Business Intelligence and Analytics in Small and Medium Enterprises:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Milton
Taylor & Francis Group
2019
|
| Schriftenreihe: | Manufacturing Design and Technology Ser
|
| Online-Zugang: | HWR01 |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 online resource (166 pages) |
| ISBN: | 9780429508745 |
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| 505 | 8 | |a Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Editors Biographies -- List of Contributors -- Chapter 1: Process Mining - Prerequisites and Their Applicability for Small and Mediumsized Enterprises -- CONTENTS -- 1.1. Introduction -- 1.2. What is Process Mining? -- 1.3. Prerequisites for Successful Process Mining -- 1.3.1. Organizational Prerequisites -- 1.3.2. Process-Related Prerequisites -- 1.3.3. IT-Related Prerequisites -- 1.3.4. Data-Related Prerequisites -- 1.3.5. Employee-Related Prerequisites -- 1.3.6. Legal Requirements -- 1.3.7. Means and Resources -- 1.4. Process Mining in SME - Two Case Studies -- 1.4.1. Is Process Mining a Suitable Technology for SMEs? -- 1.4.2. Are the Seven Identified Prerequisites for Process Mining Being Fulfilled in the Respective SME? -- 1.5. Concluding Remarks -- Notes -- References -- Chapter 2: Using Customer Analytics to Succeed: The Case of Mexican SMEs -- CONTENTS -- 2.1. Introduction -- 2.2. Business Intelligence and Analytics in SMEs -- 2.3. Small and Medium Enterprises in Mexico -- 2.4. Social Media Analytics Tools for Customer Engagement in Mexican SMEs -- 2.5. Digital Recommendation for SMEs: A Framework for Customer Analytics on Social Media -- 2.6. Challenges and Opportunities -- References -- Chapter 3: Data Management Software Solutions for Business Sustainability - An Overview -- CONTENTS -- 3.1. Introduction -- 3.2. Materials and Methods -- 3.3. Result and Discussions -- 3.3.1. DG, DM, and MDM Software Solutions -- 3.3.2. The Study Regarding the Use of Data Management Software Solutions by Romanian Companies -- 3.4. Conclusions -- References -- Chapter 4: A Paradigm Shift in Accounting and Auditing of Big Data -- CONTENTS -- 4.1. Introduction -- 4.2. Business Intelligence, Analytics and Big Data | |
| 505 | 8 | |a 4.3. The Opportunities of Big Data Analytics for the Accounting and Auditing Professions -- 4.4. The Case of SMEs -- 4.5. The Impact on Accounting Education -- 4.6. Conclusion -- Note -- References -- Chapter 5: Mobile Advertising Framework: Format, Location and Context -- CONTENTS -- 5.1. Introduction -- 5.2. Research Method -- 5.3. Findings -- 5.3.1. Location-Based Advertising (LBA) -- 5.3.2. SMS -- 5.3.3. In-app Advertising -- 5.3.4. Mobile Social Media and Search Engine Advertising -- 5.3.4.1. Mobile Search Engine Advertising -- 5.4. Privacy and Application of GDPR -- 5.5. Theoretical Implications -- 5.6. Practical Implications -- 5.7. Limitations and Future Research Directions -- 5.8. Conclusion -- References -- Chapter 6: Marketing Analytics: Why Measuring Web and Social Media Matters -- CONTENTS -- 6.1. Introduction: What You Can't Measure, Doesn't Exist -- 6.2. Setting Objectives and Kpis: The Smart Rule -- 6.3. Funnel Analytics: Conversion Funnel -- 6.4. Measuring -- 6.4.1. Web: Main Metrics with Web Analytics: Segments, Filters -- 6.4.1.1. e-Commerce Websites -- 6.4.2. Social Media: Main Metrics on Facebook, Twitter or Instagram -- 6.4.3. Newsletters -- 6.4.4. Mobile Apps -- 6.5. Analyzing and Reporting: What a Web Analytics and Social Media Report Should Analyze -- 6.6. Where Should the Efforts of Small and Medium Size Enterprises be Invested -- References -- Chapter 7: Managers' Perception of Business Intelligence Capability of SMEs in Turkey -- CONTENTS -- 7.1. Introduction -- 7.2. Need for Business Intelligence -- 7.3. The Future of Business Intelligence -- 7.4. The Challenges for Business Intelligence Practitioners -- 7.5. SME and BI Usage in Turkey -- 7.5.1. Research on Business Intelligence Adoption of SMEs in Turkey -- 7.6. Conclusion and Discussion -- References -- Chapter 8: The Development of Loyalty Programs in the Retail Sector | |
| 505 | 8 | |a CONTENTS -- 8.1. Introduction -- 8.2. Literature Review -- 8.2.1. Loyalty Programs -- 8.2.2. Traditional Loyalty Programs -- 8.2.3. Loyalty Programs and its Technology Use -- 8.3. The Loyalty Program Lifecycle: Design, Implementation and Assessment -- 8.3.1. The Design Stage -- 8.3.2. The Implementation Stage -- 8.3.2.1. Communication -- 8.3.2.2. Communication Style -- 8.3.3. Firm-Created Communication -- 8.3.4. Customer-Created Communication -- 8.3.4.1. Customer Support -- 8.3.4.2. Privacy Matters -- 8.3.4.3. Location Based Services -- 8.3.4.4. Automation and Efficiency -- 8.3.5. The Performance Assessment Stage -- 8.4. Discussion -- References -- Chapter 9: Business Intelligence, Big Data and Data Governance -- CONTENTS -- 9.1. Introduction -- 9.2. From Business Intelligence to Big Data and Data Science -- 9.2.1. Evolution and Applications -- 9.2.2. Challenges -- 9.3. Business Intelligence Maturity Assessment -- 9.3.1. Maturity Assessment -- 9.3.2. Maturity Assessment and Business Intelligence -- 9.3.3. Data Governance, BI Maturity Model and Small Business -- 9.4. Data Governance -- 9.4.1. Data Governance Maturity Assessment -- 9.4.2. Data Governance Program Approach -- 9.4.3. Tools -- 9.4.4. Data Governance Program Progress and Impact Analysis -- 9.5. Conclusions -- References -- Index | |
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| contents | Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Editors Biographies -- List of Contributors -- Chapter 1: Process Mining - Prerequisites and Their Applicability for Small and Mediumsized Enterprises -- CONTENTS -- 1.1. Introduction -- 1.2. What is Process Mining? -- 1.3. Prerequisites for Successful Process Mining -- 1.3.1. Organizational Prerequisites -- 1.3.2. Process-Related Prerequisites -- 1.3.3. IT-Related Prerequisites -- 1.3.4. Data-Related Prerequisites -- 1.3.5. Employee-Related Prerequisites -- 1.3.6. Legal Requirements -- 1.3.7. Means and Resources -- 1.4. Process Mining in SME - Two Case Studies -- 1.4.1. Is Process Mining a Suitable Technology for SMEs? -- 1.4.2. Are the Seven Identified Prerequisites for Process Mining Being Fulfilled in the Respective SME? -- 1.5. Concluding Remarks -- Notes -- References -- Chapter 2: Using Customer Analytics to Succeed: The Case of Mexican SMEs -- CONTENTS -- 2.1. Introduction -- 2.2. Business Intelligence and Analytics in SMEs -- 2.3. Small and Medium Enterprises in Mexico -- 2.4. Social Media Analytics Tools for Customer Engagement in Mexican SMEs -- 2.5. Digital Recommendation for SMEs: A Framework for Customer Analytics on Social Media -- 2.6. Challenges and Opportunities -- References -- Chapter 3: Data Management Software Solutions for Business Sustainability - An Overview -- CONTENTS -- 3.1. Introduction -- 3.2. Materials and Methods -- 3.3. Result and Discussions -- 3.3.1. DG, DM, and MDM Software Solutions -- 3.3.2. The Study Regarding the Use of Data Management Software Solutions by Romanian Companies -- 3.4. Conclusions -- References -- Chapter 4: A Paradigm Shift in Accounting and Auditing of Big Data -- CONTENTS -- 4.1. Introduction -- 4.2. Business Intelligence, Analytics and Big Data 4.3. The Opportunities of Big Data Analytics for the Accounting and Auditing Professions -- 4.4. The Case of SMEs -- 4.5. The Impact on Accounting Education -- 4.6. Conclusion -- Note -- References -- Chapter 5: Mobile Advertising Framework: Format, Location and Context -- CONTENTS -- 5.1. Introduction -- 5.2. Research Method -- 5.3. Findings -- 5.3.1. Location-Based Advertising (LBA) -- 5.3.2. SMS -- 5.3.3. In-app Advertising -- 5.3.4. Mobile Social Media and Search Engine Advertising -- 5.3.4.1. Mobile Search Engine Advertising -- 5.4. Privacy and Application of GDPR -- 5.5. Theoretical Implications -- 5.6. Practical Implications -- 5.7. Limitations and Future Research Directions -- 5.8. Conclusion -- References -- Chapter 6: Marketing Analytics: Why Measuring Web and Social Media Matters -- CONTENTS -- 6.1. Introduction: What You Can't Measure, Doesn't Exist -- 6.2. Setting Objectives and Kpis: The Smart Rule -- 6.3. Funnel Analytics: Conversion Funnel -- 6.4. Measuring -- 6.4.1. Web: Main Metrics with Web Analytics: Segments, Filters -- 6.4.1.1. e-Commerce Websites -- 6.4.2. Social Media: Main Metrics on Facebook, Twitter or Instagram -- 6.4.3. Newsletters -- 6.4.4. Mobile Apps -- 6.5. Analyzing and Reporting: What a Web Analytics and Social Media Report Should Analyze -- 6.6. Where Should the Efforts of Small and Medium Size Enterprises be Invested -- References -- Chapter 7: Managers' Perception of Business Intelligence Capability of SMEs in Turkey -- CONTENTS -- 7.1. Introduction -- 7.2. Need for Business Intelligence -- 7.3. The Future of Business Intelligence -- 7.4. The Challenges for Business Intelligence Practitioners -- 7.5. SME and BI Usage in Turkey -- 7.5.1. Research on Business Intelligence Adoption of SMEs in Turkey -- 7.6. Conclusion and Discussion -- References -- Chapter 8: The Development of Loyalty Programs in the Retail Sector CONTENTS -- 8.1. Introduction -- 8.2. Literature Review -- 8.2.1. Loyalty Programs -- 8.2.2. Traditional Loyalty Programs -- 8.2.3. Loyalty Programs and its Technology Use -- 8.3. The Loyalty Program Lifecycle: Design, Implementation and Assessment -- 8.3.1. The Design Stage -- 8.3.2. The Implementation Stage -- 8.3.2.1. Communication -- 8.3.2.2. Communication Style -- 8.3.3. Firm-Created Communication -- 8.3.4. Customer-Created Communication -- 8.3.4.1. Customer Support -- 8.3.4.2. Privacy Matters -- 8.3.4.3. Location Based Services -- 8.3.4.4. Automation and Efficiency -- 8.3.5. The Performance Assessment Stage -- 8.4. Discussion -- References -- Chapter 9: Business Intelligence, Big Data and Data Governance -- CONTENTS -- 9.1. Introduction -- 9.2. From Business Intelligence to Big Data and Data Science -- 9.2.1. Evolution and Applications -- 9.2.2. Challenges -- 9.3. Business Intelligence Maturity Assessment -- 9.3.1. Maturity Assessment -- 9.3.2. Maturity Assessment and Business Intelligence -- 9.3.3. Data Governance, BI Maturity Model and Small Business -- 9.4. Data Governance -- 9.4.1. Data Governance Maturity Assessment -- 9.4.2. Data Governance Program Approach -- 9.4.3. Tools -- 9.4.4. Data Governance Program Progress and Impact Analysis -- 9.5. Conclusions -- References -- Index |
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| id | DE-604.BV047687746 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T18:57:00Z |
| indexdate | 2024-07-10T09:19:14Z |
| institution | BVB |
| isbn | 9780429508745 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033071762 |
| oclc_num | 1129206670 |
| open_access_boolean | |
| owner | DE-2070s |
| owner_facet | DE-2070s |
| physical | 1 online resource (166 pages) |
| psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
| publishDate | 2019 |
| publishDateSearch | 2019 |
| publishDateSort | 2019 |
| publisher | Taylor & Francis Group |
| record_format | marc |
| series2 | Manufacturing Design and Technology Ser |
| spelling | Melo, Pedro Novo Verfasser aut Business Intelligence and Analytics in Small and Medium Enterprises Milton Taylor & Francis Group 2019 ©2021 1 online resource (166 pages) txt rdacontent c rdamedia cr rdacarrier Manufacturing Design and Technology Ser Description based on publisher supplied metadata and other sources Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Editors Biographies -- List of Contributors -- Chapter 1: Process Mining - Prerequisites and Their Applicability for Small and Mediumsized Enterprises -- CONTENTS -- 1.1. Introduction -- 1.2. What is Process Mining? -- 1.3. Prerequisites for Successful Process Mining -- 1.3.1. Organizational Prerequisites -- 1.3.2. Process-Related Prerequisites -- 1.3.3. IT-Related Prerequisites -- 1.3.4. Data-Related Prerequisites -- 1.3.5. Employee-Related Prerequisites -- 1.3.6. Legal Requirements -- 1.3.7. Means and Resources -- 1.4. Process Mining in SME - Two Case Studies -- 1.4.1. Is Process Mining a Suitable Technology for SMEs? -- 1.4.2. Are the Seven Identified Prerequisites for Process Mining Being Fulfilled in the Respective SME? -- 1.5. Concluding Remarks -- Notes -- References -- Chapter 2: Using Customer Analytics to Succeed: The Case of Mexican SMEs -- CONTENTS -- 2.1. Introduction -- 2.2. Business Intelligence and Analytics in SMEs -- 2.3. Small and Medium Enterprises in Mexico -- 2.4. Social Media Analytics Tools for Customer Engagement in Mexican SMEs -- 2.5. Digital Recommendation for SMEs: A Framework for Customer Analytics on Social Media -- 2.6. Challenges and Opportunities -- References -- Chapter 3: Data Management Software Solutions for Business Sustainability - An Overview -- CONTENTS -- 3.1. Introduction -- 3.2. Materials and Methods -- 3.3. Result and Discussions -- 3.3.1. DG, DM, and MDM Software Solutions -- 3.3.2. The Study Regarding the Use of Data Management Software Solutions by Romanian Companies -- 3.4. Conclusions -- References -- Chapter 4: A Paradigm Shift in Accounting and Auditing of Big Data -- CONTENTS -- 4.1. Introduction -- 4.2. Business Intelligence, Analytics and Big Data 4.3. The Opportunities of Big Data Analytics for the Accounting and Auditing Professions -- 4.4. The Case of SMEs -- 4.5. The Impact on Accounting Education -- 4.6. Conclusion -- Note -- References -- Chapter 5: Mobile Advertising Framework: Format, Location and Context -- CONTENTS -- 5.1. Introduction -- 5.2. Research Method -- 5.3. Findings -- 5.3.1. Location-Based Advertising (LBA) -- 5.3.2. SMS -- 5.3.3. In-app Advertising -- 5.3.4. Mobile Social Media and Search Engine Advertising -- 5.3.4.1. Mobile Search Engine Advertising -- 5.4. Privacy and Application of GDPR -- 5.5. Theoretical Implications -- 5.6. Practical Implications -- 5.7. Limitations and Future Research Directions -- 5.8. Conclusion -- References -- Chapter 6: Marketing Analytics: Why Measuring Web and Social Media Matters -- CONTENTS -- 6.1. Introduction: What You Can't Measure, Doesn't Exist -- 6.2. Setting Objectives and Kpis: The Smart Rule -- 6.3. Funnel Analytics: Conversion Funnel -- 6.4. Measuring -- 6.4.1. Web: Main Metrics with Web Analytics: Segments, Filters -- 6.4.1.1. e-Commerce Websites -- 6.4.2. Social Media: Main Metrics on Facebook, Twitter or Instagram -- 6.4.3. Newsletters -- 6.4.4. Mobile Apps -- 6.5. Analyzing and Reporting: What a Web Analytics and Social Media Report Should Analyze -- 6.6. Where Should the Efforts of Small and Medium Size Enterprises be Invested -- References -- Chapter 7: Managers' Perception of Business Intelligence Capability of SMEs in Turkey -- CONTENTS -- 7.1. Introduction -- 7.2. Need for Business Intelligence -- 7.3. The Future of Business Intelligence -- 7.4. The Challenges for Business Intelligence Practitioners -- 7.5. SME and BI Usage in Turkey -- 7.5.1. Research on Business Intelligence Adoption of SMEs in Turkey -- 7.6. Conclusion and Discussion -- References -- Chapter 8: The Development of Loyalty Programs in the Retail Sector CONTENTS -- 8.1. Introduction -- 8.2. Literature Review -- 8.2.1. Loyalty Programs -- 8.2.2. Traditional Loyalty Programs -- 8.2.3. Loyalty Programs and its Technology Use -- 8.3. The Loyalty Program Lifecycle: Design, Implementation and Assessment -- 8.3.1. The Design Stage -- 8.3.2. The Implementation Stage -- 8.3.2.1. Communication -- 8.3.2.2. Communication Style -- 8.3.3. Firm-Created Communication -- 8.3.4. Customer-Created Communication -- 8.3.4.1. Customer Support -- 8.3.4.2. Privacy Matters -- 8.3.4.3. Location Based Services -- 8.3.4.4. Automation and Efficiency -- 8.3.5. The Performance Assessment Stage -- 8.4. Discussion -- References -- Chapter 9: Business Intelligence, Big Data and Data Governance -- CONTENTS -- 9.1. Introduction -- 9.2. From Business Intelligence to Big Data and Data Science -- 9.2.1. Evolution and Applications -- 9.2.2. Challenges -- 9.3. Business Intelligence Maturity Assessment -- 9.3.1. Maturity Assessment -- 9.3.2. Maturity Assessment and Business Intelligence -- 9.3.3. Data Governance, BI Maturity Model and Small Business -- 9.4. Data Governance -- 9.4.1. Data Governance Maturity Assessment -- 9.4.2. Data Governance Program Approach -- 9.4.3. Tools -- 9.4.4. Data Governance Program Progress and Impact Analysis -- 9.5. Conclusions -- References -- Index Machado, Carolina Sonstige oth Erscheint auch als Druck-Ausgabe Melo, Pedro Novo Business Intelligence and Analytics in Small and Medium Enterprises Milton : Taylor & Francis Group,c2019 9780367173883 |
| spellingShingle | Melo, Pedro Novo Business Intelligence and Analytics in Small and Medium Enterprises Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Editors Biographies -- List of Contributors -- Chapter 1: Process Mining - Prerequisites and Their Applicability for Small and Mediumsized Enterprises -- CONTENTS -- 1.1. Introduction -- 1.2. What is Process Mining? -- 1.3. Prerequisites for Successful Process Mining -- 1.3.1. Organizational Prerequisites -- 1.3.2. Process-Related Prerequisites -- 1.3.3. IT-Related Prerequisites -- 1.3.4. Data-Related Prerequisites -- 1.3.5. Employee-Related Prerequisites -- 1.3.6. Legal Requirements -- 1.3.7. Means and Resources -- 1.4. Process Mining in SME - Two Case Studies -- 1.4.1. Is Process Mining a Suitable Technology for SMEs? -- 1.4.2. Are the Seven Identified Prerequisites for Process Mining Being Fulfilled in the Respective SME? -- 1.5. Concluding Remarks -- Notes -- References -- Chapter 2: Using Customer Analytics to Succeed: The Case of Mexican SMEs -- CONTENTS -- 2.1. Introduction -- 2.2. Business Intelligence and Analytics in SMEs -- 2.3. Small and Medium Enterprises in Mexico -- 2.4. Social Media Analytics Tools for Customer Engagement in Mexican SMEs -- 2.5. Digital Recommendation for SMEs: A Framework for Customer Analytics on Social Media -- 2.6. Challenges and Opportunities -- References -- Chapter 3: Data Management Software Solutions for Business Sustainability - An Overview -- CONTENTS -- 3.1. Introduction -- 3.2. Materials and Methods -- 3.3. Result and Discussions -- 3.3.1. DG, DM, and MDM Software Solutions -- 3.3.2. The Study Regarding the Use of Data Management Software Solutions by Romanian Companies -- 3.4. Conclusions -- References -- Chapter 4: A Paradigm Shift in Accounting and Auditing of Big Data -- CONTENTS -- 4.1. Introduction -- 4.2. Business Intelligence, Analytics and Big Data 4.3. The Opportunities of Big Data Analytics for the Accounting and Auditing Professions -- 4.4. The Case of SMEs -- 4.5. The Impact on Accounting Education -- 4.6. Conclusion -- Note -- References -- Chapter 5: Mobile Advertising Framework: Format, Location and Context -- CONTENTS -- 5.1. Introduction -- 5.2. Research Method -- 5.3. Findings -- 5.3.1. Location-Based Advertising (LBA) -- 5.3.2. SMS -- 5.3.3. In-app Advertising -- 5.3.4. Mobile Social Media and Search Engine Advertising -- 5.3.4.1. Mobile Search Engine Advertising -- 5.4. Privacy and Application of GDPR -- 5.5. Theoretical Implications -- 5.6. Practical Implications -- 5.7. Limitations and Future Research Directions -- 5.8. Conclusion -- References -- Chapter 6: Marketing Analytics: Why Measuring Web and Social Media Matters -- CONTENTS -- 6.1. Introduction: What You Can't Measure, Doesn't Exist -- 6.2. Setting Objectives and Kpis: The Smart Rule -- 6.3. Funnel Analytics: Conversion Funnel -- 6.4. Measuring -- 6.4.1. Web: Main Metrics with Web Analytics: Segments, Filters -- 6.4.1.1. e-Commerce Websites -- 6.4.2. Social Media: Main Metrics on Facebook, Twitter or Instagram -- 6.4.3. Newsletters -- 6.4.4. Mobile Apps -- 6.5. Analyzing and Reporting: What a Web Analytics and Social Media Report Should Analyze -- 6.6. Where Should the Efforts of Small and Medium Size Enterprises be Invested -- References -- Chapter 7: Managers' Perception of Business Intelligence Capability of SMEs in Turkey -- CONTENTS -- 7.1. Introduction -- 7.2. Need for Business Intelligence -- 7.3. The Future of Business Intelligence -- 7.4. The Challenges for Business Intelligence Practitioners -- 7.5. SME and BI Usage in Turkey -- 7.5.1. Research on Business Intelligence Adoption of SMEs in Turkey -- 7.6. Conclusion and Discussion -- References -- Chapter 8: The Development of Loyalty Programs in the Retail Sector CONTENTS -- 8.1. Introduction -- 8.2. Literature Review -- 8.2.1. Loyalty Programs -- 8.2.2. Traditional Loyalty Programs -- 8.2.3. Loyalty Programs and its Technology Use -- 8.3. The Loyalty Program Lifecycle: Design, Implementation and Assessment -- 8.3.1. The Design Stage -- 8.3.2. The Implementation Stage -- 8.3.2.1. Communication -- 8.3.2.2. Communication Style -- 8.3.3. Firm-Created Communication -- 8.3.4. Customer-Created Communication -- 8.3.4.1. Customer Support -- 8.3.4.2. Privacy Matters -- 8.3.4.3. Location Based Services -- 8.3.4.4. Automation and Efficiency -- 8.3.5. The Performance Assessment Stage -- 8.4. Discussion -- References -- Chapter 9: Business Intelligence, Big Data and Data Governance -- CONTENTS -- 9.1. Introduction -- 9.2. From Business Intelligence to Big Data and Data Science -- 9.2.1. Evolution and Applications -- 9.2.2. Challenges -- 9.3. Business Intelligence Maturity Assessment -- 9.3.1. Maturity Assessment -- 9.3.2. Maturity Assessment and Business Intelligence -- 9.3.3. Data Governance, BI Maturity Model and Small Business -- 9.4. Data Governance -- 9.4.1. Data Governance Maturity Assessment -- 9.4.2. Data Governance Program Approach -- 9.4.3. Tools -- 9.4.4. Data Governance Program Progress and Impact Analysis -- 9.5. Conclusions -- References -- Index |
| title | Business Intelligence and Analytics in Small and Medium Enterprises |
| title_auth | Business Intelligence and Analytics in Small and Medium Enterprises |
| title_exact_search | Business Intelligence and Analytics in Small and Medium Enterprises |
| title_exact_search_txtP | Business Intelligence and Analytics in Small and Medium Enterprises |
| title_full | Business Intelligence and Analytics in Small and Medium Enterprises |
| title_fullStr | Business Intelligence and Analytics in Small and Medium Enterprises |
| title_full_unstemmed | Business Intelligence and Analytics in Small and Medium Enterprises |
| title_short | Business Intelligence and Analytics in Small and Medium Enterprises |
| title_sort | business intelligence and analytics in small and medium enterprises |
| work_keys_str_mv | AT melopedronovo businessintelligenceandanalyticsinsmallandmediumenterprises AT machadocarolina businessintelligenceandanalyticsinsmallandmediumenterprises |