Articles
Avoiding Pitfalls in a BI Initiative
By Sherman Kong, Business Intelligence Practice Leader,
Broadstreet Data Solutions
“87% of BI-related initiatives in the United Kingdom alone have failed to live up to stakeholder expectations”
Most organizations have been pitched the hypes and values that Business Intelligence (BI) brings to the table. BI is widely recognized as an effective practice of data collection and Information Access. Knowledge would be modeled and fed to different entities of a company to streamline business analysis and in turn improve the efficiency of its daily operations and strategic planning.
Informatica PowerCenter Metadata Manager and its use in a Data Integration project
By Kevin Madrick, Senior Director, Data Integration Practice
So you have PowerCenter Advanced Edition, and it comes with this Metadata Manager tool. What is it? What do you use it for? How is another tool going to make your job easier?
Metadata is normally defined as “data about data”, which is a pretty generic concept. In the context most of us use Metadata, it’s the sources, targets, mappings, etc in PowerCenter, as well as the databases PowerCenter extracts from and loads to, and the BI tools that report against the databases. That sounds like a lot. There’s a lot of documentation on how to load the tool, but what do you do with it then?
Evolution of Search: Information Access and Guided Summarization
By Dinesh Chand, Senior Consultant – Information Search & Access, Broadstreet Data Solutions
It all began with their inability to understand human-friendly or unstructured data. Yes, I am talking about computers. The position of data became more important than the content or the context of the data in order to use it effectively with the computer. Rows and Columns became the norm of the day.
7 Ways to reduce ETL project cost and risk
By Karthik Muthuraman, Practice Manager - Business Objects Data Services
ETL as a tool has evolved over time, from being used only for data warehouse to being used anywhere there is significant movement of data and data transformation required. And it continues to evolve.
Data Quality Assurance in Enterprise Data Warehousing from a Risk Management Standpoint
By Beng Lim, Data Quality Practice Lead, Broadstreet Data Solutions
Data Quality is the state of completeness, validity, consistency, timeliness and accuracy that makes data appropriate for use.
There is no nightmare worse than lost or disappearing profits due to poor decisions made based on incorrect data. If not rapidly addressed, the long term viability of the corporate entity itself may even be threatened.
How can reliable information be obtained then…
