Business Intelligence (BI): tools and systems that provide business the capability to store, analyze and understand business data to make good business decision, generate report/dash boards/metrics for better understanding of company data which helps to improve efficiency and drive revenues.
Typical application of business intelligence:
a) Metrics of gross revenue, profits, sales, etc related to financial and sales analytics
b) Customer behavior profiling
c) Order management and supply chain
d) Geo-Spatial analytics
e) Regulatory complaince
f) Human Resource management
The source of data for Business Intelligence:
Operational data
Web services
Data marts/ODS and enterprise data warehouses
Social media websites (Facebook/Twitter)
B2B includes feeds from other business
MDM data- Master data management data
Geo-Spatial information
Pervasive computing devices such as sensors, cell phones, etc.
Business Intelligence tools:
a) Reporting/Dashboard tools such as Business objects and microstrategy
b) Data mining tools such as Weka
c) Statistical analysis tools such as SAS/R
d) Big data tools such as Hive/Impala etc for analysis of huge volume of data
There are obviously other complex tools that can be used for business intelligence. The tools above is what is normally found in industries.
Recent trends:
a) Moving business analytics to cloud such as Amazon redshift.
b) Using Big data for handling huge volume of data and offloading work from traditional data warehouse appliances.
c) Mobile BI applications
d) Social media analysis
Success Factors:
a) Management involvement and sponsorship
b) Focus on solving business problems
c) Stable and efficient BI environment
Required skill set for building business intelligence systems:
a) Report/dashboard developers.
d) Data modellers and data architects.
c) ETL designers/developers and understanding of data warehousing concepts.
d) Statisticians/Data scientists or Data Analysts.
e) Testers and Business analysts with background in data warehousing and business intelligence
See also: http://dwbitechguru.blogspot.ca/2014/07/a-standard-etl-architecture.html
Typical application of business intelligence:
a) Metrics of gross revenue, profits, sales, etc related to financial and sales analytics
b) Customer behavior profiling
c) Order management and supply chain
d) Geo-Spatial analytics
e) Regulatory complaince
f) Human Resource management
The source of data for Business Intelligence:
Operational data
Web services
Data marts/ODS and enterprise data warehouses
Social media websites (Facebook/Twitter)
B2B includes feeds from other business
MDM data- Master data management data
Geo-Spatial information
Pervasive computing devices such as sensors, cell phones, etc.
Business Intelligence tools:
a) Reporting/Dashboard tools such as Business objects and microstrategy
b) Data mining tools such as Weka
c) Statistical analysis tools such as SAS/R
d) Big data tools such as Hive/Impala etc for analysis of huge volume of data
There are obviously other complex tools that can be used for business intelligence. The tools above is what is normally found in industries.
Recent trends:
a) Moving business analytics to cloud such as Amazon redshift.
b) Using Big data for handling huge volume of data and offloading work from traditional data warehouse appliances.
c) Mobile BI applications
d) Social media analysis
Success Factors:
a) Management involvement and sponsorship
b) Focus on solving business problems
c) Stable and efficient BI environment
Required skill set for building business intelligence systems:
a) Report/dashboard developers.
d) Data modellers and data architects.
c) ETL designers/developers and understanding of data warehousing concepts.
d) Statisticians/Data scientists or Data Analysts.
e) Testers and Business analysts with background in data warehousing and business intelligence
See also: http://dwbitechguru.blogspot.ca/2014/07/a-standard-etl-architecture.html
No comments:
Post a Comment