Using Open Source Platforms for Business Intelligence: Avoid Pitfalls and Maximize Roi
by Lyndsay Wise · 16 Sep 2012 · 227pp · 32,306 words
......................................................................................................... 3 Why is there a need for this book? ............................................................................ 3 What to expect in this book........................................................................................ 4 An introduction to BI.................................................................................................. 6 The components of business intelligence ................................................................... 9 CHAPTER 2 OS overview ........................................................................................................... 13 Why understanding OS matters ................................................................................ 13 A historical look at the broader OS market ............................................................. 14 The general appeal of OS
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a need for this book? Many books exist that identify how to get the most out of analytics or how to develop an open source business intelligence (OSBI) solution based on specific development or solution requirements. The reality is that even though these books provide value within the niche they address,
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going over budget are all signs of mismanagement, a lack of processes and best practices, and a misunderstanding of the requirements and end goal. Unfortunately, business intelligence (BI) is no different. And adding open source (OS) to the mix doesn’t make things easier. In many cases, it is the opposite
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business. Either way, knowledge is power, and this knowledge has not existed in a cohesive guide to help business decision makers make sense out of business intelligence, OS, its overlaps, and how to make the right decision for the 1 Project Management Solutions, http://www.pmsolutions.com/collateral/research/Strategies%20for%20Project
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%20Recovery %202011.pdf 2 Geneca, http://calleam.com/WTPF/?page_id 5 1445 Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 3 4 CHAPTER 1 Introducing BI organization as a whole. In the past, OS was a tool used by
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them by creating better visibility and higher productivity. As an industry analyst and consultant working primarily with small and mid-sized businesses looking at implementing business intelligence solutions, I continue to see collaboration among c-level executives and IT directors when making technology and specifically, BI decisions. Because many IT developers like
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software costs. Nowhere does the adage “free as in a puppy and not as in free beer” apply more directly than within a BI project. Business intelligence requires many separate components to make it work. Knowing how to put these together and understanding all of the areas where OS offerings may fit
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software offset by development efforts and long-term maintenance? Is OSBI more strategic than traditional BI offerings? And how does OSBI differ from the broader business intelligence market landscape? All of these questions will be addressed while guiding you through the process of what it takes to successfully start and complete your
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realm of BI adoption. Because OS represents a niche area within the broader BI market, what it has to offer organizations is different from other business intelligence offerings. In addition, we will look at the increase in OS popularity and how it affects the BI market specifically and what it means for
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) and by looking at ROI and TCO models that apply. This involves taking a step back and looking at what constitutes ROI and TCO within business intelligence projects and how they differ with OS specifically. This includes comparing options and looking at some of the differences in cost, internal resources required, and
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this data from disparate data sources leads to gained insights that are needed in order to remain competitive within a constantly changing competitive landscape. Enter business intelligence. Figure 1-1 will provide an overview of how BI enables organizations to consolidate data from various sources, manage both data quality and business processes
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data warehouse with separate data marts4 to address the needs of individual departments or reporting requirements, whereas Ralph Kimball,5 known as the father of business intelligence, believed in the opposite approach in essence, the importance of building individual data marts that reside within a broader data warehouse infrastructure.6 Over time
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enables both technical and business decision makers to make the right choices for their company. BI Delivery Type Breakdown. BI Type Definition Solution Parameters Traditional Business intelligence is installed and developed at the customer site, with the general purpose of reporting and analytics using historical data sets. Software as a Service BI
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. To identify which option best meets your needs, you might want to start with an online search with parameters “ELT vs. ETL.” The components of business intelligence Data Warehouse Entry #1 Sales Product Customer Retail Location Sales Rep Supply Chain 11 Data Warehouse Entry #2 Product ID Prod Desc Customer # Number of
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they have selected their BI solution because a former colleague of theirs or one of their friends working for another Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 13 14 CHAPTER 2 OS overview organization implemented X solution. Although most BI offerings can be broadly applied within
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://www.opensourceconference.nl/771, http://www.opensourceworldconference.com/en, with others being specific to universities, types of OS applications, etc. Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 21 22 CHAPTER 3 The convergence of OS and BI the dark about OS outside of knowing the name
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a broader understanding of what is available and how it can be applied within the organization. Overall, the best way Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 31 32 CHAPTER 4 A look at the OSBI market to do this in relation to OSBI offerings
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/02/gartner-study-showsbi-importance.html, with the actual report being found at: http://www.gartner.com/id=1901814. 2 Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 45 46 CHAPTER 5 The increasing popularity of OS in the way it was originally intended. In essence, they
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of new capabilities or bug fix efforts and target their development efforts based on the projects they are working on. Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 55 56 CHAPTER 6 The differences between general OS and commercial offerings SpagoBI, an Italian-based OSBI provider, actually
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in the way BI is managed. It is no longer enough to provide a value assessment of technology, infrastructure, or Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 65 66 CHAPTER 7 Business benefits and challenges of OS for BI what a solution can do. Organizations are
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the data without all of these data joins and additional preparation, these tasks are still required to develop strategic queries. Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 79 80 CHAPTER 8 The strategy behind BI adoption The bottom line is that to get the most out
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them, they were only at the testing phase of Pentaho so our conversation focused on Vectorwise and data warehouse development. Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 89 90 CHAPTER 9 Implications for users Even though NK provides a good example of identifying the convergence of
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or not, BI projects involve risk. Granted, all IT-related projects and software implementations do, but it’s important to Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 101 102 CHAPTER 10 Selling an OSBI project to the business be cognizant of this fact to try to
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to the point that one industry-defined calculation will not suit the needs of all businesses. But, the benefit of Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 117 118 CHAPTER 11 Evaluating ROI and TCO these calculators is that they do provide a basis for
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://www.businessdictionary.com/definition/total-cost-of-ownership-TCO.html and http://www.interimtechexec.com/ blog/roi-for-enterprise-software/. 3 Lowering the Cost of Business Intelligence With Open Source: A Comparison of Open Source and Traditional Vendor Costs Mark Madsen, Third Nature, Prepared for Pentaho, 2010. 2 Total cost of ownership
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offerings are minimizing these differences and potential barriers to entry, but OSBI still has the benefit of no-cost software. 4 Lowering the Cost of Business Intelligence With Open Source: A Comparison of Open Source and Traditional Vendor Costs Mark Madsen, Third Nature, Prepared for Pentaho, page 4. 122 CHAPTER 11 Evaluating
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use them as is. Within the next several pages, we will look at how three consultancy/analyst firms evaluate ROI Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 129 130 CHAPTER 12 Developing a cost-benefit analysis for OSBI for BI. All of these models are
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embarking on a BI project. The first was developed by TDWI1 (The Data Warehouse Institute), in collaboration with Hall Consulting & Research LLC2. Called the TDWI Business Intelligence ROI Calculator,3 its goal is to help organizations with their BI evaluation. Figure 12-1 identifies the aspects involved in ROI. This calculator looks
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, these KPI changes are not converted into financial benefits Business Management Effectiveness Sales/Marketing Performance Supply/Operations Performance Financial Management Effectiveness FIGURE 12-1 TDWI Business Intelligence ROI Calculator Model Components/Flowchart. 1 http://tdwi.org/ http://hallcr.com/ 3 http://hallcr.com/BI.aspx developed by Hall Consulting & Research LLC (hallcr
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the business unit, this may enable broader implementation due to the ability to allocate costs to the appropriate departments. Nucleus Research has also developed a Business Intelligence ROI Tool (Figure 12-4) that provides a survey to help guide users through the ROI evaluation process. Factors considered include Net Present Value (NPV
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in year 2 0 0 0 Enter # Shares Here Impact in year 3 0 0 0 Impact on earnings per share FIGURE 12-2 TDWI Business Intelligence ROI Calculator Total Cost Summary (Including Labor). applying overall calculations. For companies looking for a quick way to evaluate the benefits of BI, selecting
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BI Applications IT Labor Client Software Server Software Server Hardware Storage Hardware $436 $500 $384 $0 $89 $28 5-Year Total FIGURE 12-3 TDWI Business Intelligence ROI Calculator Total Implementation (Cost per User). • • How do internal development efforts offset software costs, and do they offset enough to justify community OSBI offerings
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a developer. For the more technical audience, looking at these considerations in a different light might help with the process Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 143 144 CHAPTER 13 A look at technical considerations of collaboration required between business units and IT on a
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of data and developing a framework to gain valuable insights out of information requires in-depth knowledge irrespective of platform. Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 155 156 CHAPTER 14 Understanding integration and data preparation This chapter looks at the components of BI in relation
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, so it is not a step-by-step guide to developing specific applications. Therefore, this chapter looks at the steps Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 163 164 CHAPTER 15 Working within an OS environment required to work within an OSBI environment, with more detailed
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you plan your BI project properly and include all the various types of resources needed to help get you there. Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 175 176 CHAPTER 16 Required skillsets both IT-related and business-oriented needs and to understand both parts of
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story due to the bigger development efforts required. In some cases This comment is based on interviewing multiple OS developers. Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 185 186 • CHAPTER 17 Technical benefits and challenges actual deployment times take longer because of the development requirements of
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implementation. Integration between data sources is not intuitive. The effort involved needs to be accounted for when planning a project. Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc. All rights reserved. 199 200 CHAPTER 18 Getting started: A checklist for OSBI readiness 4 What are the integration requirements in relation
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to what other solution providers offer. This page intentionally left blank Index A Analytics, 6 12, 26, 179 Analytics engine, 10 11 B BI, see business intelligence BI adoption, 80 83 acquisitions, 83 business visibility, 81 competitive edge, 83 consolidating information, 80 81 metrics/KPIs, 82 83 mitigating risk, 82 BI drivers
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price comparability, 46 48 Business and IT benefits and challenges for, 68 69 relationship between, 68 in terms of outlook, 66 68 Business efficiencies, 46 Business intelligence applications, 7 components, 156 157 components of, 9 12 delivery methods, 7 8 environment, 159 expansion, 166 market, 16 strategy, 77 traditional, 9f Business rules
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of, 37 38 increasing popularity of, 43 IT developer flexibility and, 18 market, 14 17, 19 open standards, 19 traditional communities, 33 34 Open source business intelligence (OSBI), 3, 13 benefits, 69 73 customization options, 71 72 deployment times, 69 70 internal development efforts, 71 OS framework, 72 73 subscriptions, 72 challenges
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and IT collaboration and project sponsorship, 75 76 development efforts, 74 long-term costs, 74 75 scalability, 76 increasing popularity of, 47, 50 Open source business intelligence (OSBI) market, 32 33 adopting, 34 37 broader deployment methods, 35 customer value, 35 36 expectations of free, 36 37 future focused, 37 low TCO
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Open source selection, 84 85 budgetary constraints, 85 experiment with BI before committing, 85 familiarity, 84 get off ground running, 85 OSBI, see open source business intelligence OSBI models, 58 61 commercial offerings, 60 61 community, 59 free software, 59 60 services approach, 61 P Project sponsors, 167 R Reporting, 27 Reports
Digital Accounting: The Effects of the Internet and Erp on Accounting
by Ashutosh Deshmukh · 13 Dec 2005
, managerial and information technology tools for Web-enabled virtual close of the books are discussed. The rest of the chapter primarily focuses on reporting software, business intelligence tools, executive dashboards, enterprise portals and its interaction with accounting data. I have primarily used SAP tools to illustrate the functionalities; however, these are supplemented
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Infrastructure •Integration with ERP Systems Customers Demand Chain Management • Customer Relationship Management • Demand Forecasting • Order Management • Product and Brand Information Management • Channel Management • Customer Services • Business Intelligence Business Finance and Accounting •Financial Reporting •Internal Controls and Audit •Cost Accounting •Treasury Functions Human Resources •Payroll Accounting •Benefits Management •Personnel Management Production •Product Design
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•Product Development Other Business Processes •Document Storage and Retrieval •Workflows Suppliers Supply Chain Management • Supplier Relationship Management • Production Planning • Materials Management • Transportation and Distribution • Business Intelligence The effects of e-commerce, as can be seen, cut across various industries; industry intermediaries; and, the ultimate, consumers; and also within the industry itself
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intersects with CRM, SRM and SCM, is also sometimes offered as a separate module. Analytical abilities of accounting/business software are also being enhanced. Earlier business intelligence applications generally collected and analyzed data from customer and supplier databases, manufacturing and marketing activities, personnel data and financial data to generate reports in the
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10, 2003, from www.crn.com/ SAP history. (2001). SAP. Retrieved December 10, 2003, from www.sap.com/ Schroeder, J. (1999). Enterprise portals: A new business intelligence paradigm. DM Review. Retrieved December 10, 2003, from www.dmreview.com/master.cfm/ Scott, R. (1999, December). J.D. Edwards counts on midmarket history. Accounting
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Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. The Revenue Cycle 141 packaged business intelligence tools. Enterprise portals and business intelligence tools are discussed in depth in the general ledger cycle. The integrated software modules that enable CRM functionalities are interactive center, e-commerce
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shared across the organization. This module is used in what SAP calls financial insight, procurement insight and sales insight, which essentially are prepackaged business intelligence tools. Enterprise portals and business intelligence tools are discussed in depth in the general ledger cycle. The next step investigates tools used to manage the SRM process. The SAP
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written permission of Idea Group Inc. is prohibited. The General Ledger Cycle 269 Exhibit 5. Financial analytics Tools •Spreadsheets •SQL •Report writing tools •Analytical tools •Business intelligence Financial data warehouse Business information warehouse Financial analytics CRM analytics SCM analytics PLCM analytics HR analytics Enterprise portals Executive dashboards Reports •Financial statements •Managerial reports
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forms without written permission of Idea Group Inc. is prohibited. 270 Deshmukh Exhibit 6. Business intelligence tools •Data extraction •Data transformation •Data load Business information warehouse ERP system Reports •Key performance measures •Ad-hoc queries •Business intelligence metadata •OLAP metadata Business intelligence tools OLAP Analysis •Business logic •Mathematical/statistical models •Data mining Executive dashboards Management dashboards
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•Corporate performance management These tools were soon superceded by specialized report writing tools and analytical tools, which now have evolved to a new category of Business Intelligence (BI) tools; Crystal Reports/Business Objects and Cognos are examples of leading software vendors in this area. This BI software can handle report writing, data
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and cost Time-to-delivery Quantity and yield Organizational effectiveness Cognos Web Services uses an XML-based interface. This service can be used to deliver business intelligence in different computing environments having a software and hardware mix via Web-based protocols. For example, such protocols can be used to deliver data to
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and work with another) for such packaged reports. This service also provides a visual test studio environment that can be used to test and verify business intelligence applications. Cognos Access Manager centralizes security functions for reports, analyses and queries. The access manager maintains user classes and applies authorization and authentication rights to
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a part. These tools are supported by technologies seen earlier — SAP exchange infrastructure, SAP knowledge warehouse, SAP business information warehouse and SAP enterprise portal. MySAP business Intelligence consists of a BI platform, BI tools and measurement and management. The BI platform provides a foundation for Exhibit 9. Cognos architecture Cognos Access Manager
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tools allow for measuring and monitoring of business performance based on packaged and user defined KPIs, management of metadata to maintain consistent data and collaborative business intelligence. Additional capabilities of mySAP BI include Web-based reporting and analysis, different modes of delivering information to the end user, integration with Microsoft Excel, multidimensional
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to understand the possibilities, or they may fail to exploit the tremendous power of these tools. Exhibit 11. SAP business intelligence Exchange infrastructure SAP R/3 ERP Knowledge warehouse Business information warehouse MySAP business intelligence •Business intelligence platform •Business intelligence tools •Measurement and management Packaged BI solutions •Financial insight •Sales insight •Procurement insight Enterprise portal Copyright © 2006, Idea
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vendors and consultants have produced multiple definitions and interpretations of enterprise portals. These definitions revolve around organization of information, collaboration among users, technical infrastructure and business intelligence capabilities. As the enterprise portal technology evolved, all these functionalities have converged, and now comprehensive software offerings have emerged in this area. So, what are
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in print or electronic forms without written permission of Idea Group Inc. is prohibited. The General Ledger Cycle 285 Exhibit 15. Components of enterprise portals •Business intelligence •Collaboration tools •Knowledge management •Search facilities •Workflows •Web servers •Content servers •Application servers •Support of standards Functionalities Infrastructure I Interface Infrastructure II •Personalization •User-friendliness
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different servers to accomplish various functions and software for the administration, security and development environment. The servers contain the logic to perform functions such as business intelligence, knowledge management, interfacing with databases and document repositories and portal management. Enterprise portals also come with software for administering and securing the portals, and a
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package for financial queries, users guide. (2003). SAP. Retrieved August 5, 2003, from www.sap.com Business planning and simulation with mySAP financials and mySAP business intelligence (SAP Solutions Brief). (2003). SAP. Retrieved August 6, 2003, from www.sap.com Business unification with mySAP enterprise portal (mySAP Enterprise Portal Brief). (2003). SAP
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. 292 Deshmukh Scherpenseel, C. (2003, July/August). Getting more from an ERP investment. Financial Executive, 19, 52-54. Schroeder, J. (1999). Enterprise portals: A new business intelligence paradigm. DM Review. Retrieved August 11, 2003, from www.dmreview.com/ The SAP procurement insight package (SAP Solutions Brief). (2003). SAP. Retrieved August 15, 2003
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1. Whither accounting? Distribution networks Inbound logistics Distribution networks Outbound logistics PLCM analytics PLCM Supplier networks SCM analytics CRM analytics SCM CRM SRM analytics SRM Business intelligence tools Budgeting consolidations Enterprise portals ERP Customers Treasury analytics Treasury functions Financial analytics HR analytics Financial data warehouse Business information warehouse Financial intermediaries Copyright © 2006
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Data warehouse Scenario analysis Knowledge warehouse Planning and budgeting Communication Monitoring Forecasting Reporting Web based collaborative tools Simulation and optimization models Planning and budgeting software Business intelligence tools Reporting and analytical tools Enterprise portals Executive dashboards Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission
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The technology tools required for the CPM process are data warehouse, knowledge warehouse, Web-based collaborative tools, simulation and optimization models, planning and budgeting software, business intelligence tools, reporting and analytical tools, and enterprise portals. These tools have been around for some time, and the applications of these tools have been investigated
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due to advances in Information Technology. CPM packages different technology tools, such as ERP systems, CRM, SCM and SRM, to name a few, and uses business intelligence tools to extract and deliver performance measures across the organization. The SAP SEM solution and its support for CPM were explored in-depth. However, do
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www.sap.com/ Optimizing the financial supply chain (white paper).(2002). Palo Alto, CA: Killen & Associates. Retrieved from www.killen.com/ Oracle 9i application server: Business intelligence technical overview (white paper). (2003). Oracle. Retrieved September 14, 2003, from www.oracle.com/ Osterland, A. (2002, January). Virtual treasury: Any day now. CFO. Retrieved
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system (BIPS) 87 benchmarking 313 Berlin Airlift 2, 90 Best Software 30 billing and collections 39 biometrics 342 BIPS (bank Internet payment system) 87 BI (business intelligence) tools 270 boot viruses 327 boxtop licenses 332 BPM (business performance measurement) 308 business function modules 31 business information warehouse 139
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business intelligence (BI) tools 270 business objects 270 business packages 287 business performance measurement (BPM) 308 business-to-business (B2B) 6, 8, 38, 141, 152, 181 business-
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improve phone performance in developing countries. It maintained Onavo’s business model, which was gathering data from deceptively “free” apps to inform its money-making business intelligence operations. When the mobile performance tool no longer served its purpose, Facebook created a different honey trap for user data, Onavo Protect, which delivered what
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by Richard A. Clarke and Robert K. Knake · 15 Jul 2019 · 409pp · 112,055 words
repository in which current and perhaps past data is stored. The information contained within a data lake can be queried and is often useful for business intelligence or analytical purposes. Defense Advanced Research Projects Agency (DARPA): A U.S. Defense Department office that funds university and laboratory investigations and experiments into new
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by Thomas H. Davenport · 4 Feb 2014
., 1954 Big data at work : dispelling the myths, uncovering the opportunities / Thomas H. Davenport. pages cm ISBN 978-1-4221-6816-5 (alk. paper) 1. Business intelligence—Data processing. 2. Big data. 3. Business planning—Statistical methods. 4. Data mining. I. Title. HD38.7.D379 2014 658.4’038—dc23 2013039005 ISBN
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people—and vendors in particular—are already using big data to mean any use of a nalytics, or in extreme cases even reporting and conventional business intelligence. It is a well-established phenomenon that vendors and consultants will take any new, hot term and apply it to their existing offerings—and that
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up with new names to describe it? The general activity of making sense of data has been called decision support, executive support, online analytical processing, business intelligence, analytics, and now big data (see table 1-3).4 There are certainly some new elements in each generation of terminology, but I’m not
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Executive support 1980–1990 Focus on data analysis for decisions by senior executives Online analytical processing (OLAP) 1990–2000 Software for analyzing multidimensional data tables Business intelligence 1989–2005 Tools to support datadriven decisions, with emphasis on reporting Analytics 2005–2010 Focus on statistical and mathematical analysis for decisions Big data 2010
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change in the nature of business software. We are moving beyond automating transactions to analyzing the data they generate. When SAP generates more money from business intelligence Chapter_01.indd 13 03/12/13 3:24 AM 14 big data @ work and analytics than from its transactional suite of applications, a major
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4 about why this is such a difficult problem, but my point here is that it’s going to get much easier. Many universities offer business intelligence or analytics degree programs or concentrations, and a good proportion are adding big data topics and skills to their curricula. A number of big data
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has been used to understand and tune the processes, keeping management informed and alerting them to anomalies (“exception reporting” has been a key aspect of business intelligence). Business and technology architecture often reflect this flow, starting with transactions and operations and moving—one hopes—to analysis and insight. Companies review performance, plan
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to create appealing products and services for customers. I’ve already mentioned that this benefit was not one that I often encountered when discussing conventional business intelligence and analytics. It’s still early days for big data in general and for data-based products and services specifically, but there are many examples
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key decision. There is some evidence that these skills are important. A Gartner study found that “between 70 percent and 80 percent of c orporate business intelligence projects fail” owing to “a c ombination of poor communications between IT and the business, the failure to ask the right questions or to think
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about the real needs of the business.”3 And granted, business intelligence projects usually involve small rather than big data. However, while the specific percentage of projects that fail is questionable, there is no doubt that lack
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Francisco. One list, compiled by Barbara Wixom at the University of Virginia and several other academics, identified fifty-nine universities with degrees or majors in business intelligence or business analytics.10 Many of these programs have added, or are planning to add, data science content to their programs. If you’re a
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, many consumers of big data (and for that matter, many consumers of traditional small data analytics) prefer it to be displayed visually. Unlike the specialized business intelligence technologies and unwieldy spreadsheets of yesterday, data visualization tools allow the average businessperson to view information in an intuitive, graphical way. The data visualization shown
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data warehouse or collection of federated data marts that house and—ideally— integrate the data for a range of analysis functions; and a set of business intelligence and analytics tools that enable decisions from the use of ad hoc queries, dashboards, and data mining. Figure 5-4 illustrates the typical big company
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data warehouse ecosystem. Indeed, big companies have invested tens of millions of dollars in hardware platforms, databases, ETL (extract, transform, and load) software, BI (business intelligence) dashboards, advanced analytics tools, maintenance contracts, upgrades, middleware, and storage systems that comprise robust, enterprise-class data warehouse environments. In the best cases, these environments
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Source: SAS Best Practices. Chapter_05.indd 130 03/12/13 1:05 PM Technology for Big Data 131 storing historical data to provision traditional business intelligence and analytics results. But those operational systems can also populate the big data environment when they’re needed for computationrich p rocessing or for raw
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data is a very strong element of each of these, and you’re not doing anything, it’s like trying to run a business without business intelligence.a a. E. B. Boyd, “LinkedIn’s Reid Hoffman on Groupon’s Big Advantage: Big Data,” FastCompany.com blog post, http://www.fastcompany.com/1795868
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/you_cant_ just_hack_your_way_to.html. 3. Bill Goodwin, “Poor Communication to Blame for Business Intelligence Failure, Says Gartner,” ComputerWeekly.com, January 10, 2011, http://www .computerweekly.com/news/1280094776/Poor-communication-toblame-for- business-intelligence-failure-says-Gartner. 4. See Thomas H. Davenport and Jinho Kim, Keeping Up with the Quants
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.com/talent-analytics-corp/research-study/. 9. E-mail correspondence with Mark Grabb, April 1, 2013. 10. Barbara Wixom et al., “The Current State of Business Intelligence in Academia,” Communications of the Association for Information Systems 29 (2011), http:// aisel.aisnet.org/cais/vol29/iss1/16. 11. Interview with Jake Klamka conducted
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technology BodyMedia, 12 Boeing, 47 British Airport Authority (Heathrow Airport Holdings), 150–151, 199 Brynjolfsson, Erik, 27, 206 Buluswar, Murli, 142 business analytics. See analytics business intelligence (BI), 7, 10, 10t, 14, 18, 23, 93, 102, 124, 128, 129, 130 business models, 41–42, 57, 168, 173, 188 business-to-business (B2B
The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies
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instance, Materials Resource Planning (MRP) systems, which begat Enterprise Resource Planning (ERP), and then Supply Chain Management (SCM), Customer Relationship Management (CRM), and, more recently, Business Intelligence (BI), Analytics and many other large-scale systems. 11. Todd Traub, “Wal-Mart Used Technology to Become Supply Chain Leader,” Arkansas Business, http://www.arkansasbusiness
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on modeling external trends, but she also led the company’s focus on analytics and data-driven decision-making. She was responsible there for the Business Intelligence and Informatics Competency Center, and had responsibility for $50 million of analytics-oriented projects and systems. At her current employer, Anthem—the second-largest company
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trillion by 2017.30 It’s interesting if you look at the high-growth markets that are currently developing around cloud computing, big data, and business intelligence. These markets are in the double-digit billions, and are often not counted toward the M2M market. This shows how blurry the borders are, and
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