BI and Analytics With or Without a Data Warehouse

What is business intelligence?

A set of theories, methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information for business purposes.
Source: Wikipedia

What is a data warehouse?

  • Clean and accurate data recognized as the only real business ‘truth’
  • A central repository of data which is created by integrating data from one or more disparate sources
  • Stores current as well as historical data

Source: Wikipedia

Traditional architectures

Approaches to the challenge

  1. Project specific analytics:
    • The development of a specific dashboard
    • An isolated initiative, with no forward-looking design approach
  1. Solution-oriented analytics:
    • The development of a specific dashboard/report, with future ones (known or
      unknown) in mind

Traditional BI – Existing data landscapes

With an existing data warehouseWithout an existing data warehouse
The data is in raw and detailed formThe data is in raw and detailed form
The data is clean (was already processed)The data may be dirty (entry errors, etc)
Usually directly accessible by IT onlyData is accessible to owner of data source
The data is centralized (single truth)The data is disparate (non-centralized)

Traditional architectures – Comparison

Centralized/DWNon Centralized/No DW
Data quality & accuracyHigherLower
Single version of the truthYesNo
Initial investmentHigherLower
Level of detailSummarizedGranular
OwnerITIT or business (optional)
Implementation timeLongerShorter
Technical complexityHigherLower

Traditional BI –Existing data landscapes

Traditional BI/AnalyticsTraditional DiscoverySisense
DW, OLAPIn-memoryElastiCube
TB scaleGB scaleTB scale

With data warehouse

Sisense vs. Traditional (DW)

Centralized/DWSisense Architecture
Data quality & accuracyHighHigh
Single version of the truthYesYes
Initial investmentHigherLower
Level of detailSummarizedGranular
OwnerITIT or Business (optional)
Implementation timeLongerShorter
Technical complexityHigherLower

Without data warehouse

Sisense vs. Traditional (No DW)

Non Centralized/No DWSisense Architecture
Data quality & accuracyLowerHigh
Single version of the truthNoYes
Initial investmentLowerLower
Level of detailGranularGranular
OwnerIT or Business (optional)IT or Business (optional)
Implementation timeShorterShorter
Technical complexityLowerLower
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