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What is Business Intelligence?
Set of theories, methodologies, architectures, and technologies that transform raw
data into meaningful and useful information for business purposes.
Over the past few decades, companies that have deployed Enterprise Resource Planning
(ERP), Customer Relationship Management (CRM) and other applications are now sitting on a mountain
of data that can be analyzed. In addition, the growth of the Web has increased the demand for BI that can
analyze large data sets.
Business Intelligence Tools
BI Tools provides,
True insights in order to improve decision making & social collaboration
Better company results
Efficient Reports, Statistics and Analysis of Big Data
Dashboards displaying key indicators
Brings your company data to life
(you can understand the success factor more quickly / indicates where things go wrong and you can make
adjustments / platform for employees and managers to improve business process on daily basis)
Data Management Tools
Better decision-making starts with better data. Data management tools help
clean-up “dirty data”, organize information by providing format and structure,
and prepare databases for analyses.
Helps organizations maintain clean, standardized
and error-free data. Standardization is especially
important for BI implementations that integrate
data from diverse sources. Data quality
management ensures that later analyses are
correct and can lead to improvements within the
Extract, Transform, and Load (ETL)
Collects data from outside sources, transforms it
and then loads the compiled data into the target
system (a database or data warehouse). Because
primary data is often organized using different
schemas or formats, analysts can use ETL tools to
normalize data for useful analysis.
Data Discovery Applications
The ability to sift(filter) through data and come to meaningful conclusions is one
of the most powerful benefits of adopting business intelligence tools.
Data discovery applications help users make sense of their data, whether it be
through quick, multivariate analysis during OLAP or via advanced algorithms
and statistical computations during data mining.
Sorts through large amounts of data to identify new or unknown
It is often the first step that other processes rely on, such as
Databases are often too large or convoluted to find patterns with
the naked eye or through simple queries.
Data mining helps point users in the right direction for further
analysis by providing an automated method of discovering
Data Discovery Applications
Online Analytical Processing (OLAP)
Enables users to quickly analyze multidimensional data from different
It is typically made up of three analytical operations:
Data sorting and classification (drill-down)
Analysis of data from a particular perspective (slice-and-dice).
For example, a user could analyze sales numbers for various products by store
and by month. OLAP allows users to produce this analysis.
Analyzes current and historical data to make predictions about future risks and
An example of this is credit scoring, which relies on an individual’s current
financial standing to make predictions about their future credit behavior.
Semantic and Text Analytics
Extracts and interprets large volumes of text to identify patterns, relationships
For example, the popularity of social media has made text analytics valuable to
companies with a large social footprint. Understanding semantic trends is a
powerful tool for organizations evaluating purchase intent or customer satisfaction
among users of these channels.
In the words of John W. Tuckey, “The greatest value of a picture is when it forces
us to notice what we never expected to see.”
Reporting applications are an important way to present data and easily convey the
results of analysis.
BI users are increasingly business users--not IT staff--who need quick, easy-to-
understand displays of information.
Helps users create advanced graphical representations of data via simple user
The ability to visualize information in a graphical format (as opposed to words or
numbers) can help users understand data in a more insightful way.
In addition, new interactive tools can provide teams the ability to both analyze and
manipulate reports in real time.
Dashboards typically highlight key performance indicators (KPIs), which help managers
focus on the metrics that are most important to them.
Dashboards are often browser-based, making them easily accessible by anyone with
Allows users to design and generate custom reports.
Many CRM and ERP systems include built-in report writing tools, but users can also
purchase stand-alone applications, such as Crystal Reports, to create ad hoc reports
based on complex queries.
This is especially helpful for organizations that continually modify analyses and need to
generate new reports, quickly.
Scorecards attach a numerical weight to performance and map progress toward goals.
Think of it as dashboards taken one step further.
In organizations with a strategic performance management methodology (e.g., balanced
scorecard, Six Sigma, etc.), scorecards are an effective way to keep tabs on key
For example, a scorecard might establish a grade of “A+" to 40% year-over-year growth
if the goal was set at 14%.
BI tool types in Market
Enterprise BI platforms
Databases or packaged BI tools
Visual Data Discovery tools
Pure reporting tools
Pure dashboard tools
Pure OLAP tools
Innovative or niche tools
IBM Cognos Series 10
Microsoft BI tools*
Oracle Enterprise BI Server (OBIEE)
Oracle Hyperion System
SAP NetWeaver BI
SAS Enterprise BI Server
Board Management IntelligenceToolkit
BI tools in Market