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In any given organization, there are a few BI projects that are marked as "suffering". I have been asked many a times as to why some projects in the BI psace are very successful and others suffer? The answer is very simple in my opinion. If your BI project is owned and driven by the business, the project has a potential to be very successful, on the other hand if your IT owns and drives the BI projects, chances of business aligning to use the end solution and adopt to it are not very high. Is organizational alignment the only answer?.
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Over the past years we have all been using the structured data content in the data warehouse to perform BI activities. But is that all the intelligence about a business there is? No, there is a lot more to the intelligence factor in the form of unstructured data.
Unstructured data is embedded in documents, reports, emails and notes. It is knowledge capital that is very useful when integrated for use in the data warehouse. Why do we need to wake up to this requirement? Consider an example scenario: there are hundreds of applications processed everyday in credit cards and consumer credit, insurance, etc. Not all of the decision-making notes are captured to the application. If this data was available for data mining and analysis purposes, we could build smarter decision-making engines since more pattern data is available. This is just a scratch of the surface, and there are more useful things that can be accomplished with unstructured data in the data warehouse.
Whenever one looks at Mt.Rushmore or the Eiffel tower, one admires the architecture and the technical finesse behind these constructions. Similarly when we see a fully functional data warehouse with all the bells and whistles on the input and output side, which provides sustained performance, we call it the perfect balance between hardware and software architectures.
When it comes to data warehousing and business intelligence programs, the tools that are needed to implement the pervasive side of the solution is one piece of the giant puzzle. The core of any initiative in this spectrum lies with the architecture.
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Microsoft has started its plans to compete in the cloud i.e internet cloud computing. With the announcement of SSDS featuring SQL Server services with storage being offered on pay per use, Microsoft joins amazon and Google in the cloud quest. While there may be differences in all the three offerings from the three vendors, the concept and Web 2.0 behind it as a key driver is powerful. Let us watch the moves as they happen.
Yahoo! hope you are listening to all this chatter.
I have been looking at this model of building a data warehouse by organizations where a corporate data warehouse is built and all its users are grouped by divisions or departments and charged for using the data warehouse. This is certainly a good model for the data warehouse team, especially if a corporate It team is owning the data warehouse. But there are a few issues that arise from this model
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Let us look at "ever hot" topic of Data Warehouse Architecture. What I define as the Data Warehouse Architecture, is a different perspective. The data warehouse ecosystem consists of layers of infrastructure ie. hardware, network, databases, storage, filesystems, operating systems, business intelligence tools and visualization layers. This is the first half of the spectrum. The second half of this spectrum is the data architecture, data model, data loading, data aggregation, data visualization, master data, metadata which presents a complete inside out perspective of the data warehouse architecture.
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In the last quarter of 2007, I had listed Operational reporting as a leading BI project for 2008 across the industry. Though I have no official surveys to check against, the feeling from the industry is that more companies are seeing the need for operational reporting and there is one project somewhere in the organization which is an operational reporting project.
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An spurt of activity is seen in the analytic appliances area. There are a number of companies working on this technology space in stealth mode. Why is all of this attention in this subject, is a matter worth discussing.
There are several key factors here, notable among them are
1. BI Acquisitions - With SAP and IBM acquiring players like BO and COGNOS, there is more room for new companies to compete with offerings.
2. Predictive Analytics - This area is going through a second coming. With the ability to process large volume of data, analytic appliances may provide a robust platform for predictive analytics.
There are more thoughts here to discuss. Let us see how this market shapes this year with the current established players and the yet to enter competition. Till then, your perspectives are welcome comments in this discussion.
Data management and architecture is becoming a nightmare for corporations. While the demand for more volumes of data at a greater detail keeps driving the IT resources, there are several issues that often get put on the shelf since the price point to manage the data and get it through the data warehouse becomes the focus of the implementation.
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We have been hearing and reading about the content of unstructured data and the potential it may unleash when integrated into the data warehouse. What is the operational value of this content and how to measure the value of such an integration effort.
Well if you are a healthcare or a pharmaceutical company, think of the vast amounts of data in your companies notes, emails, documents, research findings etc. Well if you rely on a document management system for all your document needs except the email portion, you have a good library.
Continue reading "A closer look at UnStructured data" »
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