What are the 5 reasons that business analysis is difficult from operational databases?

In the 1990s as organizations began to need more timely information about their business, they found that traditional operational information systems were too cumbersome to provide relevant information efficiently and quickly. Operational systems typically include accounting, order entry, customer service, and sales and are not appropriate for business analysis for the following reasons:

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Sorry, I Didn't Mean to Post Your Social Security Number on the Internet Programming 101 teaches all students that security is the crucial part of any system. You must secure your data! It appears that some people working for the state of Oklahoma forgot this important lesson when tens of thousands of Oklahoma residents had their sensitive data—including numbers—posted on the Internet for the general public to access. You have probably heard this type of report before, but have you heard that the error went unnoticed for three years? A programmer reported the problem, explaining how he could easily change the page his browser was pointing to and grab the entire database for the state of Oklahoma. Also, because of the programming, malicious users could easily tamper with the database by changing data or adding fictitious data. If you are still thinking that isn't such a big deal, it gets worse. The website also posted the Sexual and Violent Offender Registry. Yes, the Department of Corrections employee data were also available for the general public to review.    Why is it important to secure data? What can happen if someone accesses your customer database? What could happen if someone changes the information in your customer database and adds fictitious data? Who should be held responsible for the state of Oklahoma data breech? What are the business risks associated with data security?

   During the latter half of the 20th century, the numbers and types of databases increased. Many large businesses found themselves with information scattered across multiple platforms and variations of technology, making it almost impossible for any one individual to use information from multiple sources. Completing reporting requests across operational systems could take days or weeks using antiquated reporting tools that were designed more or less to execute the business rather than run the business. From this idea, the data warehouse was born as a place where relevant information could be held for completing strategic reports for management. The key here is the word strategic as most executives were less concerned with the day-to-day operations than they were with a more overall look at the model and business functions.

   A key idea within data warehousing is to take information from multiple platforms/technologies (as varied as spreadsheets, databases, and word files) and place them in a common location that uses a common querying tool. In this way operational databases could be held on whatever system was most efficient for the operational business, while the reporting/strategic information could be held in a common location using a common language. Data warehouses take this a step further by giving the information itself commonality by defining what each term means and keeping it standard. An example of this would be gender, which can be referred to in many ways (Male, Female, M/F, 1/0), but should be standardized on a data warehouse with one common way of referring to each sex (M/F).

   This design makes decision support more readily available without affecting day-to-day operations. One aspect of a data warehouse that should be stressed is that it is not a location for all a business's information, but rather a location for information that is interesting, or information that will assist decision makers in making strategic decisions relative to the organization's overall mission.

   Data warehousing is about extending the transformation of data into information. Data warehouses offer strategic level, external, integrated, and historical information so businesses can make projections, identify trends, and decide key business issues. The data warehouse collects and stores integrated sets of historical information from multiple operational systems and feeds them to one or more data marts. It may also provide end-user access to support enterprisewide views of information.

What is an operational database used for?

What is operational database example?

Which of the following represent the five common characteristics of high quality information check all that apply?

In which ways does a data warehouse enable business users to be more effective?