Relational Databases are Not Easy to Use; They are Easy to Abuse

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Relational databases are often advertised as easy to use – that’s true for a single table. However a database of hundreds or thousands of interconnected tables is complex and difficult to use. It is not helpful for marketers to set such misleading expectations – all it does is lead to frustration when projects overrun on cost and time and sometimes fail.

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Use Cases Are Overblown

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A use case is a piece of functionality that an app can perform. Each app has many use cases and the use cases taken collectively specify the app’s functionality. For an example, consider an app for tracking library loan records. Some use cases are: borrow books, borrow magazines, return books, return magazines, renew books, renew magazines, pay fines, get library card, and change address.

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Ten Reasons Why You Should Use Data Models to Build Apps

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Most business applications revolve around databases that store and retrieve data. If you are building a business app, a data model can help you understand that data. Utilizing the model as a blueprint can help determine what data is involved and how it is organized. Data models have many benefits. Here are 10 of them:

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Data Modeling Zone 2015

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Mike Blaha will be at Data Modeling Zone (October 5-7, 2015 in Chapel Hill, NC) and will be presenting twice at the conference.

  • Monday October 5, 12:00-1:00 PM — Data Modeler 2020 – Future of Data Modeling Panel
  • Tuesday October 6, 2:15-3:15 PM — Advanced SQL Queries
Save 20% by using the code “BLAHA” in your registration for Data Modeling Zone. Send us an email (blaha@computer.org) if you do and we’ll give you one of Michael Blaha’s books.

What Is Big Schema?

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“Big Data” has become a popular buzzword. Big Data is data that is so massive that it is difficult to manage. For example, the volume of search engine queries, online retail sales, and Twitter messages exceed the capabilities of traditional databases.

There’s a complement to “Big Data” that we call “Big Schema”. Today’s data can not only have vast quantities and fast rates, but can also have diverse structure. Big Schema can arise with enterprise data models, large data warehouses, and scientific data.
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