I cannot tell you how many times I have had customers that do not have a specific vision for their data. What I mean by this is that there is no data strategy.
In a number of recent posts, we have discussed the issues that surround big data, largely looking at the need to access data from a number of sources of variant structure and format. From the perspective of the analytical environment, this has not only complicated the population of data warehouses
To allow file uploads into your business intelligence environment or not to allow file uploads – what is your decision? I have a tendency to look at this issue like this: Someone on the business side needs this data – and probably needs to looking at existing data another way. For example,
Last time we began to look at the opportunity for integrating a newly developed master data repository with existing business applications supported by a data warehouse. That meant understanding the requirements for integration and verifying that those requirements are met.
I am asked quite frequently whether a company needs master data. Actually, I believe everyone has master data, it just depends on whether your company wants to manage their master data or not.
David Loshin discusses master data model requirements.
When I first thought about writing a blog post about data management, picking a topic was an obvious, if daunting, first step. The challenges facing both IT and business are increasing in the era of bigger, more complex and more immediate data. My experience working with organizations across a variety
@philsimon on innovation from a very unlikely source.
New blog post by Dylan Jones (@dataqualitypro): Why Data Quality Becomes Critical to CEP.
This is the second in a series of posts about the topic of data federation. Click here for the full series. In the previous post, I described the basics of data federation and how the technology can be useful in today’s complicated IT environments. Next, let’s apply data federation to some real-world
