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The Voice of the DBA

What Data is Really Needed?

The GDPR took effect in May of this year, at least with regards to enforcement. A few days after the May 25 date, a German court ruled against ICANN, the company that registers domain names on the Internet and manages the global WHOIS database. The case revolves around the information collected when you register a domain. ICANN wants multiple contacts, which they've required for decades. However, a company in Germany that is a partner, argued that the additional technical and administrative contacts were not required for fulfilling the business that both ICANN and EPAG (the German registrar) are engaged in. ICANN Is appealing the ruling, citing the need for clarification of what this means with regard to the law.

This is interesting to me, because a) it concerns data, and b) there is an interesting argument here to be made about what data is needed for a business purpose. I could see this being argued successfully either way, and not just in court. As a domain holder, does the registrar really need multiple different sets of personal information from me? Arguably, this is a convenience for them, one that is based on tradition. However, one could argue the other way.

It is a little scary that a court, with no expertise in some industry (Internet domain registration, in this case), will decide if there is an actual business need. After all, can a lawyer or judge really understand what data a business needs in their daily activities? 

Maybe, maybe not, but I do think this forces businesses to actually stop and think about what data they collect, have a justification, and document that. That's a good thing, because often I find business people just asking to collect data without any idea what they'll do with the information. I also find technical people collecting data, not maliciously, but often to anticipate what might be asked of a system, or because they want to avoid rework and just decide to collect everything they can.

Data is precious, and while I don't want to put many limits on what data businesses can collect, I also don't want to them be able to collect anything, not disclose what they've collected, and not secure it properly. Having some limits, or at least forcing them to consider the risk of holding old, useless data, is likely a good thing for all of us.

Steve Jones from SQLServerCentral.com

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Question of the Day

Today's Question (by Steve Jones):

I have this code to create a table and add an index.

 CREATE TABLE dbo.PurchaseOrder ( PurchaseOrderKey INT IDENTITY(1, 1) NOT NULL CONSTRAINT PurchaseOrderPK PRIMARY KEY , PONumber VARCHAR(100) , CustomerName VARCHAR(100) , PODate DATETIME , PODetails XML ); GO CREATE PRIMARY XML INDEX PurchaseOrderXML ON dbo.PurchaseOrder (PODetails); GO 

I now run this:

 ALTER TABLE dbo.PurchaseOrder DROP CONSTRAINT PurchaseOrderPK GO 

What happens?

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Yesterday's Question of the Day

Yesterday's Question (by Steve Jones):

I have a data frame in R that I am using to track my travel for the year. The data looks like this:

 > travel Passenger FlightDate Destination Miles Dollars 1 Steve 20180225 LHR 11789 1100 2 Steve 20180512 LHR 10989 1500 3 Steve 20180620 LHR 11789 1800 4 Steve 20180830 LHR 11789 1100 5 Steve 20181015 LHR 9678 2700 6 Steve 20181212 LHR 10520 1500 7 Steve 20180810 MSY 2427 440 8 Steve 20180225 OSL 1502 210 9 Steve 20180225 DCA 1475 310

I want to convert this from a wide format to a long format that I will use to plot my consumption of both distance and cost. I plan on trying to get this format of data:

 Passenger Destination variable value 1 Steve LHR Miles 11789 2 Steve LHR Miles 10989 3 Steve LHR Miles 11789 4 Steve LHR Miles 11789 5 Steve LHR Miles 9678 6 Steve LHR Miles 10520 7 Steve MSY Miles 2427 8 Steve OSL Miles 1502 9 Steve DCA Miles 1475 10 Steve LHR Dollars 1100 11 Steve LHR Dollars 1500 12 Steve LHR Dollars 1800 13 Steve LHR Dollars 1100 14 Steve LHR Dollars 2700 15 Steve LHR Dollars 1500 16 Steve MSY Dollars 440 17 Steve OSL Dollars 210 18 Steve DCA Dollars 310 

What function should I use?

Answer: melt(travel, id.vars = c("Passenger","Destination"), measure.vars = c("Miles","Dollars"))

Explanation:

The data is currently in a wide format, with multiple measures of values listed in columns. To shorten this to a long format, we use the melt() function, specifying which values are to be retained and repeated, and which values are to be combined into a column.

Ref: Melt() - click here

Reshaping data - click here


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