology to enhance their competitiveness. But not to say that integration equipment is omnipotent, it also has many limitations, acc

Data warehouse model development methodology (for future reference) Based on the business data model, the data model of the data warehouse system is formed through the eight-step conversion process: Procedure Action

General Purpose = Take account of both OLTP and OLAPTransaction processing =OLTPData Warehouse =olapCustom DATABASE = Custom Gold dividing line (deep analysis) ******************************* Data processing can be roughly divided into two main categories: online transaction processing OLTP (on-line transaction processing), online analytical processing OLAP (On-line Analytical Processing). OLTP is the ma

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

This paper gives the basic concept of SQL Server Data Warehouse, and uses the example construction process to analyze, for everyone's reference! Basic concepts: 1. Cubes: Cubes are the primary object of online analytical processing (OLAP) and are a technology that allows fast access to data in a data

"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 warehouse