1. Business intelligence
Business intelligence refers to competencies, technologies, process ,application and practices used to
support evidence based decision making process of organization .It is collection of approaches for gathering
,storing ,analyzing and providing access to data that helps to gain better insight and take decision on fact
based evidence.
What is BI used for?
Organizations’ use Business Intelligence to gain data-driven insights on anything related to business
performance. It is used to understand and improve performance and to cut costs and identify new business
opportunities, this can include, among many other things:
Analyzing customer behaviors, buying patterns and sales trends.
Measuring, tracking and predicting sales and financial performance
Budgeting and financial planning and forecasting
Tracking the performance of marketing campaigns
Optimizing processes and operational performance
Improving delivery and supply chain effectiveness
Web and e-commerce analytics
Customer relationship management
Risk analysis
Strategic value driver analysis
Basics of busines intelligence :
1. Gathering data
2. Gathering data is concerned with collecting or accessing data which can be used for decision
making process .It is used for collection of performance measurement. Example like transactional
systems that keep logs of past transactions, point-of-sale systems, web site software, production
systems that measure and track quality, etc.
2. Storing data
Storing data is concerned with making sure that data is filed and stored in proper way so that it can
be easily found and used for analysis purpose .Data warehouse is used to store the data under
different category .
3. Analyzing data
Analyzing data is important step to gain better insight that will support organization decision making
process .It is done with help of statistical tools, data mining approaches or visual analytics.
4. Providing access
In order to support decision making the decision makers need to have access to the data. Access is
needed to perform analysis or to view the results of the analysis. The former is provided by the
latest software tools that allow end-users to perform data analysis while the latter is provided
through reporting, dashboard and scorecard applications.
What Is Data Mining?
Data mining is the practice of automatically searching large stores of data to discover patterns and
trends that go beyond simple analysis. Data mining uses sophisticated mathematical algorithms to
segment the data and evaluate the probability of future events. Data mining is also known as
Knowledge Discovery in Data (KDD).
The key properties of data mining are:
Automatic discovery of patterns
Prediction of likely outcomes
Creation of actionable information
Focus on large data sets and databases
Business Intelligence is more than Software Tools and Technology
The term Business Intelligence is often used in a very narrow way to refer to software applications
used to analyze an organization’s raw data. Terms often associated with BI in an IT sense are data
mining, online analytical processing, querying and reporting.
Business analytics
Business analytics (BA) is the practice of iterative, methodical exploration of an organization’s data
with emphasis on statistical analysis. Business analytics is used by companies committed to data-driven
decision making.
3. BA is used to gain insights that inform business decisions and can be used to automate and
optimize business processes. Data-driven companies treat their data as a corporate asset and leverage it for
competitive advantage. Successful business analytics depends on data quality, skilled analysts who
understand the technologies and the business and an organizational commitment to data-driven decision
making.
Examples of BA uses include:
•
Exploring data to find new patterns and relationships (data mining)
•
Explaining why a certain result occurred (statistical analysis, quantitative analysis)
•
Experimenting to test previous decisions (A/B testing, multivariate testing)
•
Forecasting future results (predictive modeling, predictive analytics)
Once the business goal of the analysis is determined, an analysis methodology is selected and data
is acquired to support the analysis. Data acquisition often involves extraction from one or more business
systems, cleansing, and integration into a single repository such as a data warehouse or data mart. The
analysis is typically performed against a smaller sample set of data. Analytic tools range from spreadsheets
with statistical functions to complex data mining and predictive modeling applications. As patterns and
relationships in the data are uncovered, new questions are asked and the analytic process iterates until the
business goal is met. Deployment of predictive models involves scoring data records (typically in a
database) and using the scores to optimize real-time decisions within applications and business processes.
BA also supports tactical decision making in response to unforeseen events, and in many cases the decision
making is automated to support real-time responses.
While the terms business intelligence and business analytics are often used interchangeably, there
are some key differences:
BI vs. BA
Business Analytics
What happened?
Answers the questions:
Business Intelligence
Why did it happen?
When?
Will it happen again?
Who?
What will happen if we changex?
How many?
What else does the data tell us that
never thought to ask?
Reporting (KPIs, metrics)
Statistical/Quantitative Analysis
Automated Monitoring/Alerting
4. Includes:
(thresholds)
Data Mining
Dashboards
Predictive Modeling
Scorecards
Multivariate Testing
OLAP (Cubes, Slice & Dice, Drilling)
Ad hoc query
Business intelligence provides a way trough data gathering through asking question, online analytical process
and reporting, while business analytics uses more quantitative and statistical data for decision making and
predictive modeling.
Business intelligence team task:
1. Working with business staff to understand the kind of information they need to know / decisions
they need to make;
2. Identifying data that would be needed to produce this information and from which systems the data
would come from;
3. Understand the data and how it would be fed into the data warehouse (what does the data mean?
what are the data quality issues? etc.);
4. Setup ETL processes to get this data into the data warehouse;
5. Develop reports that join / filter / aggregate / the data and show results in a nice clear report format
or dashboard.
6. Maintain these feeds and ensure end users are clear on what reports are showing.
Competitive intelligence:
Competitive intelligence is process of ethically and legally gathering, analyzing information about
competitor’s strength and weakness to enhance business decision making.
It grouped into two categories –
1. Tactical –
Short term and seeks to provide input into issues such as capturing market share and increase revenue of
company.
5. 2. StrategicStrategic competitive intelligence focuses on long term issues such as risk and opportunities facing the
enterprise.
Information analyzed to the point where strategic decision can be made. It is tool to alert management to
early treats and opportunities in the market. It requires for reasonable assessment of data and gives best
views and approximation of market and the competition. Competitive intelligence is understanding and
learning of what is happening outside your business in the world so that you can be competitive in the
market.
For example to sales representative .intelligence means tactical advice on how to best bid for lucrative
contract. To top management, it represents insight to gain market share against competitors.