Browsing articles tagged with " Snark"

What Your Database Security Design….

Jul 15, 2015   //   by Karen Lopez   //   Blog, Data Modeling, Database Design, DLBlog, Fun, Snark, WTF  //  3 Comments

…looks like to me.

Sure, you’ve got your own home-grown database security system all designed and working in development.  And then you ask me to confirm that it’s “safe”. I’ll tell ya “it’s safe as long as you don’t actually put any data in it”.

I’m all ‘bout the data…

Dec 5, 2014   //   by Karen Lopez   //   Blog, Data, Data Governance, Fun, Parody, Snark  //  No Comments

AllAboutTheData

I Welcome You All to Cloud Cuckoo Land! #NoSQLKitty

Mar 5, 2014   //   by Karen Lopez   //   Awesome, Blog, Data, Fun, NoSQL, Parody, Snark  //  2 Comments

I introduce to you, NoSQKitty

 

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With this dialog, I had to do this. I had no choice, really.  Trust me. Just ask Biznis Kitty.

Emmet: I’m just gonna come right out, I have no idea what’s going on or what this place is at all.
Unikitty: Hi! I am Princess Unikitty, and I welcome you all to Cloud Cuckoo Land!
Emmet: So there are no signs or anything. How does anyone know what not to do?
Unikitty: Here in Cloud Cuckoo Land, there are no rules. There’s no government, no baby sitters, no bedtimes, no frowny faces, no bushy moustaches, and no negativity of any kind.
Lucy: You just said the word "no" like a thousand times.
Unikitty: And there’s also no consistency.
Batman: [the clown and the lizard man are dancing around him] I hate this place.

Every single line in that scene had me choking on my popcorn.  There’s a blog post in each one.  No rules? Nope, not in schemaless.  No signs? Nope.  No bedtimes? Nope, none. As a matter of fact, I want to make up t-shirts with each of these lines. Everything is Awesome about them.

I’m not anti-cloud, at all.   Nor am I anti-NoSQL (Hey, I know that’s a double negative.  Don’t blame me that the name NoSQL seriously needs rebranding.)    Plus, with a Starbucks name of Kitty, this is *so* my character.  Cloud Cuckoo Land and all.

*And I really do get what eventual consistency is all about. I know it means there is consistency. I know when it’s perfect for solving a problem.  I’m just quoting Unikitty.  Blame her.  But watch out for Angry Kitty if you do that.

Data Modeling…Data, Numbers and Bikinis

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My Twitter friend Geoff Crane ( blog | @papercutpm ) made this for me today.  So I’ll just leave it here for you.

Romancing the Data….

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Today is Valentine’s Day in many parts of the the world.  That means either you are looking forward to a happy day full of fun and a night full of …fun… or you are are planning on catching up with Frank Underwood on Netflix.  Both sound great to me.

Last year I wrote about 5 Naughty and Nice Ways to Love Your Data.  This year I’m going to focus on ways you can romance your data for a stronger, more lasting relationship.  So I’m assuming in the past you’ve followed my advice and have long since left the honeymoon phase of your data coffee dates.  But where are you now?  Are you starting to feel like maybe you need some more passion with your bits and bytes?  I’m here to help.

1.  Tell your data you love it.  Often. 

Heck, even show it you love it. Maybe one of the reasons your data has let itself go is that you haven’t told it how much you love it. Do you even remember the things you used to say to woo your data when you first met?  Do you have actively managed data models: conceptual, logical, and physical?  Do you give your database objects great names?  Do you keep good metadata about this data?  Do you follow data model-driven development? If you did all these in your early years of your relationship, are you still doing all that now? Are you doing all this in a modern way, not just the way you did it in 1980? Do you just talk a good game, but fail when it comes to actively showing it love?

Some day, when I’m awfully low,
When the query is slow,
I will feel a glow just charting  you
And the way you look tonight.

You’re lovely, with your axes so true
And your bars so blue
There is nothing for me but to report you,
And the way you look tonight.

With each crow’s foot your normalization grows,
Tearing my pages apart
And that CHAR that wraps your text,
Touches my foolish heart.

Yes you’re lovely, never, ever refactor
Keep that structured charm.
Won’t you never change it?
‘Cause I love you
Just the way you look tonight.

Data FTW Candy Heart.

2. Stop with the games. 

We’ve all seen it in personal relationships.  One person makes everything a game.  Do you store your data in one format, say ZIPCodes as INTEGERS, but have to pad out all those missing leading zeros every time you have to deal with North Eastern United States postal codes?  Stop doing that. Do you pretend that doing something faster is always better than doing it good enough?  Forget perfect. Good enough.  Do you tell management you have data models but all you really do is reverse engineer them?   It’s all games.

Daylight, alright
I don’t know, I don’t know if numbers are REAL
Been a LONG night and something ain’t right
You won’t SHOWPLAN, you won’t SHOWPLAN how you feel

No DATETIME ever seems right
To talk about the reasons why CAST and I fight
It’s DATETIME to end the TIMESTAMP
Put an end to this game before it’s too late

Data games, it’s you and me baby
Data games, and I can’t take it anymore
Data games, I don’t wanna play the…
Data games

HAWT Data Candy Heart.

3. Know where your data lives

Do you have an active inventory of what data resides where?  No?  How can you romance data you don’t know about?  If a server walked out the door of your organization, how long would it take you to figure out what was on it?  If a user had a legal need to access all the data the company held about a customer, would you be able to tell them?  If you really wanted a happy strong relationship with your data, you’d know.  Yes, it’s a lot of data to track where you data is.  That’s why they invented tools that do this.  And why data professionals are expected to use them.

Data is bigger
It’s bigger than the drives and they are not PB
The servers it is spread to
The bits in your drives
Oh no, I’ve duplicated too much

I set it up
That’s me in the ETL
That’s me in the database
Losing my governance
Trying to keep up with it all
And I don’t know if I can do it
Oh no, I’ve deployed too much

I haven’t documented enough
I thought that I heard you laughing
I thought that I heard you coughing
I think, I thought, I saw you cry

Data Kisses Candy Heart.

4. Stop faking it.

Yeah, sometimes little white lies are good for a relationship (BTW, You DO Look Beautiful!).  But the big ones? Nope, never.  The paranoia about NULLs often leads to a lot of lying.  Do you pretend that NULLs don’t exist by giving them various fake values like 999999 or N/A, UNKNOWN, WHO KNOWS or  __ ?  Does every developer get to choose their own NULL Imposter Text?  Are your aggregates all a huge lie due to all those zeros and 1980s dates you use to lie to your database?  Stop it.  It’s not helping that your queries are 2 ms faster when the data is one big lie.

Late at night a big database gets slower
I guess every normal form has its price
And it breaks her data to think her love is
Only given to a user with queries as fragile as ice

So it tells me it all adds up just fine
To aggregate the sales numbers for every town
But only the dev knows where those NULL have been killed
And it’s is headed for the cheatin’ UNKNOWN town

You can’t hide your lyin’ nines
And your N/A is a thin disguise
I thought by now you’d realize
There ain’t no way to hide your lyin underlines….

Sexy Data Candy Heart.

5. Protect it.

Do you l et just anyone throw code at your data without ensuring it’s treated right?  Do you participate in security and privacy reviews of application code?  You have those, right? Do you have metadata that describes the privacy and sensitive data requirements for each data element? Do you ensure that things like SQL injection tests happen for every application?

Oh where, oh where can my data be?
The dev took her away from me.

She’s gone to pastebin, so I’m gonna be sad, 
So I can see my data, by now I’m so mad.
We were out on a date in my modelling tool,
I had been too much a fool.

There in the database, all laid out,
a data was there, the database queried by a lout.
The dev allowed the inject, the data failed to be right.
I’ll never forget, the sound that night–
the screamin users, the bustin app,
the painful scream that I– heard crash.

Oh where, oh where can my data be?
The dev took her away from me.
She’s gone to pastebin, so I’m gonna be sad,
So I can see my data when my new job is had.

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Keep saying it. Keep doing it. 

There’s so much more you can do to revitalize your relationship with data.  But if you do these, your data will keep on loving you back. I promise.  Remember, you data wants to love you back. It’s up to you to make sure it’s still there in morning.

#SQLLinkBait Contest Winner (CLICK HERE NOW!)…

Sep 16, 2013   //   by Karen Lopez   //   Awesome, Blog, Data, Fun, Snark, SQL Server  //  4 Comments

Recently on Twitter I ran a fun contest to come up with the best SQL blog post title link bait.  Link baiting is a controversial approach to blogging.  The term itself is controversial actually.  In some contexts it just means using a great title.  But this contest was looking for the the best example of a different use of the term, one that’s a little bit more on the dark side of blogging:

Linkbait Definition #2 – “Attracting Link Attention with Controversy”
A lot of folks seem to suggest that certain things people write on the web or create on their sites are “just for the linkbait” – these can include negative or derogatory pieces, inflammatory material, and anything else that designed to incite or provoke a reaction from one or many online communities or blogs.

From <http://moz.com/blog/the-two-kinds-of-linkbait>

That’s the definition I was going for in this contest.  An snark we did receive.   I think this means that the SQL & Twitter communities have seen a lot of linkbaiting.  This was a short contest, with just under 300 posts and about 100 people participating in the conversation, but it reached more than 1 million potential impressions.  That’s the power of social media.

(click to enlarge this chart)

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The full report on this hashtag can be found at http://keyhole.co/realtime/zA3oKj/

 

Some honourable (dishonourable?) mentions:

Our crack team of judges – Allen Kinsel ( blog | @AllenKinsel ), Thomas LaRock ( blog | @SQLRockstar ) and I picked  Tracy McKibben’s ( blog | @RealSQLGuy ) entry.  I’ll be DMing you, Tracy, with info for collecting your prize pack.  I sure hope you are following me (hint, hint).

I’d love to see some of you take this challenge to heart and write those blog posts.  Hmmm.  Maybe a new contest idea?

Update: It seems that Twitter or WP is having a bit of an issue rendering some of the tweets. Perhaps they will fix this data quality problem soon. Anyway, congrats Tracy.

NULLs

Mar 13, 2013   //   by Karen Lopez   //   Blog, Data, Data Modeling, Database Design, Fun, Snark  //  3 Comments

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