Pros and cons of using a vendor provided analytical data model in your BI implementation

The following question comes from many of our clients: what are some of the advantages and risks of implementing a vendor provided analytical logical data model at the start of any Business Intelligence, Data Warehousing or other Information Management initiatives? Some quick thoughts on pros and cons:

Pros:

  • Leverage vendor knowledge from prior experience and other customers
  • May fill in the gaps in enterprise domain knowledge
  • Best if your IT dept does not have experienced data modelers 
  • May sometimes serve as a project, initiative, solution accelerator
  • May sometimes break through a stalemate between stakeholders failing to agree on metrics, definitions

Cons

 

  • May sometimes require more customization effort, than building a model from scratch
  • May create difference of opinion arguments and potential road blocks from your own experienced data modelers
  • May reduce competitive advantage of business intelligence and analytics (since competitors may be using the same model)
  • Goes against “agile” BI principles that call for small, quick, tangible deliverables
  • Goes against top down performance management design and modeling best practices, where one does not start with a logical data model but rather
    • Defines departmental, line of business strategies  
    • Links goals and objectives needed to fulfill these strategies  
    • Defines metrics needed to measure the progress against goals and objectives  
    • Defines strategic, tactical and operational decisions that need to be made based on metrics
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BI In The Cloud? Yes, And On The Ground, Too

Slowly but surely, with lots of criticism and skepticism, the business intelligence (BI) software-as-a-service (SaaS) market is gaining ground. It's a road full of peril — at least two BI SaaS startups have failed this year — but what software market segment has not seen its share of failures? Although I do not see a stampede to replace traditional BI applications with SaaS alternatives in the near future, BI SaaS does have a few legitimate use cases even today, such as complementary BI, in coexistence with traditional BI, BI workspaces, and BI for small and some midsize businesses. 

In our latest BI SaaS research report we recommend the following structured approach to see if BI SaaS is right for you and if you are ready for BI SaaS:

  1. Map your BI requirements and IT culture to one of five BI SaaS use cases
  2. Evaluate and consider scenarios where BI SaaS may be a right or wrong fit for you
  3. Select the BI SaaS vendor that fits your business, technical, and operational requirements, including your tolerance for risk

First we identified 5 following BI SaaS use cases.

  1. Coexistence case: on-premises BI complemented with SaaS BI in enterprises
  2. SaaS-centric case in enterprises: main BI application in enterprises committed to SaaS
  3. SaaS-centric case in midmarket: main BI application in midsized businesses
  4. Elasticity case: BI for companies with strong variations in activity from season to season
  5. Power user flexibility case: BI workspaces are often considered necessary by power analysts
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Bottom Up And Top Down Approaches To Estimating Costs For A Single BI Report

How much does it cost to produce a single BI report? Just like typical answers to most other typical questions, the only real answer is “it depends”. But let’s build a few scenarios:

Scenario 1: Services only. Bottom up, ABC approach.

Assumptions.

 

  • Medium complexity report. Two data sources. 4 way join. 3 facts by 5 dimensions. Prompting, filtering, sorting ranking on most of the columns. Some conditional formatting. No data model changes.
  • Specifications and design – 2 person days. Development and testing - 1 person day. UAT – 1 person day.
  • Loaded salary for an FTE $120,000/yr or about ~$460/day.
  • Outside contractor $800/day.

Cost of 1 BI report: $1,840 if done by 2 FTEs or $2,520if done by 1 FTE (end user) and 1 outside contractor (developer). Sounds inexpensive? Wait.

 

Scenario 2. Top down. BI software and services:

Assumptions:

  • Average BI software deal per department (as per the latest BI Wave numbers) - $150,000
  • 50% of the software cost is attributable to canned reports, the rest is allocated to ad-hoc queries, and other forms of ad-hoc analysis and exploration.
  • Average cost of effort and services - $5 per every $1 spent on software (anecdotal evidence)
  • Average number of reports per small department - 100 (anecdotal evidence)
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