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CIEN_O4 - BI&CI gloosary of terms Flipbook PDF
CIEN_O4_Training Modules_BI&CI Glossary of Terms - An Intellectual Output developed in the Erasmus+ Strategic Partne
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O4 – Business and Competitive Intelligence Training Modules GLOSSARY OF TERMS Erasmus+ Programme – Strategic Partnership Project Nr: 2016-1-RO01-KA203-024798
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”Improving decision making skills in students and professionals.”
Business and Competitive Intelligence for Entrepreneurship
A Brief Description of the Project Strategic Highlights 24 months – October 2016-September 2018 5 universities: Bucharest University of Economic Studies BUES (ASE) - Romania, University Ovidius of Constanța - Romania, Aristotelio Panepistimio Thessaloniki – Greece, University of Economics – Varna – Bulgaria, Conservatoire National des Arts et Metiers – CNAM – Paris – France. Objectives: Creating a network of universities in Romania, Bulgaria, Greece, and France, aimed at developing knowledge, skills and competences in the field of business and competitive intelligence (BI and CI). The project creates ready kits for universities to implement new curricula, ready-made training modules for academia and businesses, and a Survival Kit, usable by any entrepreneur, without guidance, through interactive resources, via the online platform. Moreover, the project creates a multiplier event, the Knowledge Fair, facilitating the creation of a knowledge alliance and a community of practice on the topic of BI/CI, and allowing for a wide know-how sharing experience.
Operating Highlights Target group: 100 students directly and 550 other stakeholders through multiplier events Key events: 2 summer schools, 2 knowledge fairs, 5 transnational project meetings, BI/CI module creation and delivery, CIEN Survival Kit creation.
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Summary of the Glossary of terms
The present Glossary is considered to be an extremely useful tool for BI/CI professionals and education staff to develop proper training programs in the field of BI and CI Education. It consists of two parts: BI terms and CI terms and it cover to basic terminology used within the industry and beyond. The scope is to define a conceptual integrated framework for experts to provide better training and to acquire additional competences in the field.
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Business and Competitive Intelligence for Entrepreneurship
Glossary of BI Terms Automated Analysis: Automatic analysis of data to find hidden insights in the data and show users the answers to questions they have not even thought of yet. BI Analyst: As stated by modernanalyst.com, a data analyst is a professional who is in charge of analyzing and mining data to identify patterns and correlations, mapping and tracing data from system to system in order to solve a problem, using BI and data discovery tools to help business executives in their decision making, and perform statistical analysis of business data, among other things. (Can be called a data analyst too) BI Governance: According to Boris Evelson, from Forrester Research, BI governance is a key part of data governance, but if focuses on a BI system and governs over who uses the data, when, and how. Big Data: Enormous and complex data sets that traditional data processing tools cannot deal with. Bottlenecks: Points of congestion or blockage that hinder the efficiency of the BI system. Business Intelligence: According to Gartner, “Business Intelligence is an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.” Centralized Business Intelligence: A BI model that enables users to work connected and share insights, while seeing the same and only version of the truth. IT governs over data permissions to ensure data security.
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Business and Competitive Intelligence for Entrepreneurship Collaborative BI: An approach to Business Intelligence where the BI tool empowers users to collaborate between colleagues, share insights, and drive collective knowledge to improve decision making. Collective Knowledge: Knowledge that benefits the whole enterprise as it comes from the sharing of insights and data findings across groups and departments to enrich analysis. Dark Data: According to Gartner, the definition for Dark Data is “information assets that organizations collect process and store in the course of their regular business activity, but generally fail to use for other purposes”. 90% of companies’ data is dark data. Dashboards: A data visualization tool that displays the current enterprise health, the status of metric and KPIs, and the current data analysis and insights. Data Analyst: As stated by modernanalyst.com, a data analyst is a professional who is in charge of analyzing and mining data to identify patterns and correlations, mapping and tracing data from system to system in order to solve a problem, using BI and data discovery tools to help business executives in their decision making, and perform statistical analysis of business data, among other things. Data Analytics: According to TechTarget, “data analytics is the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software.” Data Governance: According to Boris Evelson, from Forrester Research, data governance “deals with the entire spectrum (creation, transformation, ownership, etc.) of people, processes, policies, and technologies that manage and govern an enterprise’s use of its data assets (such as data governance stewardship applications, master data management, metadata management, and data quality).
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Business and Competitive Intelligence for Entrepreneurship Data Mashup: Integration multiple data sets in a unified analytical and visual representation. Data Silos: According to Tech Target, a data silo is “data that is under the control of one department or person and is isolated from the rest of the organization.” Data silos are a bottleneck for effective business operations. Data Sources: The source where the data to be analyzed comes from. It can be a file, a database, a dataset, etc. Modern BI solutions like Necto can mashup data from multiple data sources. Data Visualization: The graphic visualization of data. It can include traditional forms like graphs and charts, and modern forms like infographics. Data Warehouse: A relational database that integrates data from multiple sources within a company. Embedded Analytics: The integration of reporting and data analytic capabilities in a BI solution. Users can access full data analysis capabilities without having to leave their BI platform. Excel Hell: A situation where the enterprise is full of unnecessary copies of data, thousands of spreadsheets get shared, and no one knows with certainty which is the most updated and real version of the data. Federated Business Intelligence: A BI model where users work in separate desktops, creating data silos and unnecessary copies of data, leading to multiple versions of the truth. Geo-analytic capabilities: The ability that a BI or data discovery tool has to analyze data by geographical area and reflect such analysis on maps on the user’s dashboard. Infographics: Visual representations of data that are easily understandable and drive engagement.
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Business and Competitive Intelligence for Entrepreneurship Insights: According to Forrester Research, insights are “actionable knowledge in the context of a process or decision.” KPI: Key Performance Indicator. A quantifiable measure that a business uses to determine how well it meets the set operational and strategic goals. KPIs give managers insights of what is happening at any specific moment and allow them to see in what direction things are going. Modern BI: An approach to BI using state of the art technology, providing a centralized and secure platform where business users can enjoy self-service capabilities and IT can govern over data security. OLAP: Stands for Online Analytical Processing and it is a technology for data discovery invented by Panorama Software and then sold to Microsoft in 1996. It has many capabilities, such as complex analytics, predictive “what if” scenario planning, and limitless report viewing. Scalability: The ability of a BI solution to be used by a larger number of users as time passes. Self-Service BI: An approach that allows business users to access and work with data sources even though they do not have an analyst or computer science background. They can access, profile, prepare, integrate, curate, model, and enrich data for analysis and consumption by BI platforms. In order to have successful self-service BI, the BI tool must be centralized and governed by IT. Smart Data: Smaller data sets from Big Data that are valuable to the enterprise and can be turned into actionable data. Smart Data Discovery: The processing and analysis of Smart Data to discover insights that can be turned into actions to make data-driven decisions in an organization.
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Business and Competitive Intelligence for Entrepreneurship Social BI: An approach where social media capabilities, such as social networking, crowdsourcing, and thread-based discussions are embedded into Business Intelligence so that users can communicate and share insights. Social Enterprise: An enterprise that has a new level of corporate connectivity, leveraging the social grid to share and collaborate on information and ideas. It drives a more efficient operation where problems are uncovered and fixed before they can affect the revenue streams. SQL: Stands for Standardized Query Language. It is a language used in programming for managing relational databases and data manipulation. State of the Art BI: The highest level of technology, the most up-to date features, and the best analysis capabilities in a Business Intelligence solution. Suggestive Discovery Engine: An engine behind the program that recommends to the users the most relevant insights to focus on, based on personal preferences and behavior. Systems of Insight: This is a term coined by Boris Evelson, VP of Forrester Research. It is a Business Intelligence system that combines data availability with business agility, where both IT and business users work together to achieve their goals. Work boards: An interactive data visualization tool. It is like a dashboard that displays the current status of KPIs and other data analysis, with the possibility to work directly on it and do further analysis.
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Glossary of CI Terms Analysis: a critical evaluation, usually made by breaking down a subject (either material or intellectual) into its constituent parts, then describing the parts and their relationship to the whole. Benchmarking Analysis: a tool by which entrepreneurs can identify and examine key assets of a competitor and then implement what is learned into their own business venture/company, operations/etc. Business Model: the variety of activities an organization performs in order to create value, how and when it performs them. Business Model Analysis: a tool to quantify the relative strength of an enterprise’s business model. Competitive: in a business sense means that a contest is occurring between two or more parties. Competitive Analysis: the core of the intelligence process whereby meaning is derived from data about the competition. Competitive Intelligence (CI): the process by which companies (or entrepreneurs) gather information about competitors and the competitive environment, analyze it and ultimately apply it in the decision making process in order to improve their performance. Competitive Positioning Analysis: a technique conducted in order to understand enterprise’s strategic plans in relation to its current competitive position. Competitor Intelligence: collection and analysis of competitor data about the identity of specific competitors in the external environment. Competitor intelligence is about the knowledge of people. It is the gathering of information about the identity and activities of competitors.
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Business and Competitive Intelligence for Entrepreneurship Corporate Espionage: targets the highest level of secrets, intelligence, information, and proprietary subject matter to steal, obtain, gather, capture, and hide from detection at the executive level, especially of the President and CEO. Counter-intelligence (CTI): is the method designed to neutralize competitive intelligence systems and operations so as to prevent transfer of intelligence to the competition. Counterintelligence is for protection and prevention. Driving Forces: factors in a situation that cause things to remain as they are or to change; Driving Forces Analysis: a tool for drawing conclusions about major changes at industry level. Economic intelligence (EI): is an econometric analysis of economic systems, cycles, monetary and fiscal policy, and tracts resources and collects information about labor, capital, markets, natural resources, scarcity, production, distribution, logistics, consumption of goods, services, money, costs, underground, absolute advantage, competitive advantage, and trends in the micro- and macro-economic, and managerial economic environments. EI is the economic analysis that allows a nation to estimate the magnitude of possible military threats and is valuable in estimating the intentions of a potential enemy in wartime. (Total environment) Espionage: illegal activity of knowingly or unknowingly taking of secrets, confidential or proprietary information to injure or for advantage. In the economic environment espionage is the clandestine art of spying to find out secrets from government or corporate enemies, designated targets, or competitors. The activity of using espionage in such instance is an immoral act, illegal practice and a criminal offense under low.
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Business and Competitive Intelligence for Entrepreneurship Indications and Warnings Analysis: a tool for continuous generating of assumptions about the environment and rivals into the future in order to easily alert decision makers when the hostile market changes in a risky way. Intelligence: the ability to apply knowledge in order to manipulate one’s environment. A combination of abilities and skills that are within the mental age of a person. It is the ability to understand ideas and use knowledge. Intelligence Cycle: the formal process of gathering, analyzing and using information. Industrial Espionage: looks for high value secrets to obtain inside the manufacturing and production units of a rival corporation or a country. Knowledge Management Systems (KMS): is a structure for organizing information and its transformation, which is selected, collected, refined, shaped and distributed for management of that knowledge. Open sources: the vast quantity of information available can be accumulated from public sources. 95% of all information for intelligence gathering is available openly and classified as legal. It is the 5 % from closed access that is forbidden clandestine knowledge. Market Intelligence: is gathered through internal analysis, competition analysis, and market analysis about the total environment forming a broad spectrum of assembled knowledge, which is then used for developing scenarios so that timely reporting of vital foreknowledge for future planning and decisionmaking. It is defined as a complete and continuing awareness of all facets of a marketplace. It centers mainly on clients, rival companies, market trends, customer spending and suppliers. Marketing intelligence: is the collection and analysis of environmental scanning data in the marketing environment that helps managers (or entrepreneurs) to prepare and adjust marketing plans to monitor earlier decisions and future
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planning in the sales environment. MI is about the everyday information of what is happening surrounding marketing in the sales environment. It picks up where CI and marketing research leave off. Scenario analysis: a tool for developing multiple scenarios that will ultimately help executives during the decision making process. Shadowing: a technique through which entrepreneurs can monitor competitors and predict their next moves. Strategic intelligence (SI): is the long-range analysis of all environmental factors for forecasting and planning that might affect the marketing and business position of the organization. Strategic intelligence is the broad concept of intelligence for strategy, plans, and policy development. SWOT Analysis: the acronym for Strengths, Weaknesses, Opportunities and Threats. The strengths are represented by those internal capacities represented by the company's resources or its organizational capabilities to achieve a certain strategy. The company's weaknesses are those capacities that are likely to hinder the achievement of a certain strategic goal. In the analysis of opportunities and threats in the external environment we can use the model of Porter's five forces. According to this model, the five external forces to be considered are: level of competition, supply power, demand power, threat of substitutes and threats of new competitors. When all these factors have high values, the opportunities on that market are low and threats are high Technical Intelligence (TI): is to use the sources of science and industry prodigy from inventions and discoveries. TI is a body of specialized knowledge from the latest research that advances ability and performance.
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Team This Output has been created by a team from the 5 partner universities from the CIEN project. The experts from this team are: •
•
•
•
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From the Bucharest University of Economic Studies, Romania: o
Dr. Dorel Mihai Paraschiv, Prof.
o
Dr. Cătălin Ploae, Lecturer
o
Dr. Roxana Voicu-Dorobanțu, Assoc. Prof.
From the University of Varna, Bulgaria: o
Dr. Valentina Makni, Assoc. Prof.
o
Dr. Yuliyan Narlev, Assist. Prof.
o
Tsanko Ivanov, PhD Student.
From Ovidius University of Constanța, Romania: o
Dr. Cristina Duhnea, Assoc. Prof.
o
Dr. Andreea-Daniela Moraru
o
Dr. Silvia Ghita-Mitrescu
o
Dr. Constantin Ilie
o
Georgiana-Loredana Frecea, PhD. Student
From Aristotelio Panepistimio Thessaloniki, Greece: o
Dr. Niki Glaveli
o
Dr. Ozouni Eirini
From CNAM: o
Dr. Jean-Michel Raicovitch
Date: Bucharest, 28 February 2018
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References Chen, H., Chiang, R. H. L., Storey, V.C., 2012. BUSINESS INTELLIGENCE AND ANALYTICS: FROM BIG DATA TO BIG IMPACT, MIS Quarterly Vol. 36 No. 4, pp. 1165-1188 Chiang, R. H. L., Goes, P., and Stohr, E. A., 2012. Business intelligence and analytics education, and program development: A unique opportunity for the information systems discipline. ACM Trans. Manage. Inf. Syst. 3, 3, Article 12 (October 2012), 13 pages. Fleisher, Cr. and Bensoussan, B. (2015) Business and Competitive Analysis: Effective Application of New and Classic Methods. NJ: Pierson Education Ltd., 2nd Edition.
Gupta, B.; Goul, M.; & Dinter, B., 2015. "Business Intelligence and Big Data in Higher Education: Status of a Multi-Year Model Curriculum Development Effort for Business School Undergraduates, MS Graduates, and MBAs," Communications of the Association for Information Systems: Vol. 36, Article 23.
Grooms, T. (2016) Market intelligence: The original work. Amazon Distribution GmbH, Germany. Kuster, J. and Rouse, C., 2009. “A Business Intelligence Primer for Higher Education: Applying BI in hgher Education.”, http://www.b-eyenetwork.com/print/9704