What is BI? BI stands for Business Intelligence (BI).

Every enterprise requires understanding of how the company is performing, what area of the business requires focus to improve. To determine these, we need data, just data will not help, it requires analysis, calculations, in one word called metrics, to understand projected information. Source of the date is being Raw data, this raw data needs to be molded to metrics and that can be possible with Business Intelligence (BI). Business Intelligence (BI) is technology driven process for Analyzing data for executives to make decisions. Business Intelligence (BI) process provide historical, current and predicted data. Business Intelligence (BI) is also termed as Decision Support Systems (DSS). Business Intelligence (BI) is getting more popular in medium to large size enterprise companies.

BI tools can be fulfilled with common items.

  1.  ETL tools (Extraction Transformation and Loading). This helps in extracting the source to destination.
  2.  Reporting tools. These tools provide calculations, values and graphs in human understanding.

Business Intelligence (BI) is the process of getting application data which normally in normalized database to Business Intelligence (BI) database which is denormalized. Primary motive of Business Intelligence (BI) is to focus on speedy retrieval of the data rather and focusing on data redundancy.

Without proper data there is no way Business Intelligence (BI) will work. To make it work data needs to be tuned filtered. This can be done in multiple stages.

  • Source Data:
    • Data Standardization: make data comparable (same unit, same pattern…)
    • Master Data Management: unique referential
  • Operational Data Store (ODS):
    • Data Cleansing: detect & correct inaccurate data
    • Data Profiling: check inappropriate value, null/empty
  • Data warehouse:
    • Completeness: check that all expected data are loaded
    • Referential integrity: unique and existing referential over all sources
    • Consistency between sources: check consolidated data vs sources
  • Reporting:
    • Uniqueness of indicators: only one share dictionary of indicators
    • Formula accuracy: local reporting formula should be avoided or checked

When its coming to the Business Intelligence (BI) data, where more focus is on fast retrieval of the data rather than focusing on data redundancy, what we call as Relational database vs Dimensional database. Types of Dimensional database used in Business Intelligence (BI) are Star Schema, Snowflake Schema were designed.

More understanding of these schema’s.

  1. Star Schema

Star schema separates business process data into facts and dimensions. Facts being all metrics and calculations, Dimensions being anything like

  • Time dimension
  • Geographical dimension
  • Customer dimension
  • Calendar dimension

Fact table contains primary keys of the dimension table as foreign keys. Dimensions will able to store history when any key information is changed. This process is called changing dimensions, where data represents with start date and end date.

Overall Business Intelligence (BI) is turning into a most important department in enterprise, helping improving the business.