Telerik blogs
  • Productivity

    Building a Data Warehouse Part IV: Extraction, Transformation, and Load

    [repost from Stephen Forte's Blog] See also: Part I: When to build your data warehouse Part II: Building a new schema Part III: Location of your data warehouse In Part I we looked at the advantages of building a data warehouse independent of cubes/a BI system and in Part II we looked at how to architect a data warehouse’s table schema. In Part III, we looked at where to put the data warehouse tables. Today we are going to look at how to populate those tables and keep them in sync with your OLTP system. No matter where your data warehouse is located, the biggest challenge with a...
    September 28, 2010
  • Productivity

    Building a Data Warehouse Part III: Location of your data warehouse

    [repost from Stephen Forte's Blog]   See also: Part I: When to build your data warehouse Part II: Building a new schema In Part I we looked at the advantages of building a data warehouse independent of cubes/a BI system and in Part II we looked at how to architect a data warehouse’s table schema. Today we are going to look at where to put your data warehouse tables. Let’s look at the location of your data warehouse. Usually as your system matures, it follows this pattern: Segmenting your data warehouse tables into their own isolated schema inside of the OLTP database Moving the data warehouse...
    September 27, 2010
  • Web

    Building a Data Warehouse Part II: Building a new schema

    [repost from Stephen Forte's Blog] In Part I: When to build your data warehouse we looked at when you should build your data warehouse and concluded that you should build it sooner rather than later to take advantage of reporting and view optimization. Today we will look at your options to build your data warehouse schema. When architecting a data warehouse, you have two basic options: build a flat “reporting” table for each operation you are performing, or build with BI/cubes in mind and implement a “star” or “snowflake” schema. Let’s take a quick look at the first option and then we will take a look at...
    September 22, 2010
  • Productivity

    Building a Data Warehouse Part I: When to build your data warehouse

    [repost from Stephen Forte`s Blog] Most developers are scared of “Business Intelligence” or BI. Most think that BI consists of cubes, pivot/drill down apps, and analytical decision support systems. While those are very typical outcomes of a BI effort, many people forget about the first step, the data warehouse. Typically this is what happens with a BI effort. A system is built, usually a system that deals with transactions. We call this an OLTP or on-line transaction processing system. Some time passes and reports are bolted on and some business analysts build some pivot tables from “raw dumps” of data. As the system grows, reports start to slow...
    September 21, 2010
  • Release

    New goodies in the Q2 Release of Telerik OpenAccess : Part II

    Yesterday Telerik released the Q2 version of OpenAccess ORM as well as the rest of the product line. Yesterday (Part I) I showed you the menus, Data Service Wizard, and new XAML templates. Today I will show you round tripping. Next week I will talk about RIA Services and model first. OpenAccess Q2’s new LINQ implementation and Visual Designer introduces database round tripping.  Now you can make changes in your model and persist them to your database table. (You always had the ability to make a database schema change and refresh your model.) Let’s see this feature in action. The Model Schema Explorer gives you a view of your mapped entities. If...
    July 16, 2010