Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: A Question of Scope
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Best Practices > A Question of Scope
Best PracticesData MiningDecision ManagementInside CompaniesModeling

A Question of Scope

zamaes
zamaes
5 Min Read
SHARE

Don’t bite off more than you can chew because nobody looks attractive spitting it back out.

– Carroll Bryant

Don’t bite off more than you can chew because nobody looks attractive spitting it back out.

– Carroll Bryant

I apologize for the image – but the sentiment is apt. My mother would have said that “my eyes were bigger than my stomach” and admonished me for letting good food go to waste. The problem is that when the size of the project is beyond the budget constraints of the business, or the capacity of the development team, work goes unfinished. And so it’s essential that the scope of the effort be understood before any commitment is made to complete it.

The scope of a data management initiative is influenced by 3 factors:

  1. Reference Architecture
  2. Source Data Requirements
  3. Target Dimensional Breakdown

Reference Architecture

The reference architecture determines the number of areas that need to be modeled and the number of times the data will be migrated from one sector to another. Each sector also has its own degree of complexity – some considerably less than others.

  • What is the reference architecture of the target solution?
  • How many sectors of the reference architecture are targeted for this initiative?
  • Are we building on an existing structure or is this the initial project?
  • Do you have existing architecture, naming and content standards?
EDW Reference Architecture

EDW Reference Architecture

Source Data Requirements

The source data requirements are the list of fields that are to be brought into the target system. It is important to understand that a cost attaches to each one of these fields; and that if one field is being drawn from a source table, it will not be the same level of effort to bring in additional fields from the same table. Therefore, the scoping needs to be based on the number of individual pieces of information, rather than source tables.

  • How many distinct fields are required? (e.g., Customer First Name, Date of Birth, Industry Classification Code)
  • How many different source systems are involved?
  • How many different source tables are involved?
  • How many fields are being drawn from multiple sources? (e.g., Customer First Name coming from Marketing database and Point of Sale system)

Target Dimensional Breakdown

The target dimensional breakdown determines the breadth of subject areas being modeled, and the potential complexity of the processes involved.

The measures are numeric “counts and amounts” that either come directly from source systems, and so are relatively straightforward, or need to be calculated or derived from component values.

Obviously, these are more complex, and will involve the storage of both components and resulting calculations.

The dimensions give the measures context (e.g, sales by product, balances by branch). The number of different dimensions that need to be modeled and potentially mastered can have a significant impact on development time, particularly when they involve hierarchies.

  • What are the measures?
  • How many require calculations/derivations vs. coming directly from the sources?
  • What dimensions are being requested (customer, employee, store, branch etc.)?
  • What hierarchies are being requested?

Once you’ve established the scope of the project, you can estimate the time it will take to develop it. These are important inputs into understanding the order of magnitude of the task at hand; and an essential set of questions to be answered when communicating with the internal development team or a potential vendor.

We all know that scope can creep once the project gets going, and that becomes a management issue; but it’s important to start with a baseline understanding of the size of the task at hand. It helps set appropriate expectations for everyone involved. And it’s good for the digestion.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

image fx (2)
Monitoring Data Without Turning into Big Brother
Big Data Exclusive
image fx (71)
The Power of AI for Personalization in Email
Artificial Intelligence Exclusive Marketing
image fx (67)
Improving LinkedIn Ad Strategies with Data Analytics
Analytics Big Data Exclusive Software
big data and remote work
Data Helps Speech-Language Pathologists Deliver Better Results
Analytics Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Driving Adoption of Social Collaboration Tools

6 Min Read
big data and virtual agents
Big Data

Why Your Business Should Use a Data Catalog to Organize Its Data

8 Min Read

What You Need to Know About Duqu

6 Min Read

The ‘Big Data’ Buzz – Revolution or Evolution?

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?