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978-1-4842-2568-4 |
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20210619065325.0 |
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170526s2017 xxu| s |||| 0|eng d |
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|a 9781484225684
|9 978-1-4842-2568-4
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|a 10.1007/978-1-4842-2568-4
|2 doi
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|a QA76.76.O62
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|a QA76.6-76.66
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|a 006.76
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|a Nogués, Albert.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Business Intelligence Tools for Small Companies
|h [electronic resource] :
|b A Guide to Free and Low-Cost Solutions /
|c by Albert Nogués, Juan Valladares.
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| 250 |
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|a 1st ed. 2017.
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|a Berkeley, CA :
|b Apress :
|b Imprint: Apress,
|c 2017.
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| 300 |
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|a XXIII, 326 p. 168 illus., 163 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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|a Chapter 1: Business Intelligence for Everybody -- Chapter 2: Agile Methodologies for BI Projects -- Chapter 3: SQL Basics -- Chapter 4: Project Initialization - Database and Source ERP Installation -- Chapter 5: Data Modeling for BI Solutions -- Chapter 6: ELT Basics -- Chapter 7: Performance Improvements -- Chapter 8: The BI Reporting Interface -- Chapter 9: MOLAP Tools for Budgeting -- Chapter 10: BI Process Scheduling: How to Orchestrate and Update Running Processes -- Chapter 11: Moving to a Production Environment -- Chapter 12: Moving BI Processes to the Cloud -- Chapter 13: Conclusions and Next Steps.
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|a Learn how to transition from Excel-based business intelligence (BI) analysis to enterprise stacks of open-source BI tools. Select and implement the best free and freemium open-source BI tools for your company’s needs and design, implement, and integrate BI automation across the full stack using agile methodologies. Business Intelligence Tools for Small Companies provides hands-on demonstrations of open-source tools suitable for the BI requirements of small businesses. The authors draw on their deep experience as BI consultants, developers, and administrators to guide you through the extract-transform-load/data warehousing (ETL/DWH) sequence of extracting data from an enterprise resource planning (ERP) database freely available on the Internet, transforming the data, manipulating them, and loading them into a relational database. The authors demonstrate how to extract, report, and dashboard key performance indicators (KPIs) in a visually appealing format from the relational database management system (RDBMS). They model the selection and implementation of free and freemium tools such as Pentaho Data Integrator and Talend for ELT, Oracle XE and MySQL/MariaDB for RDBMS, and Qliksense, Power BI, and MicroStrategy Desktop for reporting. This richly illustrated guide models the deployment of a small company BI stack on an inexpensive cloud platform such as AWS. You will learn how to manage, integrate, and automate the processes of BI by selecting and implementing tools to: Implement and manage the business intelligence/data warehousing (BI/DWH) infrastructure Extract data from any enterprise resource planning (ERP) tool Process and integrate BI data using open-source extract-transform-load (ETL) tools Query, report, and analyze BI data using open-source visualization and dashboard tools Use a MOLAP tool to define next year's budget, integrating real data with target scenarios Deploy BI solutions and big data experiments inexpensively on cloud platforms.
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|a Open source software.
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|a Computer programming.
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|a Database management.
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|a Information storage and retrieval.
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|a Big data.
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|a Open Source.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I29090
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| 650 |
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|a Database Management.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I18024
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| 650 |
2 |
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|a Information Storage and Retrieval.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I18032
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| 650 |
2 |
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|a Big Data/Analytics.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/522070
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| 700 |
1 |
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|a Valladares, Juan.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer Nature eBook
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| 776 |
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8 |
|i Printed edition:
|z 9781484225677
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| 776 |
0 |
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|i Printed edition:
|z 9781484225691
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| 856 |
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|u https://doi.org/10.1007/978-1-4842-2568-4
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| 912 |
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|a ZDB-2-CWD
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| 912 |
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|a ZDB-2-SXPC
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| 950 |
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|a Professional and Applied Computing (SpringerNature-12059)
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| 950 |
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|a Professional and Applied Computing (R0) (SpringerNature-43716)
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