bussiness intelligence and tools

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ASSIGNMENT

DRIVE FALL 2013

PROGRAM MBA IT

SUBJECT CODE &

NAMEMI0036- BUSINESS INTELLIGENCE & TOOLS

SEMESTER 3

BK ID B1219

CREDITS 4

MARKS 60

Q.1 How do you classify the different types of business Intelligence

Ans : Business intelligence is a set of theories, methodologies, processes, architectures, and technologies

that transform raw data into meaningful and useful information for business purposes. BI can handle largeamounts of information to help identify and develop new opportunities.

Some of the benefits of having a Business Intelligence system include the ability to access data in acommon format from multiple sources and a way to measure goals and analyze cross-departmental data.Some of the types are:

Business process Modeling: It is an activity to represent the processes of an organisation to helpin the analysis and improvement of the current process.

Data flow Modeling: It is the process by which we can identify, model and document themovement of data around an information system. It checks processes (activities that transform

data from one form to another), data stores (the areas holding data), external entity (what sendsdata into a system or receives data from a system), and data flows (routes through which data canflow).

Data Modeling: In this method, the data requirements needed to support the business processesof an organisation is defined and analysed. It can be performed during various types of projects

and in multiple phases of the project.

Dimensional Modeling: According to Dr. Kimball1 Data modeling is a design technique fordatabases intended to support end-user queries in a data warehouse.

ETL & Data Warehouse: As discussed earlier, data warehouse is a database that stores businessrelated information. ETL is the tool used to extract, transform and load data into the data

warehouse.

BI Reporting: To create a successful BI report, a lot of attention must be given to both thebusiness end-users and IT professionals. Business users usually feel that looking at the BI reportis like looking at the data warehouse itself. So, if they do not like the report, there are chances that

they will not use the data warehouse also. Online Analytical Processing (OLAP): It is an approach to quickly answer the queries of users.

It encompasses relational reporting and data mining. OLAP finds its applications in businessreporting for sales, marketing, business process management, management reporting, and

financial reporting and so on.

Dashboard Software: It is one of the types of BI. As mentioned earlier, dashboard is aninteractive user interface. Dashboards contain Key Performance Indicator (KPI), metrics, trends,charts, data visualisation and so on.


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Key Performance Indicator (KPI) is often identified in a business to help them drive a businesstowards success and is associated with a number of business activities like Customer RelationshipManagement (CRM), Supply Chain Analytics or any other activities within the Organisation.

The OLAP (Online Analytical Processing) Option of the Oracle Database provides a dimensional modelin support of the query and analysis that are common to business intelligence and other types of analytic

applications. Oracle supports the dimensional model with both Relational and Multidimensional datatypes.

Q.2 a. Similarity measures determine the similarity between the two objects. What are the four

methods to determine the similarity characteristic between the two objects?

Ans :Similarity Measures

Similarity measures determine the similarity between the two objects. Similarity measure is an importanttool of business intelligence system which is useful in determining the similarities between the twofactors in a business application. This helps the user to adapt the suitable steps to improve the businessand bring in the necessary steps to achieve business intelligence concepts. When concerned with pure

verification and identification application in a business, it is very important to determine whether the newtemplate matches with the stored one.Similarity measures determine the match between the two essential components of a business applicationwhich helps in taking critical decisions.

It gives the similarity characteristic between the objects. In internet, all the web pages represent the wholedatabase. These pages are classified into two category i.e. pages that answer the given query and thosethat do not answer. The pages that answer the query are more similar like each other than those pageswhich do not answer the query. Query stated determinesthe similarity between the pages in this case. The similarity between the two objects t i and tj, sim(ti, tj), in

the database D is a mapping from D*D to the range [0, 1]. The objective is to define the similaritymapping such that documents that are more alike have higher

similarity value. The characteristic of good similarity measure is given below.ti D, sim(ti, tj) = 1

ti , tj D, sim(ti, tj) = 0 if ti and tj are not alike at all

ti , tj, tk D, sim(ti, tj) < sim(ti, tk) if ti is more like tk than it is like tj

There are four methodsto determine the similarity characteristic between the two objects namely:

Dice Jaccard Cosine Overlap


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b. Illustration of Decision Tree

In the general form of decision tree modelling

approach, a relationship is extracted to which one ormore decision rules can be derived that describes the

relationship between the input and target. Every ruleassigns a record or observation from the data set to a

node in a branch. The assigned record/observation isbased on the value of one of the fields or columns inthe data set. Fields or columns that are used to create

values are called inputs. Splitting rules applied ondata results in a hierarchy of branches within

branches that form an inverted decision tree. Rulescan be selected and used to display the decision tree.Selected rule provides a means to visually examine

and describe the tree-like network of relationshipsthat characterise the input and target values.Decision tree is a nested hierarchy of branches. Each

branch in the tree is referred as a node. A node with

all its descendent segments forms an additionalsegment or a branch of that node. The bottom nodes of the decision tree are referre d as terminal nodesor leaves. The decision rule provides each leaf with a unique path for data to enter the class that isdefined as the leaf.

Q. 3 Define data mining and describe the architectural framework of data mining.

Ans : Data Mining :

Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data

from different perspectives and summarizing it into useful information - information that can be used to

increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools foranalyzing data. It allows users to analyze data from many different dimensions or angles, categorize it,and summarize the relationships identified. Technically, data mining is the process of finding correlationsor patterns among dozens of fields in large relational databases.

In other words, Data mining is a process of extracting the hidden predictive information from large

database. It is a new powerful technology with great potential to attack problems such as obtainingefficient summaries of large amount of data. It can also identify the interesting structures and


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relationships within a data set. Data mining tools are capable of predicting the future trends and

behaviours which helps to take proactive and knowledge driven decisions in businesses.

Architecture of Data Mining

The technological purpose in KDD (Knowledge Discovery in Databases) process is to designarchitecture for Data Mining, it is also planned to tackle the process-related issues. It is hypothetical thatthe function of the Data Mining Technology is to process, memory and information intensive work whichrequires constant interaction with the database.It is believed that the Data Preparation (Data mining, Transformation, Cleansing and Loading) is

beyond the range of the Data Mining architecture. To protect the correctness of the data mining results,Data preparation includes:

Data mining: To make sure that the information is pulled out from the accurate and reliable'master' source. For example- In an organisation, the employees customer ID and address may be

available in three different systems, but it should be taken out from a source which is mostauthentic and complete. The main source for this purpose is Source Systems Mapping1.

Transformation: Once the Data is mined out, a variety and numerous amounts of cleaningactivities are performed to deliver it in Data-warehouse loaded/presentation server. Its anintricate and biggest challenge in data-warehouse.

Cleansing: The preliminary point of data cleansing is, when one knows one type and extent ofthe data quality issues For example, this is done, when there are dissimilar records for the same

customer. In one verification it has the right name and address, while the other has the righttelephone and Fax. We combine the two records to have all the basics filled-up.

Loading: Data loading starts after the information sets are ready in the Data production in thepresentation server. This is considered to be a simple process. The key concern in the Loading

process is to achieve the speed. This is achieved by using various methods. Example Certain ETLtools will allow you to extract, transform, and load in one process. That is, it is not necessary to

create intermediate files.

DM has three layers

:

Database layer with sub-layers of database & metadata. Application layer in data management & algorithms. Front-end layer for management, input structure settings and results display/visualisation

Architecture of Data Mining


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The first tier is the database tier where information and metadata 2 is made ready and it is stored. Thesecond tier is the Data Mining Application where the algorithms processes the information and collects

the results in the database. The third tier is the Front-End layer, which facilitates the structure settings forData Mining Application and visualisation of the results in comprehensible form.

Database tier: It is not essential that the Database tier is hosted on an RDBMS. It can becombination of RDBMS and file system or just a file system. Example. the data from base

systems may be stacked up on a files system and then loaded onto an RDBMS. The Database tierconsists of a variety of layers. The data in these layers interface with numerous systems based on

the actions in which it participates.

Various layers in the Database tier

Metadata tier: The Metadata layer is the most regularly used layer. It contains information aboutresources, transformations, cleaning rules and the Data Mining Results. It forms the backbone for thefacts in the entire Data Mining Architecture.

Data Layer: This layer consists of Staging Area, Prepared / Processed Data and Data Mining Results. TheStaging Area is used for provisionally holding the data taken from various source systems. It can be kept

in any form e.g. flat files, tables in RDBMS. This data is transformed, cleaned, combined and loaded intoa planned scheme during Data Preparation process. This equipped data is used as Input Data for DataMining. The base data may undergo summarisation or source based on the business case before its

presented to the Data Mining Application.

The Data Mining production can be captured in the Data Mining Results layer so that it can be made

available to the users for visualisation and analysis.

Q.4 Discuss the features of various types of business models with the help of examples.

Ans : There are different types of business models and are as follows:

Business to Consumer (B2C): Business to consumer (B2C) describes the activities ofbusinesses serving end consumers with products and/or services. This is the most common e-commerce segment. In this model, online businesses are sold to individual consumers. an

exponential growth. The basic idea behind this type of business is that the online retailers and


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marketers could sell their products to the online consumer by using crystal clear data which wasmade available through various online marketing tools. This is done using online catalogue and

shopping cart transaction systems. For example, the Business to Consumer is followed by onlinepharmacy to give free medical consultation and also to sell medicines to patients. The servicessuch as payments to information sites or online data backup are examples of B2C e-commerce.Amazon.com is an example of one of the first and is still one of the most successful B2C e-

commerce companies.

Business to Business (B2B): It is the biggest form of e-commerce business. B2B impliescommerce transactions between businesses like the one between a manufacturer and awholesaler or a wholesaler and a retailer. In this form, both the buyers and the sellers are both

business entities and do not need an individual consumer. It is like the manufacturer supplyinggoods to the retailer or to the wholesaler. For example, Dell sells computers and other related

accessories online but it does not manufacture all the products. So, in order to sell the products, itwill first have to purchase them from different businesses that are the manufacturers of those

products. Cisco is an example of one of the first B2B catalogues online. The other examples ofB2B e-commerce are the intranet services and web-meetings.

Consumer to Business (C2B): It is an electronic commerce business model in which consumersor individuals can offer products and services to companies and the companies have to pay them.

This business model is a complete reverse of traditional business model where companies offergoods and services to consumers. Elance is an example of C2B where the consumer put a projectand businesses answer it with bid proposals. Online loan brokers are also an example of C2B.

Consumer to Consumer (C2C): It is the fastest growing segment of e-commerce after theintroduction of social networking. It helps to ease the online transaction of goods or services

between consumers through some third party. A common example is the online auction where aconsumer posts an item for sale and other consumers propose to purchase it. Then, the third partyusually charges a flat fee or commission. The sites are only intermediaries which are just there to

match consumers. They do not have to check for the quality of the products being offered.

Examples of C2C are eBay, Craigslist and Amazon.com where the consumers can put classifiedads or offers to sell the property to other consumers.

Government-to-Business (G2B): It is an online non-commercial interaction between local andcentral government and the commercial business sector, rather than private individuals (G2C).For example http://www.dti.gov.uk is a government web site where businesses can get theinformation and also give advice on e-business. http://g2b.perm.ru is also another example.

Government-to-Citizen (G2C): It is the communication connection between a government andprivate individuals or residents. The G2C communication most often relates to the

communication that takes place through Information Communication Technologies (ICT) butcan also include direct mail and media campaigns. G2C may take place at the federal, state, and

local levels. G2C is in contrast to Government-to-Business (G2B).

Q.5 A non-profit organisation - a leader in promoting urban sustainability in India - has the

permission to supervise and propose resourceful energy and source utilisation by corporate entities

across India. The customer was using spreadsheets to confine various information with regards to

unit consumption, charges, research, and analytics of Energy Usage. The Intensity for both Heating

Degree Days & Cooling Degree Days, and it was suffering from the disadvantages of utilisation of

multiple non-standard spreadsheets. The crucial challenge of the organisation was to develop


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excellence of data; time needed to gather & authenticate information, distribute graphs & analysis

with cyclic time series, and carry out other ad hoc queries & difficult analysis.

Customer also wanted a BI solution that is easy to use, available from web, and needs negligible

human resources to execute these periodic tasks. Elegant BI Business Intelligence solution deployed

with customised ETL solution has offered web based, simple to use, and error-free analytic system

to client, in short time span and small budget. Research coordinators at client side, now have

complete picture of the energy usage patterns and trends in hours rather than days, and they spendmore time doing other ad hoc research and data mining, rather than collecting, consolidating, and

validating data from large number of spreadsheets received from member organisations every

month. This initiative is helping customer sustain its management position for a better cause of

supporting sustainable metropolitan communities in India.

a. What are the aspects of BI framework? Explain each of them in detail

b. What are the tools used in the above case study to meet the challenges of the organization and to

maintain food quality as well?

a. Ans : The BI Framework joins some significant aspects that motivate business operations and the ITstructures that encourage them. These aspects are people, procedures, methods, and performances.

1. People- Employees are the basic foundation on which the industry is developed. Without havinggood workers an organisation will not succeed. How employees achieve their tasks in thecompany is varying. The rapidity of business in recent times defines that employees can no more

be seated in ivory towers, or control and limit the course of information inside the organisation. If

information is vital then it has to be readily obtainable to the people who require it for theirprofession.

2. Procedure- As higher management defines business schedules and objectives they shouldcommunicate with them throughout the company hierarchy. Goals must be set and measured, andworkers must be explained what has been look forward from them. Employee compensation

should generally be tied to achieving expected targets. Planning, budgeting, and forecastingsystems form the basis of the planning process, but collaboration capabilities are required forcommunicating plans and goals, and business intelligence is essential for monitoring and

managing targets. Methodologies like balanced scorecards are also valuable for formalising theplanning process and managing targets.

3. Methods- Once business plans and initiatives are agreed on, they are implemented in businessprocesses. Business process management is a growing technology for modelling, simulating,deploying, integrating, and monitoring business processes. At present, process management is

used primarily with operational business transaction applications, but the need to managedocument and information workflows is bringing process management concepts and technologies

into the collaborative application environment.4. Performance- The performance of employees using BI tools is much more than the others.

(b) Ans : Tools used in the above case study to meet the challenges of the organization :

The most common tools used for meeting the challenges of the organization and as well as formaintaining the food quality are given below. They are listed in the following order: Increasing cost,

increasing functionality, increasing business intelligence complexity, and decreasing number of totalusers.

1. Excel :

1. It's relatively cheap.2. Easily available


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3. user friendly4. compatible to any OS5. Accurate

2. ETL :

It means Extraction Transform and Loading. First data is to be extracted from the raw data and the it is

analysed and transform into a usable form called information, which is to be loaded and used further.It is one of the basic software method used for BI.

Q.6 ABC is an online educational organization which offers number of programmes. Throughout

the world. It has its franchise all over the world. It has to maintain huge data about the entire all

the programmes that are currently running and also that are withdrawn but still running for old

students. How should it plan to implement the business intelligence solutions? What are the

limitations of Business Intelligence?

Ans The Business Intelligence solutions and the real time data charts are highly efficient in getting thecorrect kind of information at the ideal time. The implementation of the Business Intelligence can be

planned by analysing the requirements appropriate to the company can be chosen. Planning to implementthe Business Intelligence solutions is more than implementing technologies and tools related to thesolution. It has to be ensured that the system gives the necessary results and at the same time be able to

refresh the real time data marts.

Planning to implement a Business Intelligence in the company, may also have graphic visuals, so that the

overall view of the desired function can be obtained. Analytic dashboards have now become a necessityand can also supplement the statistical and the numeric information. The real time information obtained

through the Business Intelligence system should be delivered to almost any place. In the market, there areseveral gadgets which will route exception alerts and the dashboard reports to the web-enabled devices.

While implementing the Business Intelligence solutions all these things should be kept in mind for the

business needs to be met effectively. The system should be planned and designed and the applicationshould be given to qualified and experienced solutions providers. This way the benefits of the businesscan be reaped.

The seven steps to be followed while rolling out the BI solutions are: Make sure that the data is clean. Train the users effectively. Quickly deploy and adjust while progressing. Huge amount of time up front developing the

perfect reports should not be spent because the needs evolve as the business evolves. Deliver

the reports which provide the most value quickly and then tweak them.

An integrated approach should be considered while building the data warehouse from the starting.Getting into unwanted data strategy must be avoided.

The ROI should be clearly defined before starting. The specific benefits that have to be achievedshould be outlined and then a reality check has to be done every quarter or six months.

There should be focus on the business objectives. Business Intelligence software should not be bought just because there is a need. Deploy the BI

with the idea that there are numbers which has to be found and roughly understood where it is

required.


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Limitations of Business Intelligence

Data warehouses, that the BI systems attach to, generally do not contain all the necessary data to generatethe revenue from the existing company data. The data present in the data warehouse may not be in the

right format for sales. The relationships in the data warehouse may not be optimised for the revenue

generating user community. Data warehouses usually do not store old data to allow the formation oftrended information.

The final data quality is questionable. The queries can take a long time to run that is more than 10mins.

The IT departments will have data warehouses but only experts can access them. The sales representativewill not or may not use the BI tools. The queries solved out of the BI systems can be burdensome and

time consuming for the end users. The data analysts and the business intelligence tools do not have todirectly generate the revenue but there should be more effective and productive sales representatives.

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