Articles filed in category 'SSIS'

If you want to be a great SQL Server developer, you’ll want to pay attention to these 13 key points. Kevin Goff covers both best practices and common pitfalls of Business Intelligence.

Kevin leaves his SQL Server-focused Baker’s Dozen behind and launches into a new series looking at the various stages of data warehousing. His first installment includes a look at reporting and storage layers, handy tips, and dealing with the business side of development.

The new release of SQL Server's Integration Services has many exciting new features

Kevin takes a look at SQL Server “then and now,” and shows us just how important it is to understand the various tools involved in BI.

For over a decade, many Microsoft database developers have used SQL Server Analysis Services (SSAS) OLAP to create database cubes for advanced business analytics. SSAS OLAP offers many powerful features, although some developers view the learning curve of OLAP (and its supporting language, MDX) as very steep.

In this article, Kevin Goff provides a comprehensive guide to using XMLA commands for updating Microsoft SQL Server Analysis Services (SSAS) analytic databases, emphasizing that unlike relational databases, OLAP updates require batch-oriented XMLA processing rather than T-SQL DML. He presents 13 practical scenarios—including full and incremental processing of dimensions and fact tables, managing rigid attribute relationships, maintaining indexes, and leveraging SSIS and ....NET for automation—highlighting best practices and common pitfalls. Kevin’s detailed walkthrough equips developers with essential XMLA knowledge to efficiently populate, update, and maintain SSAS cubes in production environments.See More

In the last Baker’s Dozen article, I demonstrated 13 SSIS packages to show what Integration Services can do. This article picks up where the last one left off. I’ll show some capabilities in SSIS, such as handling irregular input files, extracting database changes, implementing package configurations, and leveraging the advanced lookup features in SSIS 2008.

Imagine you’re working for a company that has accumulated a tremendous amount of transaction data. The business users want to perform all sorts of analysis, monitoring and analytics on the data. Some OLTP developers might reply with, “Just create views or stored procedures to query all the data the way the users want.” Many companies initially take that approach - however, just like certain technologies and system hardware configurations don’t scale well, certain methodo...logies don’t scale well either. Fortunately, this is where data warehousing and dimensional modeling can help. In this article, I’ll provide some basic information for developers on the basics of data warehousing and dimensional modeling - information that might help you if you want to provide even more value for your company.See More