Description
Ever since mainframe computers began accumulating vast storehouses of data in the 1970s, managers and executives have sought ways to turn random facts and figures into useful information upon which to base reliable business decisions.
ANALELE ?TIIN?IFICE ALE UNIVERSIT??II „ALEXANDRU IOAN CUZA” DIN IA?I
Tomul LII/LIII ?tiin?e Economice 2005/2006
BUSINESS INTELLIGENCE:
APPLICATIONS, TRENDS, AND STRATEGIES
LUMINI?A HURBEAN
*
Business Intelligence: aplica?ii, tendin?e ?i strategii
Abstract
Ever since mainframe computers began accumulating vast storehouses of data in the 1970s,
managers and executives have sought ways to turn random facts and figures into useful information
upon which to base reliable business decisions.
But it wasn't until the introduction of relational databases and client/server technology in the
1990s that companies took advantage of the market's need for decision support systems to create and
define a new industry, which is now widely known as business intelligence (BI). Business intelligence
allows organizations to extract useful, actionable information from a rapidly growing inventory of
disparate data sources, including multiple database platforms, packaged applications, data
warehouses, data marts and e-business systems.
The purpose of this paper is to point out the essentials of Business Intelligence in connection to
the ERP system, the evolution of the concept and the benefits of its implementation in the enterprise
information system. Finally, we will make some considerations on the adoption of business
intelligence applications.
Key words: business intelligence, ERP, analytics, OLAP, Corporate Performance Management.
1 Introduction
The Enterprise Resource Planning (ERP) concept is an growing one. As we like to say,
“ERP is a journey, not a destination” [Fotache, 2004, p. 14]. ERP revolutionized the
enterprise applications market in the 90s, but no one could envisage the subsequent
development.
The new millennium dawn brought a new generation of enterprise applications,
intended to be more customer-focused and to extend beyond the enterprise through e-
commerce interaction and collaboration with business partners. The key to the Internet-
driven, dynamic trade environment is agility. Thus, early ERP adopters discovered that
implementing these systems was only the first step toward creating a competitive IT
infrastructure. They and new users alike are now looking for significantly more
comprehensive functionality – from advanced planning and scheduling (APS) and
manufacturing execution systems (MES), to sales force automation (SFA) and customer
relationship management (CRM), to business intelligence (BI) and different e-business tools
to name only some – and demanding that they be integrated into their ERP system.
*
Conferen?iar doctor, Catedra de Informatic? ?i Statistic? Economic?, Facultatea de ?tiin?e
Economice, Universitatea de Vest din Timi?oara, e-mail: [email protected]
LUMINI?A HURBEAN
308
The new generation of enterprise applications goes beyond traditional transactional
business functions by enabling organizations to deliver real-time performance analysis
directly on the desktops of all business managers, for they can become more knowledgeable
and proactive [Fotache, 2004, pp. 96-98].
2 Business Intelligence: another step in the ERP evolution
At first, organizations realized that to maximize the value of the information stored in
their ERP systems, it was necessary to extend the ERP architectures to include more
advanced reporting, analytical and decision support capabilities.
While relational databases, presently used by ERP systems, are capable of retrieving a
small number of records in short time, they are not good at retrieving a large number of
records and summarizing them on demand. Most ERP products have a valuable database,
but, translating the data stored to information useful for decision making process has proven
difficult. With the availability of analytic solutions, several dozens of ERP providers can
offer their customers a valuable tool for harvesting the business value out of their database.
Thus, major ERP vendors have been increasingly embracing OLAP (On-line Analytical
Processing) tools that provide a high-level aggregated view of data.
Various analytics and business intelligence solutions enable organizations to track,
understand, and manage enterprise performance; they leverage the information that is stored
in corporate databases or data warehouses, legacy systems, and other enterprise applications.
Contrary to traditional core ERP, business intelligence and analytics provide an
environment in which business users receive information that is reliable, consistent,
understandable and easily manipulated. Because executives and middle management have
always had a need to understand their business’ performance regardless of good or bad
economic times - while the output from BI might change, the need is always there. The
classical three level business intelligence pyramid shows the instruments frequently used by
managers in different echelons – see figure 1.
Top
Management
Middle Management
Operational Management
Preformatted
Reports
Dashboards
Ad-hoc
Querying
OLAP
Fig. 1 Business Intelligence tools
Given that the BI tools have neither been terribly complex nor expensive to deploy, but
have still been helpful in easing the decision-making process, in the recent years they have
become considered necessary rather than as a luxury.
The latest evolutionary step introduces the concept of corporate performance
management (CPM), also referred to as enterprise performance management (EPM) or
business performance management (BPM), which is an emerging portfolio of applications
and methodology with business intelligence architectures and technologies at its core.
Business Intelligence: Applications, Trends and Strategies
309
Historically, BI applications have focused on measuring sales, profit, quality, costs and
many other indicators within an enterprise, but CPM goes well beyond these by introducing
the concepts of management and feedback, by embracing processes such as planning and
forecasting as core tenets of a business strategy.
So, CPM is the evolutionary combination of technology and business philosophy, built
on the basis of BI technology and applications that many enterprises have already
implemented (see figure 2). The demand for these applications lies in the fact that they add
value to previously installed enterprise applications, to a degree that the enterprise may
finally see some long delayed benefits and feel better about implementing ERP systems and
BI solutions.
DATA I NTEGRATI ON
BI Portal Collaboration
Metadata Analytic Engines
Security Developer Services
Reporting
Query and
Analysis
Interactive Analysis
Ad-Hoc Query
Enterprise Reporting
Embedded Reporting
Performance Management
Dashboards Scorecards
Fig. 2 Business Intelligence Tools and Technologies
CPM crosses traditional department boundaries to manage the full life cycle of
business decision-making. It involves mapping a structured set of data against predefined
reports, alerts, dashboards, analysis tools, key performance indicators (KPIs), etc., to
monitor and improve business processes based on the upfront established corporate strategic
objectives. Further, CPM creates a closed-loop process, starting with developing high-level
corporate goals and subsequent predefined KPIs, through measuring actual results against
the KPIs and representing this comparison in a scorecard, with the results reported to
management through intuitive reporting tools, and ultimately delivering these results back
into the business modeling process for corrections in the next planning cycle.
CPM augments BI applications, traditionally focused on measurement – mostly useless
without the ability to act on it! CPM represents a renewed focus on quantitative
management, a “management by numbers” method using insight gained from data analysis
and performance reporting [Cowan, 2004].
3 Business Intelligence benefits and challenges
Whole pages can be written to answer the first question but a compressed answer
shows that BI allows businesses:
• to leverage their information assets as a competitive advantage,
• to better understand the demand side of the business and manage customer
relationships,
LUMINI?A HURBEAN
310
• and to monitor results of change – both positive and negative.
There are thousands of articles, white papers, books, vendors, and consultants
dedicated to Business Intelligence. BI is listed among the top 10 technologies in 2005.
Motive? Because businesses today are moving “at the speed of information” as analysts like
to say. And because the economy demands it – companies are struggling to survive the
economic storm, by reducing costs or increasing revenues.
BI solutions enable decision-makers to launch queries against the various data sets that
are captured during the course of everyday business transactions: financial transactions,
customer records, inventories, sales, production, etc. By analyzing these data in various
ways, managers can discover trends, compare results, spot anomalies, and experiment with
„what if” scenarios. BI has thus become the quintessential enabling technology for effective
business management.
Howard Dresner, father of the Business Intelligence concept, explains why enterprises
must make business intelligence an imperative: “Doing business is information-intensive.
Enterprises are being pushed to share information with increasingly more audiences. The
business intelligence imperative insists we elevate BI to a strategic initiative now, or risk
disaster!” [Dresner, 2001]. He stresses the immense risk of not knowing and the worst of
incomplete information compared to no information. BI attempts to eliminate guessing and
ignorance in enterprises by leveraging the huge volume of quantitative data gathered every
day in a variety of corporate applications.
Nowadays, popular uses of BI include management dashboards and scorecards,
collaborative applications, workflow, analytics, enterprise reporting, financial reporting, and
both customer and supplier extranets. These solutions enable companies to gain visibility
into their business, acquire and retain profitable customers, reduce costs, detect patterns,
optimize the supply chain, analyze product portfolio, increase productivity and improve
financial performance.
4 Some aspects about Business Intelligence implementation
An enterprise should go through two phases before it is ready for BI. The first phase
refers to the implementation of a solid transaction system; an integrated system like ERP, if
possible. Its major aim is to create an OLTP system for collecting, storing, and updating
transactional data in relational databases. Initially, these systems were reduced to the finance
and accounting area – the market offered lots of financial accounting applications. Then,
other types of applications were added: sales, procurement, inventory management, human
resources management, and so on. Sometimes companies used different solutions from
different vendors, or they combined it with domestic software, so they faced the problem of
multiple data sources. The second phase is meant to solve the problem of asynchronous
master data. The upgrade to integrated systems became crucial as the number of modules
significantly increased.
There are two types of BI implementations:
• Implementing BI applications with the standard functionality, for creating simple,
multidimensional OLAP cubes. It often reduces to an OLAP module which
includes a set of predefined multidimensional models for analysis of different
types of data. The data are available in the OLTP system. Oracle, Microsoft, or
Business Objects (recently entered Romania) offer the most popular tools for
creating OLAP modules.
• Development of more sophisticated analytical models, in order to reflect the
unique mix of the company’s targets and factors of influence. Developing a
Business Intelligence: Applications, Trends and Strategies
311
“home-grown solution” is a good choice when functional criteria are not met by
standard applications and there is a wish for total integration within the existing
planning and control and/or knowledge management procedures, methodologies,
and tools within the enterprise.
Recommendations for BI applications should be based on a company’s functional
requirements, budget, technical architecture, and overall user need. Selecting and
implementing the right BI is a challenging job. Implementing BI is a costly and time
consuming venture. If the wrong BI is implemented without good research and planning it
could be a failure initiative. One very important point to be considered for selecting BI is
there should be a close match between company’s requirements and vendors provided
solutions.
5 Conclusions
Today’s organizations are relying on Business Intelligence applications to provide
them with hard facts that help them make better, more informed decisions to obtain
unforeseen rewards.
We can conclude that their success in business depend on the implementation of BI
systems. The vast amounts of data, growing at 30-50 percent a year [Baxter, 2005], the
increasing burden of government regulation and compliance obligations, competition and
customer demands are focusing attention on the need for timely – and often real-time –
information, and in plenty of detail. The issues that should be addressed in order to
successfully integrate BI into the enterprise are:
• prepare a solid foundation with the ERP system in the core, so as to take care of
the purity of the data sources (data quality),
• identify where, who, and when BI is needed in harmony with the established
business objectives, in an attempt to prevent the “shelfware” – unused or
underused software, sitting around in enterprise,
• keep in mind the necessity for set up a common BI platform of integrated tools,
with the intention of avoiding the “BI islands” – different applications that can’t
communicate with each other,
• integrate BI into enterprise portals or keep this option open for the near future, as
users have different roles across the enterprise, and use different applications –
they should have the BI they needed, integrated to fit their job function.
Last, but not least, large enterprises should tackle BI strategically, because they have
valuable data that can tell them about performance, customer behavior, process efficiency,
and important trends. There are a lot of companies with a tactical view of BI: specific
BI/analytical applications implemented in some departments or as part of some other
application. For many of them it is difficult to implement BI strategically, as this approach
forces the enterprise to reflect upon itself and how it actually work. Another reason that can
be mentioned here is the cultural profile of the organizations – the resistance to change and
the fear of what they might learn are serious challenges for BI strategic projects.
Final conclusion: businesses can create intelligence from their data and provide timely,
accurate access to their end users. Business Intelligence is the latest buzzword working its
way through the business and technology worlds. Much like ERP, SFA, and CRM before it,
the hype is now shifting toward Business Intelligence.
LUMINI?A HURBEAN
312
References
Baxter, A., Business Intelligence needs smarter handling, 2005,http://www.gartner.com,
accessed on March 12, 2006.
Computerworld Executive Briefings, Get smart about Business Intelligence, 2004,http://www.computerworld.com, accessed on November 20, 2005.
Cowan, T., Unified Business Performance Management, www.businessintelligence.com,
2004, accessed on February 18, 2006.
Dresner, H., Why enterprises must make business intelligence an imperative, 2001,http://www.gartnergroup.com, accessed on February 18, 2006.
Dwight, H., Business Intelligence for the rest of us – Five reasons why this has not yet
become a reality, 2003,http://www.businessintelligence.com, accessed on November 20,
2005.
Fotache, D., Hurbean L., Solutii informatice integrate pentru gestiunea afacerilor - ERP,
Editura Economica, Bucuresti, 2004.
Hurbean, L., A new ERP era: integration of CRM, SCM and BI Applications, Proceedings of
the First International Conference on Information and Management Sciences, May 2002,
Xi’An, China, pp.305-310.
Liautaud, B., Hammond, M., E-Business intelligence: Turning information into knowledge
into profit, McGraw-Hill, New York, 2001.
Vitt, E., Business Intelligence: Making better decisions faster, Microsoft Press, 2002.
***, “Business Intelligence – cover story”, 2004, Computerworld Romania, no. 5/2004.
***, Romanian IT&C Directory, a supplement of Computerworld Romania, No. 3/2005.
doc_167401384.pdf
Ever since mainframe computers began accumulating vast storehouses of data in the 1970s, managers and executives have sought ways to turn random facts and figures into useful information upon which to base reliable business decisions.
ANALELE ?TIIN?IFICE ALE UNIVERSIT??II „ALEXANDRU IOAN CUZA” DIN IA?I
Tomul LII/LIII ?tiin?e Economice 2005/2006
BUSINESS INTELLIGENCE:
APPLICATIONS, TRENDS, AND STRATEGIES
LUMINI?A HURBEAN
*
Business Intelligence: aplica?ii, tendin?e ?i strategii
Abstract
Ever since mainframe computers began accumulating vast storehouses of data in the 1970s,
managers and executives have sought ways to turn random facts and figures into useful information
upon which to base reliable business decisions.
But it wasn't until the introduction of relational databases and client/server technology in the
1990s that companies took advantage of the market's need for decision support systems to create and
define a new industry, which is now widely known as business intelligence (BI). Business intelligence
allows organizations to extract useful, actionable information from a rapidly growing inventory of
disparate data sources, including multiple database platforms, packaged applications, data
warehouses, data marts and e-business systems.
The purpose of this paper is to point out the essentials of Business Intelligence in connection to
the ERP system, the evolution of the concept and the benefits of its implementation in the enterprise
information system. Finally, we will make some considerations on the adoption of business
intelligence applications.
Key words: business intelligence, ERP, analytics, OLAP, Corporate Performance Management.
1 Introduction
The Enterprise Resource Planning (ERP) concept is an growing one. As we like to say,
“ERP is a journey, not a destination” [Fotache, 2004, p. 14]. ERP revolutionized the
enterprise applications market in the 90s, but no one could envisage the subsequent
development.
The new millennium dawn brought a new generation of enterprise applications,
intended to be more customer-focused and to extend beyond the enterprise through e-
commerce interaction and collaboration with business partners. The key to the Internet-
driven, dynamic trade environment is agility. Thus, early ERP adopters discovered that
implementing these systems was only the first step toward creating a competitive IT
infrastructure. They and new users alike are now looking for significantly more
comprehensive functionality – from advanced planning and scheduling (APS) and
manufacturing execution systems (MES), to sales force automation (SFA) and customer
relationship management (CRM), to business intelligence (BI) and different e-business tools
to name only some – and demanding that they be integrated into their ERP system.
*
Conferen?iar doctor, Catedra de Informatic? ?i Statistic? Economic?, Facultatea de ?tiin?e
Economice, Universitatea de Vest din Timi?oara, e-mail: [email protected]
LUMINI?A HURBEAN
308
The new generation of enterprise applications goes beyond traditional transactional
business functions by enabling organizations to deliver real-time performance analysis
directly on the desktops of all business managers, for they can become more knowledgeable
and proactive [Fotache, 2004, pp. 96-98].
2 Business Intelligence: another step in the ERP evolution
At first, organizations realized that to maximize the value of the information stored in
their ERP systems, it was necessary to extend the ERP architectures to include more
advanced reporting, analytical and decision support capabilities.
While relational databases, presently used by ERP systems, are capable of retrieving a
small number of records in short time, they are not good at retrieving a large number of
records and summarizing them on demand. Most ERP products have a valuable database,
but, translating the data stored to information useful for decision making process has proven
difficult. With the availability of analytic solutions, several dozens of ERP providers can
offer their customers a valuable tool for harvesting the business value out of their database.
Thus, major ERP vendors have been increasingly embracing OLAP (On-line Analytical
Processing) tools that provide a high-level aggregated view of data.
Various analytics and business intelligence solutions enable organizations to track,
understand, and manage enterprise performance; they leverage the information that is stored
in corporate databases or data warehouses, legacy systems, and other enterprise applications.
Contrary to traditional core ERP, business intelligence and analytics provide an
environment in which business users receive information that is reliable, consistent,
understandable and easily manipulated. Because executives and middle management have
always had a need to understand their business’ performance regardless of good or bad
economic times - while the output from BI might change, the need is always there. The
classical three level business intelligence pyramid shows the instruments frequently used by
managers in different echelons – see figure 1.
Top
Management
Middle Management
Operational Management
Preformatted
Reports
Dashboards
Ad-hoc
Querying
OLAP
Fig. 1 Business Intelligence tools
Given that the BI tools have neither been terribly complex nor expensive to deploy, but
have still been helpful in easing the decision-making process, in the recent years they have
become considered necessary rather than as a luxury.
The latest evolutionary step introduces the concept of corporate performance
management (CPM), also referred to as enterprise performance management (EPM) or
business performance management (BPM), which is an emerging portfolio of applications
and methodology with business intelligence architectures and technologies at its core.
Business Intelligence: Applications, Trends and Strategies
309
Historically, BI applications have focused on measuring sales, profit, quality, costs and
many other indicators within an enterprise, but CPM goes well beyond these by introducing
the concepts of management and feedback, by embracing processes such as planning and
forecasting as core tenets of a business strategy.
So, CPM is the evolutionary combination of technology and business philosophy, built
on the basis of BI technology and applications that many enterprises have already
implemented (see figure 2). The demand for these applications lies in the fact that they add
value to previously installed enterprise applications, to a degree that the enterprise may
finally see some long delayed benefits and feel better about implementing ERP systems and
BI solutions.
DATA I NTEGRATI ON
BI Portal Collaboration
Metadata Analytic Engines
Security Developer Services
Reporting
Query and
Analysis
Interactive Analysis
Ad-Hoc Query
Enterprise Reporting
Embedded Reporting
Performance Management
Dashboards Scorecards
Fig. 2 Business Intelligence Tools and Technologies
CPM crosses traditional department boundaries to manage the full life cycle of
business decision-making. It involves mapping a structured set of data against predefined
reports, alerts, dashboards, analysis tools, key performance indicators (KPIs), etc., to
monitor and improve business processes based on the upfront established corporate strategic
objectives. Further, CPM creates a closed-loop process, starting with developing high-level
corporate goals and subsequent predefined KPIs, through measuring actual results against
the KPIs and representing this comparison in a scorecard, with the results reported to
management through intuitive reporting tools, and ultimately delivering these results back
into the business modeling process for corrections in the next planning cycle.
CPM augments BI applications, traditionally focused on measurement – mostly useless
without the ability to act on it! CPM represents a renewed focus on quantitative
management, a “management by numbers” method using insight gained from data analysis
and performance reporting [Cowan, 2004].
3 Business Intelligence benefits and challenges
Whole pages can be written to answer the first question but a compressed answer
shows that BI allows businesses:
• to leverage their information assets as a competitive advantage,
• to better understand the demand side of the business and manage customer
relationships,
LUMINI?A HURBEAN
310
• and to monitor results of change – both positive and negative.
There are thousands of articles, white papers, books, vendors, and consultants
dedicated to Business Intelligence. BI is listed among the top 10 technologies in 2005.
Motive? Because businesses today are moving “at the speed of information” as analysts like
to say. And because the economy demands it – companies are struggling to survive the
economic storm, by reducing costs or increasing revenues.
BI solutions enable decision-makers to launch queries against the various data sets that
are captured during the course of everyday business transactions: financial transactions,
customer records, inventories, sales, production, etc. By analyzing these data in various
ways, managers can discover trends, compare results, spot anomalies, and experiment with
„what if” scenarios. BI has thus become the quintessential enabling technology for effective
business management.
Howard Dresner, father of the Business Intelligence concept, explains why enterprises
must make business intelligence an imperative: “Doing business is information-intensive.
Enterprises are being pushed to share information with increasingly more audiences. The
business intelligence imperative insists we elevate BI to a strategic initiative now, or risk
disaster!” [Dresner, 2001]. He stresses the immense risk of not knowing and the worst of
incomplete information compared to no information. BI attempts to eliminate guessing and
ignorance in enterprises by leveraging the huge volume of quantitative data gathered every
day in a variety of corporate applications.
Nowadays, popular uses of BI include management dashboards and scorecards,
collaborative applications, workflow, analytics, enterprise reporting, financial reporting, and
both customer and supplier extranets. These solutions enable companies to gain visibility
into their business, acquire and retain profitable customers, reduce costs, detect patterns,
optimize the supply chain, analyze product portfolio, increase productivity and improve
financial performance.
4 Some aspects about Business Intelligence implementation
An enterprise should go through two phases before it is ready for BI. The first phase
refers to the implementation of a solid transaction system; an integrated system like ERP, if
possible. Its major aim is to create an OLTP system for collecting, storing, and updating
transactional data in relational databases. Initially, these systems were reduced to the finance
and accounting area – the market offered lots of financial accounting applications. Then,
other types of applications were added: sales, procurement, inventory management, human
resources management, and so on. Sometimes companies used different solutions from
different vendors, or they combined it with domestic software, so they faced the problem of
multiple data sources. The second phase is meant to solve the problem of asynchronous
master data. The upgrade to integrated systems became crucial as the number of modules
significantly increased.
There are two types of BI implementations:
• Implementing BI applications with the standard functionality, for creating simple,
multidimensional OLAP cubes. It often reduces to an OLAP module which
includes a set of predefined multidimensional models for analysis of different
types of data. The data are available in the OLTP system. Oracle, Microsoft, or
Business Objects (recently entered Romania) offer the most popular tools for
creating OLAP modules.
• Development of more sophisticated analytical models, in order to reflect the
unique mix of the company’s targets and factors of influence. Developing a
Business Intelligence: Applications, Trends and Strategies
311
“home-grown solution” is a good choice when functional criteria are not met by
standard applications and there is a wish for total integration within the existing
planning and control and/or knowledge management procedures, methodologies,
and tools within the enterprise.
Recommendations for BI applications should be based on a company’s functional
requirements, budget, technical architecture, and overall user need. Selecting and
implementing the right BI is a challenging job. Implementing BI is a costly and time
consuming venture. If the wrong BI is implemented without good research and planning it
could be a failure initiative. One very important point to be considered for selecting BI is
there should be a close match between company’s requirements and vendors provided
solutions.
5 Conclusions
Today’s organizations are relying on Business Intelligence applications to provide
them with hard facts that help them make better, more informed decisions to obtain
unforeseen rewards.
We can conclude that their success in business depend on the implementation of BI
systems. The vast amounts of data, growing at 30-50 percent a year [Baxter, 2005], the
increasing burden of government regulation and compliance obligations, competition and
customer demands are focusing attention on the need for timely – and often real-time –
information, and in plenty of detail. The issues that should be addressed in order to
successfully integrate BI into the enterprise are:
• prepare a solid foundation with the ERP system in the core, so as to take care of
the purity of the data sources (data quality),
• identify where, who, and when BI is needed in harmony with the established
business objectives, in an attempt to prevent the “shelfware” – unused or
underused software, sitting around in enterprise,
• keep in mind the necessity for set up a common BI platform of integrated tools,
with the intention of avoiding the “BI islands” – different applications that can’t
communicate with each other,
• integrate BI into enterprise portals or keep this option open for the near future, as
users have different roles across the enterprise, and use different applications –
they should have the BI they needed, integrated to fit their job function.
Last, but not least, large enterprises should tackle BI strategically, because they have
valuable data that can tell them about performance, customer behavior, process efficiency,
and important trends. There are a lot of companies with a tactical view of BI: specific
BI/analytical applications implemented in some departments or as part of some other
application. For many of them it is difficult to implement BI strategically, as this approach
forces the enterprise to reflect upon itself and how it actually work. Another reason that can
be mentioned here is the cultural profile of the organizations – the resistance to change and
the fear of what they might learn are serious challenges for BI strategic projects.
Final conclusion: businesses can create intelligence from their data and provide timely,
accurate access to their end users. Business Intelligence is the latest buzzword working its
way through the business and technology worlds. Much like ERP, SFA, and CRM before it,
the hype is now shifting toward Business Intelligence.
LUMINI?A HURBEAN
312
References
Baxter, A., Business Intelligence needs smarter handling, 2005,http://www.gartner.com,
accessed on March 12, 2006.
Computerworld Executive Briefings, Get smart about Business Intelligence, 2004,http://www.computerworld.com, accessed on November 20, 2005.
Cowan, T., Unified Business Performance Management, www.businessintelligence.com,
2004, accessed on February 18, 2006.
Dresner, H., Why enterprises must make business intelligence an imperative, 2001,http://www.gartnergroup.com, accessed on February 18, 2006.
Dwight, H., Business Intelligence for the rest of us – Five reasons why this has not yet
become a reality, 2003,http://www.businessintelligence.com, accessed on November 20,
2005.
Fotache, D., Hurbean L., Solutii informatice integrate pentru gestiunea afacerilor - ERP,
Editura Economica, Bucuresti, 2004.
Hurbean, L., A new ERP era: integration of CRM, SCM and BI Applications, Proceedings of
the First International Conference on Information and Management Sciences, May 2002,
Xi’An, China, pp.305-310.
Liautaud, B., Hammond, M., E-Business intelligence: Turning information into knowledge
into profit, McGraw-Hill, New York, 2001.
Vitt, E., Business Intelligence: Making better decisions faster, Microsoft Press, 2002.
***, “Business Intelligence – cover story”, 2004, Computerworld Romania, no. 5/2004.
***, Romanian IT&C Directory, a supplement of Computerworld Romania, No. 3/2005.
doc_167401384.pdf