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Iterative (and Incremental) Warehouse Development

We have often discussed the concept of using an iterative methodology when constructing a data warehouse, and have detailed the benefits of such an approach: better alignment with business needs, faster delivery of results, better return on the investment and overall lower development costs, just to name a few. However, it is also important to […]

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Data Science and Agile Methodology

Last week Kalido hosted a webinar entitled “Data Scientist: Your Must-Have Business Investment NOW.”   The panelists (Carla Gentry, David Smith and Gregory Piatetsky) spoke eloquently about the role of the Data Scientist and the types of analysis they perform. In case you missed the webinar, a Data Scientist is someone that looks at data with […]

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Building an Agile Data Warehouse – Part 2

Tools for Agile Data Warehousing

If you accept the concepts of Agile Data Warehousing you quickly will discover that the traditional toolset (modeling tools, ETL tools, etc.) bring little to the table to advance an agile methodology.  As we saw in part one, acquiring a pre-built model can help focus some of the requirements gathering, but it does little to […]

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Building an Agile Data Warehouse – Part 1

Prebuilt Models That Aren’t

Data warehouses are hard to build.  The goal, of course, of any data warehouse is to house all the data required to provide the business with the answers needed to run the business effectively.  The problem is that the questions keep changing and evolving.  This is compounded by the fact that building an enterprise level […]

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There is no such thing as “Unstructured Analysis”

There is a lot of interest in unstructured data these days.  Whether this is the more “traditional” forms like video and other large bit-stream objects or things like clickstream data from the web, lots of people are devoting lots of time and effort towards the creation and management of systems to collect and store this […]

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