Master Data Services: Analogy to remember what are Models, Entities and Attributes

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Let’s understand master data services terminologies using an analogy. We’ll use the world of RDBMS for our analogy:

Terminology in MDS Analogy w/ RDBMS
 Models  SQL server Schema which is used to group logical entities together.
 Entities  Table
Attributes Columns

And here’s a picture that captures the thought: Models contains entities; entities contains Attributes:

master data services models entities attributes

And Here’s the official reference: http://msdn.microsoft.com/en-us/library/ee633763.aspx

Conclusion:

Thinking about the master data services terminologies by drawing an analogy helps me remember them – I hope it helps someone out there too.

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Data Mining Demo for Marketing vertical: How to create a Targeted mailing list?

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Tools I’ll be using for the Demo:

Excel 2010

SQL Server 2012 (specifically SQL Server Analysis Services)

Excel Add-in for Excel.

Sample data-set that comes with the excel add-in

Scenario:

Marketing Department needs to create Targeted Mailing list.

What data do we need?

To create a Targeted mailing list – we’ll need a historical data-set of customer purchase history

What will we do with the data?

Based on the historical data-set, we’ll be able to find “patterns” in the past consumer behavior. E.g. A single male going to college living in Europe is likely to buy a bike. And the using these patterns – we would then classify NEW customers.

Technically, we’ll be using the classification method using the Microsoft’s decision Tree algorithm

(Read the difference between classification and clustering)

Let’s get in action!

STEP 1: Build a Model

Data Mining Tab > click on classify:

data mining in excel example customer classification for maketing maling list 0

Follow the steps:

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Select the data:

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In this case, since we want to predict the likelihood of buying a bike – our column to analyze is BikeBuyer

 

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For the Demo, I am going to just leave it default. There are “optimization” steps that you can do but for the demo I am going to keep it super simple

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Name the model:

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The Model has been created!

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STEP 2: Query the MODEL to predict the likelihood of bike purchase of a new customer

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Select the model:

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Select the data:

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Specify the columns that would be used in predicting the likelihood:

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Add the column that will have the “predicted value”

 

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And example of Data Mining Expressions (DMX):

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For the demo, I am just going to add the column to the existing table:

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Yay! Here’s our Targeted Mailing list – see the last column:

Screenshot 1

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Screenshot 2:

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Now what?

Marketers can now send “coupons” to ONLY those people who are most likely to buy a bike! And so that’s how you create a targeted mailing list using the Excel Data Mining add-in.

Crunch more than 1 million rows in Excel 2010 with free addin called Power Pivot!

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Lately, I have been talking to few business folks who do their own data analysis in excel (2010) and sometimes they run into the excel 2010 limit of 1 million rows. And so when I hear that, I talk about Power Pivot and I talk about what It can do and what it cannot and they are just amazed that there’s a FREE add-in that will help them crunch more than 1 million rows!

happy suprised business user excel power pivot

Image courtesy

You can explore more about this amazing add-in here: http://www.microsoft.com/en-us/bi/powerpivot.aspx

And Read more about pros/benefits of PowerPivot:

Top 5 Ways PowerPivot Helps Excel Pros

PowerPivot? But I use pivot tables in Excel

Things I shared on Social Media Networks during Oct 11 – Oct 18

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The Goal of this series is to recap the conversations that I’m having on social networks and I do not want my Blog readers to miss that. So Here is this week’s post:

1)

WOW! Global Internet Traffic (in Peta Bytes Per Month):
27483 PB/Month!
via http://www.evolutionoftheweb.com/

 growth of the internet big data

(Thanks Hardki pandya for sharing. Here’s his tweet: https://twitter.com/HPsay/status/258207371162181632 )

Also for the a related link:

https://www.facebook.com/suvendu.shekhar.giri said “This is really awesome and very informational ”

evolution of the web and surge in Data

2)

Patent wars: http://flowingdata.com/2012/10/08/patent-war/

patent wars google apple motorola htc samsung

3)

Quote: One reason Wikipedia is still a popular source for information is because most people don’t know they can edit it themselves.

Via https://www.facebook.com/thedolt and Gaurang Patel (https://www.facebook.com/Gaurang.patel7 ) commented that: “Yes, Absolutely true,most people don;t know they can edit post them selves,and i think they don’t have other alternative to get quick information.”

4)

https://www.facebook.com/janakiramm quote:

“Without Stackoverflow, 50% of the developers cannot continue to be developers and without Google, 80% of the developers cannot even claim to be developers!”

5)

Status update: “I just worked on a SQL Server 2012 Master Data Services Tutorial where I learned how to 1) create a new Model 2) Use MDS Excel Add – In to load entities to the model 3) use Master data manager web app 4) add a new member via MDM web app 5) And create a subscription view to retrieve entity members. if you want to do learn that: search for “SQL Server 2012 Developer Training kit“. Awesome resource!”

MDS SQL Server 2012 master data services tutorial

6)

Shared a Resource: Introducing SQL Server 2012 Master Data Services Improvements http://channel9.msdn.com/posts/SQL11UPD05-REC-03

7)

SolidQ mentioned me a post about the Sep 2011 SolidQ Journal edition: https://plus.google.com/u/0/105279914944150120482/posts/cKh6hurWndj

8)

SolidQ India (https://twitter.com/SolidQIndia) Re-Tweeted my post about “Blog: Why am I not seeing “Month Names” in correct logical order?” http://parasdoshi.com/2012/07/22/powerpivot-model-why-am-i-not-seeing-month-names-in-correct-logical-order/

9) Milena Petrovic said “Lovely Graph” for this graphic: https://plus.google.com/u/0/105010538932095629627/posts/2uvE5B2HSk5

From the webinar "How to Walk The Path from BI to Data Science: An interview with Michael Driscoll, data scientist and CEO of Metamarkets" - A global surge in Data // A nice slide about Big Data

Image Courtesy: From the webinar “How to Walk The Path from BI to Data Science: An interview with Michael Driscoll, data scientist and CEO of Metamarkets” – A global surge in Data

That’s about it. You can read last week’s post here: Things I shared on Social Media Networks during Oct 3 – Oct 10

Let’s connect and converse on any of these people networks!

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