A Report on Business Intelligence

BUSINESS INTELLIGENCE

Amulya Lohani | 12063542 1

1. Introduction

1.1. General Introduction In today’s challenging business environment, it is a vital for organization to

access useful information and knowledge. Business Intelligence (BI) is an umbrella concept for tools, techniques and solutions that helps organizations to understand business situation. BI is defined as “computer based techniques used in identifying, extracting, and analyzing business data”. BI helps organization turn data into useful and meaningful information and then distribute this information to those who need it, when they need it, wherever they need it – so that they can make timely and better-informed decisions. (Schiff, 2012)

BI software is already being used by thousands of companies to find new revenue opportunities, reduce costs, reallocate resources, and improve operational efficiency. BI has settled a place among the priorities in technological solutions for the last couple of years. Not surprisingly, BI and analytics are one of the top-ranked technologies for 2012 according to Gartner. Since 2003, the market has grown from $1.6 billion, which accounts for an almost 500% growth. An increase in BI investments is an indicator that organizations recognize the value of properly implemented BI solutions. BI has achieved this importance because it is an integral part of the decision making process, and this trend is expected to continue in future. (Vizgaitytė, 2012)

Key Terms

Data: Raw value elements or facts.

Information: The result of collecting and organizing data that provides context and meaning.

OLAP: A multi-dimensional analysis and reporting application for aggregated data great for discovering details from large quantities of data.

Data Mining: Processes and techniques for seeking knowledge (relationship, trends, patterns, etc.) from a large amount of data.

Dashboard: Digital dashboard is a visual and interactive presentation of data to make it easy to read and understand in a short time.

Data Marts: A data mart is a subset of the data warehouse that is used to support analytical needs of a particular business function or department.

Meta Data: Metadata refers to data about data.



1.2. History

Term BI was used first in 1958. However, in the sense in which currently the term BI was used, it started happening since 1990’s. From technology prospective, BI was born in 1990’s.

Figure 1: Timeline showing the evolution of BI (Harris, 2014)



2. Background

Companies today are awash in a sea of information. This ever-growing surge of data can cause uncertainty and bring on stormy and messy conditions for businesses. To maintain a strong decision management strategy and harness the power of data, companies need the right tools to achieve breakthrough insights. Business Intelligence tools offers a compelling vision of the transformation of data from its raw state all the way through to distilling clear and actionable insights.

When companies perform their day to day operations either using ‘Enterprise resource planning (ERP)’ software or some other applications, data gets generated. These raw data should be analyzed to extract meaningful information from it. Based on this meaningful information, organizations comes up with strategies for the future so that they could make more profit and could be more stable in the future. Making future decisions directly based on the raw data is nearly impossible. This has to be converted into meaningful information. It is business intelligence software that converts the raw data into meaningful information. Management of the company analyses the meaningful information and they take actions based on this information to make future decisions.

Figure 2: Dashboard of a BI tool (Conceptdraw, 2014)



2.1 How does BI system work?

The BI system has four major stages. Each of them are described briefly below.

Figure 3: BI Architecture (Khan, 2012)

a. Data capture The data capturing component consists of an interface to collect data from

operational systems to load into the data warehouse. Data is first entered or processed by a daily business process that is based on Online Transaction Processing (OLTP) environment and stored in any kind of operational database.



b. ETL (Extract, Transform, and Load) Engine

Before raw data is stored in the data warehouse, it has to be passed through ETL engine.

Extraction: Data captured from numerous sources are purified. It checks for the correctness of extracted data to correct inconsistent, missing, or invalid values.

Transform: Data transformation integrates data into standard formats and applies business rules that map data to the warehouse schema. Aggregates (e.g., summary table data) and imputed characteristics are generated.

Load: Finally extracted and transformed data are loaded in the data warehouse.

c. Data Warehousing

The primary purpose of data warehouse is to support organization in decision making. Data warehouse stores data collected from operational systems or external data sources. It must contain enough data to answer certain questions about business.

Data Marts: Data marts helps to get prototype as soon as possible without waiting for a larger corporate data warehouse, because it’s small and easy to develop. (Bukhbinder, 2005) Meta Data: It describes where data are being used and stored, the source of data, what changes have been made to the data, and how one piece of data relates to other information (Giovinazzo, 2003).

d. Data access and analysis This component consists of data accessing tools and techniques that give

analysts clear and interactive information, friendly enough for use by a non-technical person. OLAP: OLAP provides users with the means to explore and analyze large amounts of data, involving complex computations, their relationships, and visually present results in different perspectives. Data Mining: Data mining helps in data analysis for discovering patterns and regularities in sets of data. It is responsible for finding the patterns by identifying the underlying rules and features in the data.



2.2. Some popular BI software

Figure 4: Major BI vendors with their products (Evelson, 2013)

There is large number of BI products and vendors. Yet, vendors and their products listed in Figure 4 are the major ones. In 2013, Forrester (technology and Market Research Company) had selected these 11 BI software vendors and their products for a market evaluation. According to Forrester, these are complete, self-contained, fully functional systems having qualities that takes to support BI in complex organizations.

There are also some Open source BI tools. The three most popular open source BI reporting tools are: Brit, JasperReport and Pentaho. (Opensource, 2014)



2.3. BI application areas Wide number of areas can be benefited from BI. Below is the list of some major application areas of BI along with key BI features from which they are benifitted.

a. Business management

Performance management

Strategy management

Benchmarking

b. Marketing and sales

Customer relationship management (CRM)

Customer behavior analysis

Targeted marketing and sales strategies

Customer profiling

Collaborative filtering

c. Financial management

Chronological analysis of data

Performance accounting

Risk management

d. Logistics

Supplier and vendor management

Shipping and inventory control

e. Web site management

Web analytics

f. Healthcare management

Monetary Assessment

Medical Data Analysis

Patient care analysis

g. Education

Learning analytics

Institutional effectiveness

h. Telecommunications

Functional and funds evaluation

Capacity supervision

Operational management of various channels

Source: (Business.mapsofindia, 2014)



3. Analysis

3.1. Analysis of pros and cons

Pros

a. Better decisions BI software provides organizations with rich, exact and up-to-date information

and let to dive into data for further investigation, which will become beneficial for organization to make better decisions.

b. Faster decisions

BI systems displays results in common reports combining data from multiple sources. It prevents decision maker to manually combine data in spreadsheets, saving bunch of time.

c. Reduced labor costs

BI tool can automatically perform multiple tasks, such as data collection, report generation, graphs and charts designing, etc. It reduces staff training needed for maintaining such activities. Thus BI system is beneficial in reducing time and effort of staffs preventing them to prepare reports manually.

d. Reduced information bottlenecks

BI tool provides individualized and role-based dashboards along with clear documentation of information allowing users to analyze and validate the data without involving IT specialists. Thus, users can easily view, assemble and personalize information.

e. Get insight into customer’s behavior

BI system allows companies to gain visibility into what customers are buying (or not), giving them "the ability to turn this knowledge into additional profit" and retain valuable customers.

Cons

a. Costs are difficult to quantify Implementing BI system is not very suitable in small and medium sized

organization. Investing too much on such expensive systems just to get information on data is quite unrealistic.

b. Complexity Even a company owns a BI system, it is very complex to maintain. To run the BI

system smoothly and extract better results, trained professionals is required. Sometimes it can be a problem in an organization.



c. Security Risks Storing valuable information in the company’s server increases the risk of being

accessed by unauthorized users. Information is less secured if there is some problem in the software itself or if any illegal users get access to storage devices of the users who have legal access.

Despite these drawbacks, BI really have cool features that can benefit a company in a greatest possible ways. It is up to the company implementing BI and the user of the system to eliminate these risks and use BI tools to make great decisions for better business future.

3.2. How is BI paying off in business?

a. Perry’s Ice Cream

Perry’s ice cream is the distributor of 12 million gallons of ice-cream every year, situated in New York.

Business Needs: According to CIO of Perry’s Ice Cream, Mr. David Hodgson, company processed lots of transactions and business was going well. However, company was not able to figure out the customer’s behavior. Company had to deal with limited customers and was not able to take its business to next level.

Solution: Logi Analytics

Results: “Logi Info turned out to be not just a solution we could afford, but also a better solution for us,” stated Mr. Hodgson. By integrating BI, company was able to analyze its sales, which showed a high level of summary of transactions across Perry’s various customer-based and item-based categories. Users were able to drill into the data to find whatever info they wanted. (Logi Analytics, 2010)

b. Stein Mart

Stein Mart is a nationwide department store with 265 locations across the United States. It offers discount brand name merchandise including clothing, shoes, accessories, and home decor.

Business Needs: Company needed better access to business data to set prices each week. Company needed to analyze trends of its sales so that it could figure out the popular products and put those popular items in stock before they became in high demands.

Solution: Microsoft data warehouse and BI solution, in July 2009



Results: According to Kevin Cornett, Senior Manager of Business Intelligence at Stein Mart, company was able to manage information more efficiently and cut reporting time from hours to minutes. The solution was easy to use and manage, and the company has cut its total cost of ownership by more than 60 percent. This created a better shopping experience for customers and a more profitable business model for Stein Mart. (Microsoft, 2014)

Above examples of BI implementation shows, companies are taking good benefit from BI tools. Not only business organizations are benefitted from BI. Customers can also experience a better shopping experience being able to shop their favorite products minimizing the chance lack of items in the stock.



3.3. BI Capabilities

Figure 5: Four synergistic BI capabilities (Sabherwal, 2011)

Figure 5 points out major capabilities of BI software. The chief BI capability is the Organizational Memory. Information and knowledge are stored in BI system in such a way that they can be accessed and observed later. It aids the next BI ability, i.e. Information Integration, which is the ability to link structured and unstructured information from variety of sources. Information integration helps in Insight Creation. Creating Insight means ability to develop new intuitions to use them in business for short term or long term for better decision making. Lastly, insight creation provides contributions to Presentation capability by providing new insights and information. Thus, BI system have ability to use appropriate reporting and stable scorecard tools making BI more appreciated to its users.



3.4. Comparison of Information gathering practice with or without using Self-service BI tool

Table 1: Comparison of information gathering practice with or without using BI tool

Based on the comparison in Table 1, we can conclude that decision making in an organization can be much more effective by the use of self-service BI tools.



3.5. Open Source BI (OSBI) vs. Proprietary BI

Table 2: Comparison between OSBI and Proprietary BI tools (MAIA Intelligence , 2010)

The comparison in Table 2 points out many limitations of OSBI comparing with proprietary BI. Most people have a mistaken perception that Open Source is Free. The cost of implementing BI is not only the cost of software. There might require indirect costs to purchase any other supporting products and monitoring tools. This comparison clearly indicates, even though Open Source BI is being hyped a lot, it is still a long way to go and compete with the actual BI market.



3.6. BI Market

Top 5 Business Intelligence and Analytics Software Vendors, Worldwide, 2012-2013 (Millions of Dollars)

Table 3: Market details of top 5 BI software vendors in 2012 and 2013 (Gartner, 2014)

Table 3 shows the details of a recent market research done by Gartner, Inc. on market growth of top BI software vendors from 2012 to 2013. According to the research, global BI and analytics software market grew by 8% (approx.). SAP became top vendor with 21.3% market share and total revenue of $3057.0 million followed by Oracle (13.9%) and IBM (12.7%). Microsoft had the highest market growth rate among top 5 vendors with revenue rising by 15.9% compared with 2012.

Business Intelligence has become the top ranked IT priority among enterprise business leaders over the last few years. But single digit market growth in 2013 shows that confusion still reign around business companies on how to make best analysis relying on information. Challenging macros and excess use of IT-led traditional BI tools might also be factors of slowing BI market in 2013.



4. Conclusion

4.1. Critical Evaluation The topic ‘Business Intelligence’ have always become the topic of my interest

since I started to know about it. So I was really excited to write report on the topic. I had gone through some difficulties while preparing the report. Major difficulty was I couldn’t find proper graphs and charts representing progress in a company after using BI tool. So I had to spend a lot of time in the analysis section. Yet, I really enjoyed this report preparation from which I also got to know many facts about BI.

Based on analysis, in my opinion, BI has lot of capabilities to enhance the way of conducting business by allowing companies to make smart decisions and take necessary actions whenever necessary. Large enterprises are already aware of this fact. However, small and medium enterprises are still in the state of confusion whether to invest in BI or not. This misperception should be eliminated and business companies should drive for finding a suitable BI tool for their business based to their needs.

4.2. Future Escalation With the rapid advancement in technology and evolving of advanced social

networking sites, smartphones and cloud based applications, BI is not only restricted to traditional desktop or web based systems. New BI trends have already emerged out and are in a position to take hike in the market within few years. Some of the new trends are Social BI (analytics through social networking sites), Mobile BI (analysis on mobile devices such as smartphones and tablets) and Cloud BI (Bi applications hosted on virtual network).

Global BI market size, by technologies, 2013-2018 ($ Billion)

Figure 6: Global BI market size by technologies, 2013-2018 (Redwood Capital, 2014)



Figure 5 shows that traditional BI is projected to slow down its growth in next few years. Newer BI technologies are expected to grow at rates between 20% and 30% over next 4 years. Cloud BI is estimated to grow by $2.94 billion by 2018, for a Compound annual growth rate of 31%.

Thus, BI has been successful to become the top ranked IT priority among enterprise business leaders over the last few years and is expected to increase its market in the future.



References

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Vizgaitytė, G. (2012). BuSiNESS iNTElliGENCE iN ThE PrOCESS Of dECiSiON MAKiNG: ChANGES ANd TrENdS. EKoNoMIKA , 149.

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Logi Analytics. (2010). Perry’s Ice Cream Improves Sales Analysis with Logi Analytics. Logi Analytics.

Microsoft.com, (2014). Microsoft Case Study: Microsoft SQL Server 2012 Enterprise - Stein Mart. [online] Available at: http://www.microsoft.com/casestudies/Microsoft-SQL-Server-2012-Enterprise/Stein-Mart/Retailer-Drives-Nationwide-Selling-Strategy-and-Cuts-TCO-by-600-000-with-BI-Solution/710000000196 [Accessed 22 Oct. 2014].

Sabherwal, R. (2011). Business intelligence Practices, Technologies and Management. Donald Fowlay.

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Gartner.com, (2014). Gartner Says Worldwide Business Intelligence and Analytics Software Market Grew 8 Percent in 2013. [online] Available at: http://www.gartner.com/newsroom/id/2723717 [Accessed 22 Oct. 2014].

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A Report on Business Intelligence

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