¶ … components of BI. Distinguish between traditional and operational BI.
BI, or Business Intelligence, is very important to companies. It takes raw data and turns it into useful information, so the business can take it and use it to find ways to make things better for customers and for themselves (Rausch, Sheta, & Ayesh, 2013). A company can recognize the need for BI by studying the data it has been collecting and how that data is used. It is very important that data is only collected if it is needed, and many companies collect a huge amount of data that they do nothing with. That wastes a great deal of time and money that could be better spent, and also fails to get the data that is needed properly analyzed (Rausch, Sheta, & Ayesh, 2013). There are a number of components to BI, including multidimensional aggregation, real time reporting, denormalization, interfacing with the source of unstructured data, and group consolidation (Rausch, Sheta, & Ayesh, 2013).
Additional components are statistical inference, the optimization of key performance indicators, process management, version control, and the management of open items (Rausch, Sheta, & Ayesh, 2013). Understanding the components of BI is a great way to provide historical and current views of the operations of a business, as well as to predict what might take place in the future (Rausch, Sheta, & Ayesh, 2013). There are two types of BI: traditional and operational. Traditional BI is based on handling data the way it has always been used for business operations, and operational BI is focused on addressing a particular operation and how the data for it is considered and processed (Rausch, Sheta, & Ayesh, 2013).
Rausch, P., Sheta, A., & Ayesh, A. (2013). Business intelligence and performance management: Theory, systems, and industrial applications. UL: Springer Verlag.
2. What is data latency? How does giving users the ability to create their own reports reduce data latency? What is the age of fresh data?
Data latency is the length of time it takes for the data to appear after a query has been initiated, and can also refer to how long it takes for a database to update after a change has been requested (Rud, 2009). With that in mind, companies have to carefully assess their data latency issues, because a serious lag time can become a problem for customers -- and a problem for customers can quickly become a problem for the company. One of the ways to help reduce data latency times is to give users the ability to create their own reports (Rud, 2009). That reduces latency because they are not waiting for others to update information for them, so they can create reports. Additionally, they are not relying on the reports of others, which may or may not have updated data. Both of those options are important to consider, as both can cause significant difficulties for people who are serious about data latency and the avoidance of it for both employees and customers.
Data should be given to those who need it as soon as possible (Rud, 2009). It is important to collect any and all data that your company can easily use to move the business forward, and it is also important to make sure the right people get that data. However, none of that will be useful if those people do not receive the data at the right time. Getting old, stale data does nothing for the company or business, and can even hurt a company by keeping its employees misinformed regarding what can and should be important to customers (Rud, 2009). When a company collects data and quickly sends it to the people who need it, it can remain fresh and be processed in a way that helps everyone involved.
Rud, O. (2009). Business intelligence success factors: Tools for aligning your business in the global economy....
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