Big Data has become the latest craze within the IT community, revolutionizing business intelligence capabilities. But what is it really--and how will it impact our community? Here are some tips for the PM to evolve with this emerging trend.
Inevitably, the intersection of big data and the idea of the quantified self (the hot movement of the moment) is going to show up in project management. Think of it as the “quantified project” where just about everything about a project can be measured, reported on and managed. Arguably, someone may be trying to invent this very thing right now. But should they?
You might have heard about the “Big Data” craze. The rush is on, and like Cloud Computing it’s gaining momentum fast. So what is all the fuss about? What exactly is Big Data and why should we care?
This Microsoft Project Plan will walk you through the ins and outs of putting together a business question assessment to analyze the data you need for your data warehouse.
Need to plan a data warehouse project? This synopsis outlines the steps, deliverables and team roles for strategizing, architecting, designing and planning the implementation of a data warehouse.
Map the transformation of the data elements from source system tables to data warehouse target tables.
How do you select the best data extraction/transformation toolset for your data warehouse? Evaluate features, functionality, vendor reputation... the works. Follow the example set by this robust tool evaluation.
A handy spreadsheet for recording Data Warehouse QA issues, from data transformation to report generation problems.
There's a lot to consider when selecting a Data Warehouse toolset. Use this comprehensive tool evaluation matrix to guide your final selection.
This Microsoft Project plan can serve as a guide to evaluating vendor tools for your data warehouse. It includes a Gantt chart schedule and cost analysis for the complete tool selection process.
Are you putting together a data warehouse? This Microsoft Project plan will help you keep tabs on all the complex stages and steps involved in building decision support systems and a knowledge-based applications architecture and environment.
This presentation presents a framework and industry best practices allowing for the definition of usable metrics and intelligence that employ all the available operational data in the organization from the shop floor activities to business operations
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"A pessimist sees the difficulty in every opportunity; an optimist sees the opportunity in every difficulty." - Winston Churchill |
