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Overview of Business Intelligence
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Business Intelligence and ReportingBy Parthiv Dixit
What is Business Intelligence?
• Corporate Performance Management (CPM)
• Data warehousing• Data mining• Predictive Analytics• Dashboards• Big Data• Reporting• Online Analytics
Processing (OLAP)• Visualisation
Business intelligence (BI) is a set of theories, methodologies, architectures, and technologies that transform raw data into meaningful and useful information for business purposes.◦ Wikipedia
Business intelligence (BI) is an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.
◦ Gartner (IT Glossary)
Relevance of BIGain business insights using dataMake better fact based decisionsAnticipate future demandTypical Applications
◦Analyse what happened and why Sales figures by region, product line,
distribution channel
◦What if Analysis Change series of parameters to see the
outcome
BI Process1
Identify business
issue2
Formulate business question
3What
information do I need
4Where do I find the
information
5Retrieve
information
6Analyse
Information
7Report
answers
8Take
actions
OLTP vs OLAP
CharacteristicsOLTP System
Online Transaction Processing (Operational System)
OLAP System Online Analytical Processing
(Data Warehouse)
Source of dataOperational data; OLTPs are the original
source of the data.Consolidation data; OLAP data comes from the
various OLTP Databases
Purpose of data To control and run fundamental business tasksTo help with planning, problem solving, and
decision support
What the dataReveals a snapshot of ongoing business
processesMulti-dimensional views of various kinds of
business activities
Inserts and UpdatesShort and fast inserts and updates initiated by
end usersPeriodic long-running batch jobs refresh the
data
QueriesRelatively standardized and simple queries
Returning relatively few recordsOften complex queries involving aggregations
Processing Speed Typically very fast
Depends on the amount of data involved; batch data refreshes and complex queries may take many hours; query speed can be improved by
creating indexes
Space RequirementsCan be relatively small if historical data is
archived
Larger due to the existence of aggregation structures and history data; requires more
indexes than OLTP
Database Design Highly normalized with many tablesTypically de-normalized with fewer tables; use
of star and/or snowflake schemas
Backup and RecoveryBackup religiously; operational data is critical to run the business, data loss is likely to entail
significant monetary loss and legal liability
Instead of regular backups, some environments may consider simply reloading the OLTP data as
a recovery method
source: www.rainmakerworks.com
Business Intelligence Landscape
Challenges in BIIdentify business
requirementsAgile BIData
rationalisationStructured vs
Unstructured data◦ ERP vs Email,
facebook, twitter)Data volumes
◦ Big data
How companies are using data
Customer Relationship Management
Adsense – stalker AdsGoogle Search- personalised search
based on 57 parameters ◦ Eli Pariser, “Filter bubbles”, TED2011
Meta data applications◦Red Ride
How is Big Data being used?Gold Coast Health using admission
records to predict ER admissions with 93% accuracy
WikiLeaks – go through 200,000 classified documents leaked by Snowden
Predicting the US election outcome in all 50 states – Nate Silver
IPL – KKR leveraged SAP Analytics tools to buy players, derive post game analytics and drive fan engagement
Emerging Trends IoT (Internet of Things)
◦ Explosion of data through device to device communication
◦ Analysis of data to drive intelligent systems Smart homes and cars
◦ Augmented Reality Google Glass
In memory databases – enable real time analytics◦ Reporting at the speed of thought◦ SAP HANA vs Oracle 12c In Memory
NoSQL (Not Only SQL)◦ Highly scalable data stores for big data applications◦ Ad hoc query and self service tools yet to reach
maturity
Reporting“If a report does not drive an
action it has no use”- Paul Hawking
Static ReportsInteractive Reports
◦Drill down, Adhoc Reports, Self Service
Dashboards ◦Graphic visualisations◦SAP Lumira, Internet-map.net
Key Innovations used by successful BI companies
Gartner 2013
Final thoughtsOld concepts in new wordsNew technologies open new
opportunitiesTake a course on Data science
◦ https://www.coursera.org/course/datasci