datamart

Datamart vs. reporting Cube, what are the differences?

由 巧了我就是萌 提交于 2020-04-05 08:07:11
问题 The terms are used all over the place, and I don't know of crisp definitions. I'm pretty sure I know what a data mart is. And I've created reporting cubes with tools like Business Objects and Cognos. I've also had folks tell me that a datamart is more than just a collection of cubes. I've also had people tell me that a datamart is a reporting cube, nothing more. What are the distinctions you understand? 回答1: Cube can (and arguably should) mean something quite specific - OLAP artifacts

Datamart vs. reporting Cube, what are the differences?

由 梦想与她 提交于 2020-04-05 08:03:02
问题 The terms are used all over the place, and I don't know of crisp definitions. I'm pretty sure I know what a data mart is. And I've created reporting cubes with tools like Business Objects and Cognos. I've also had folks tell me that a datamart is more than just a collection of cubes. I've also had people tell me that a datamart is a reporting cube, nothing more. What are the distinctions you understand? 回答1: Cube can (and arguably should) mean something quite specific - OLAP artifacts

What makes access to OLAP Cubes / Datamarts and similar datastructures, faster than to relational databases?

由 限于喜欢 提交于 2020-01-02 09:55:15
问题 What makes access to OLAP Cubes/Datamarts and similar datastructures, faster than to relational databases? EDIT A bounty of 200 will be provided asap. 回答1: I would say mainly because of different purposes. OLAP cubes / datamarts are used mainly in read mode for data analysis by business users whereas I'm assuming when mentioning relational DBs you're talking about OLTP usage requiring for example ACID transactions. Those different purposes means: different constraints for the implementation

Inmon data Marts vs Kimball data marts

由 一个人想着一个人 提交于 2019-12-11 12:14:20
问题 Is the only difference between kimball and inmon, the Enterprise layer(EDW). I was googling around and found out that inmon also creates data marts using EDW. so does that mean, both these data marts are similar in structure for a given business process and source systems ? Once the data marts are readily available for both the procedures, do they give same performance ? correct me if i am wrong, the data warehouse is created first and then dimensional model is created on top of it for

Data warehousing principles and NoSQL

由 拟墨画扇 提交于 2019-12-01 00:44:38
with MongoDB, CouchDB and related technologies we can get faster querying so is this still valid? “A copy of transaction data, specially restructured for queries and analyses.” (R. Kimball The Data Warehouse Toolkit, 1996 I mean, do we really need to restructure our data to an OLAP scheme to query it for analysis purposes? More specifically can drill-down, slice and dice and other reporting for analysis purposes be achieved with NoSQL (NOT necessarily with OLAP modelling)? Also could we overcome the "data subset" querying limitation of OLAP and report on the whole data universe with NoSQL? In

Data warehousing principles and NoSQL

由 自闭症网瘾萝莉.ら 提交于 2019-11-30 19:17:06
问题 with MongoDB, CouchDB and related technologies we can get faster querying so is this still valid? “A copy of transaction data, specially restructured for queries and analyses.” (R. Kimball The Data Warehouse Toolkit, 1996 I mean, do we really need to restructure our data to an OLAP scheme to query it for analysis purposes? More specifically can drill-down, slice and dice and other reporting for analysis purposes be achieved with NoSQL (NOT necessarily with OLAP modelling)? Also could we
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