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Database management depends on structure -- of reality and of data representing it in databases -- which determines the data manipulation and integrity enforcement by database management systems (DBMS).

Having argued this for decades I have been, predictably, quite skeptical of the hype of systems that manage and extract information from so-called "unstructured data," purportedly obviating the need for business modeling and database design. It's also why I've been skeptical of the criticism of SQL-based DBMS as inflexible because they force big data, much of it text, into tabular schemas in which it doesn't fit or that is difficult to envision upfront. 

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See N-ary vs. Binary Relations: Anatomy of a Compound Misconception

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1. Quote of the Week.

My best advice in all architecture, and platform choices, like RDBMS vs NoSql. The number 1 question, every single assumption you have about the system, the "this is important because X Y X and this that etc etc. Every single "has to be" you have there, expect every single part of it to change. How would you build your system if every "key fact" was expected to change. These key facts, that are supposed to be pillars are actually volatility themselves and need accounted for, not accepted. --LinkedIn

2. To Laugh or Cry?

How can we add employees, dept and location tables in oracle 10g?

3. Online exchanges I participated in

I am referring you back to an item I posted in last update:

What is a Data Model And which “Data Model” do you prefer?

for two reasons: comments were added since then that should be read, some of which belong in the "To Laugh or Cry" category.


4. What do these two items tell you?

Next gen NoSQL: The demise of eventual consistency

Currently search engines are thought of as tools to find text but Ashok Chandra, Microsoft distinguished scientist and general manager of the Interaction and Intent Group at Microsoft Research Silicon Valley, believes people soon will think of search engines as “task engines.”

“Search technology began with words,” says Chandra.  “We built a whole search infrastructure around words. But in this new era of search, we are working with entities, because people think in terms of them, such as a hotel, a movie, an event, a hiking trail, or a person. The Leibniz platform is designed from the ground up to deal in entities, with the goal of making it easier for people to accomplish the tasks they set out to do.”

--A Look Microsoft’s ‘Leibniz’ Platform

BTW, I love "Interaction and Intent Group". Wonderful.


5. And now for something completely different.

 I Challenged Hackers to Investigate Me

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See Date Model: The RDM Is, the E/RM Isn't



 

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1. Quote of the Week

Can any one guide me, how to search specific value in all database table? in output we required tables and columns name.
--LinkedIn.com

2. To Laugh or Cry?

Go On, Live a Little. Denormalize Your Data

3. Online

My October post @All Analytics

Big Data Uber Alles

A follow-up exchange to previous exchanges on my post E/RM Is Not a Data Model.

What is a Data Model And which “Data Model” do you prefer

My own follow-up is forthcoming here.


4. I've done some house cleaning and found some links that I accumulated at various points in time that I deemed worth reading, but which fell victims to lack of time. They may be interesting or useful to others, so I list them here.

On SQL:

• Comparison of different SQL implementations
• Common MySQL Queries
• SQL Database Design
• SQL Relational Algebra Examples

On relational technology:

• Why Programmers Don’t Like Relational Databases
• The Vietnam of Computer Science

General:

• Simple Made Easy
• How do we tell truths that might hurt
• Out of the Tar Pit

5. And now for something completely different: the wastebasket and the barber.

• Who Is NYSE CEO John Thain 
• Canned Merrill Lynch CEO John Thain's spending spree included $1,200 trash bin 
• Reporter's Notebook At The NYSE 
• NYSE's `Jerry the Barber' to Close After Exchange Goes Public

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1. Quote of the Week

... MongoDB, or RavenDB ... are excellent for non-relational, loose schema databases. Databases always have schemas, the data is the schema, inherently in dbs like Raven & Mongo.
--LinkedIn.com

2. To Laugh or Cry?

Easy Steps to a Complete Understanding of SQL

3.  Three online exchanges on my E/RM post in which in participated.

Entity-Relationship Model Not a Data Model

Entity-Relationship Model Not a Data Model

Entity-Relationship Model Not a Data Model

The last one is an excellent validation that many data professionals erroneously believe they know and understand the RM--which prevents them from appreciating its value and doing something about it. It also demonstrates that schooling is not education.

I may tackle some of the comments in a future post.


4.  How much would you bet against my suspicion that there is little/superficial, if any, relational
background to this?

SQL Database for Beginners

  
6.  And now for something completely different

 From article on Marissa Meyer:

They say her obsession with the user experience masks a disdain for the money-making side of the technology industry. There is some truth to what they say ... Mayer joined Google as a programmer and rose to become the executive in charge of the way Google search and many other popular Google products looked to web users ... She obsessed over pixels; their hue, shade, and placement. She co-authored a handful of patents, including an important one for Google: "Graphical user interface for a universal search engine." By 2005, Mayer moved into management, overseeing the look and feel of Google's most important products ... But being in charge of how Google products should look, Mayer's job was, basically, to relate with Google's millions of users. How would she do that? ... The first is that she would recreate the technological circumstances of her users in her own life. ...  Mayer's second method was to lean on data. She would track, survey, and measure every user interaction with Google products, and then use that data to design and re-design.

Wow, and after all this the user interface of all Google's online services sucks, they are buggy and there is practically no user support? Imagine what will happen without Marissa Meyer there!

And, oh, the cultural sophistication of the technology elite. Helps understand their output.

2013 Tour de Coop Chickens, Beehives & Homesteads Silicon Valley Funcheap

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Expertise in a field and ability to convey it to others are distinct and the latter requires different motivation, skills and talent. Many top technical experts are more often than not poor communicators, whether verbally or in writing, for some inherent reasons, Codd being an excellent example. That's one of the core reasons for poor foundation knowledge in data management in general, and the appreciation of the relational model in particular.

In a previous post I started a little experiment: I asked both readers who think they know and understand the relational model (RM) and those who do not but want to, to comment on whether a theoretically correct explanation of data fundamentals offered by reader PK was helpful and, if not, why not. I promised to draw some conclusions regarding the difficulty of dispelling misconceptions without losing either theoretical rigor, or the audience--a non-trivial task for an educator in an industry that deems theory impractical.

I can't say the response exactly answered my question (I recommend reading the comments, though). But let me, as promised, try my hand at making better sense of both the explanation and the comments (for an in-depth treatment see paper #1, Business Modeling for Database Design). Let me know if it helps..