T DW I R E S E A R C H   T DW I CHECK L IS T RE P OR T   SEVEN STEPS TO   ACTIONABLE PERSONAL   ANALYTICS AND DISCOVERY   ...
JUNE 2012T DW I CHECK L IS T RE P OR T                                       TABLE OF CONTENTSSEVEN STEPS TOACTIONABLE PER...
TDWI CHECKLIST REPORT: SE VEN STEPS TO ACTION A BLE PERSON A L A N A LY TICS A ND DISCOVERY  FOREWORD                     ...
TDWI CHECKLIST REPORT: SE VEN STEPS TO ACTION A BLE PERSON A L A N A LY TICS A ND DISCOVERY   	    NUMBER TWO             ...
TDWI CHECKLIST REPORT: SE VEN STEPS TO ACTION A BLE PERSON A L A N A LY TICS A ND DISCOVERY  	     NUMBER FOUR            ...
TDWI CHECKLIST REPORT: SE VEN STEPS TO ACTION A BLE PERSON A L A N A LY TICS A ND DISCOVERY  	     NUMBER SIX             ...
TDWI CHECKLIST REPORT: SE VEN STEPS TO ACTION A BLE PERSON A L A N A LY TICS A ND DISCOVERY  ABOUT OUR SPONSOR            ...
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Seven steps to actionable personal analytics and discovery

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Organizations today want to be driven by data. They want to
anchor daily and strategic decisions in a bedrock of solid,
extensive, and timely analysis and reporting. Organizations want to
reach out to more data sources and integrate diverse data to gain
single views of important business objects and domains, including
customers, products, and services. Business intelligence (BI) and
analytics are essential technologies, methods, and processes to
support data-driven decisions. However, in most organizations,
only a minority of users can access them. This needs to change if
data-driven objectives are to be achieved.
Past attempts at extending BI out to users in operations have
been met with mixed success. Users have gained significant
advantages, including better data quality, data access, and
reporting; yet, they are frustrated by their inability to tailor the BI
environment to their personal needs. Customizing the environment
and performing ad hoc, what-if analytical queries can require
significant IT involvement. Many organizations are deepening
their analytical power by investing in hiring specialists dedicated
to marketing, finance, or other business functions to implement
data mining tools and methods; however, the mass of users share
only indirectly in the fruits of their labors. Most users cannot do
advanced discovery analysis on their own.
Personal, self-service BI and analytics tools are now available
that can give users more control over how they view and access
data and the reports, dashboards, and visualizations they need
to perform their roles in the enterprise. Easier deployment and
configuration, improved self-service features, and technology
advances such as in-memory computing are giving users work
environments that are robust enough to perform significant BI and
analytics processes without involving IT at every step, as has been
necessary in the past.
This TDWI Checklist Report details seven steps toward personal BI
and analytics success. Note that IT is not left out of the picture;
on the contrary, this checklist shows that IT has an important
role to play in guiding users and provisioning enterprise data
resources. Users are more productive when personal, self-service
BI and analytics technologies are well integrated with enterpriselevel
systems.

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Seven steps to actionable personal analytics and discovery

  1. 1. T DW I R E S E A R C H T DW I CHECK L IS T RE P OR T SEVEN STEPS TO ACTIONABLE PERSONAL ANALYTICS AND DISCOVERY By David StodderSponsored bytdwi.org
  2. 2. JUNE 2012T DW I CHECK L IS T RE P OR T TABLE OF CONTENTSSEVEN STEPS TOACTIONABLE PERSONAL 2 FOREWORDANALYTICS AND DISCOVERY 2 UMBER ONE N Determine user needs for personal BI and analytics functionality.By David Stodder 3 NUMBER TWO Increase users’ personal productivity with enterprise BI management. 3 NUMBER THREE Provide users with complete views of data using enterprise integration. 4 NUMBER FOUR Strengthen performance management with personal BI and analytics. 4 UMBER FIVE N Capitalize on in-memory computing for advanced BI and analytics. 5 NUMBER SIX Enable users to realize the power of dashboards and visual analysis. 5 NUMBER SEVEN Make collaboration a priority in the deployment of personal BI and analytics. 6 ABOUT OUR SPONSOR 6 ABOUT THE TDWI CHECKLIST REPORT SERIES 6 ABOUT THE AUTHOR 6 ABOUT TDWI RESEARCH1201 Monster Road SW, Suite 250Renton, WA 98057T 425.277.9126F 425.687.2842E info@tdwi.orgtdwi.org © 2012 by TDWI (The Data Warehousing InstituteTM), a division of 1105 Media, Inc. All rights reserved. Reproductions in whole or in part are prohibited except by written permission. E-mail requests or feedback to info@tdwi.org. Product and company names mentioned herein may be trademarks and/or registered trademarks of their respective companies.
  3. 3. TDWI CHECKLIST REPORT: SE VEN STEPS TO ACTION A BLE PERSON A L A N A LY TICS A ND DISCOVERY FOREWORD NUMBER ONE DETERMINE USER NEEDS FOR PERSONAL BI AND ANALYTICS FUNCTIONALITY.Organizations today want to be driven by data. They want to Some users are satisfied with standard BI reports as deliveredanchor daily and strategic decisions in a bedrock of solid, by IT, and they will continue to need such reports. However,extensive, and timely analysis and reporting. Organizations want to research by TDWI and market analyst firms shows that the BIreach out to more data sources and integrate diverse data to gain penetration rate in most organizations hovers between 15 andsingle views of important business objects and domains, including 25 percent of the total user community—below what it could be.customers, products, and services. Business intelligence (BI) and With application backlogs bulging, IT is struggling to satisfy useranalytics are essential technologies, methods, and processes to requirements, not to mention frequent “what-if” analysis requestssupport data-driven decisions. However, in most organizations, from users who want to explore data fully on their own. A delay ofonly a minority of users can access them. This needs to change if weeks or months before users can implement BI or get answers todata-driven objectives are to be achieved. queries is a severe problem when organizations are under pressure to compete on intelligence.Past attempts at extending BI out to users in operations havebeen met with mixed success. Users have gained significant Traditional IT methods of gathering requirements and developingadvantages, including better data quality, data access, and applications are proving inadequate due to the variety of users andreporting; yet, they are frustrated by their inability to tailor the BI needs. As organizations attempt to extend BI systems, they areenvironment to their personal needs. Customizing the environment discovering that users have widely varying levels of experience.and performing ad hoc, what-if analytical queries can require Nontechnical users have sophisticated questions that they cansignificant IT involvement. Many organizations are deepening only articulate once they have explored the data; yet, because theytheir analytical power by investing in hiring specialists dedicated are not “power users” who know how to pose queries and navigateto marketing, finance, or other business functions to implement schemas, they are frustrated.data mining tools and methods; however, the mass of users share As users become familiar with BI, their needs often grow moreonly indirectly in the fruits of their labors. Most users cannot do diverse. For some requirements, users need visual dashboardsadvanced discovery analysis on their own. that convey easily understood information. The same users mightPersonal, self-service BI and analytics tools are now available need the ability to do forecasting calculations that they havethat can give users more control over how they view and access previously known how to do only with spreadsheets. Meeting suchdata and the reports, dashboards, and visualizations they need diverse needs from even single users can prove a headache for ITto perform their roles in the enterprise. Easier deployment and organizations, let alone when multiplied by hundreds or thousandsconfiguration, improved self-service features, and technology of users.advances such as in-memory computing are giving users work The deliverable in this step is to evaluate personal, self-serviceenvironments that are robust enough to perform significant BI and BI and analytics. New versions of existing enterprise BI toolsanalytics processes without involving IT at every step, as has been as well as recently introduced tools have features that enablenecessary in the past. users to personalize how they view, access, analyze, and shareThis TDWI Checklist Report details seven steps toward personal BI information. Other steps in this checklist will discuss specificand analytics success. Note that IT is not left out of the picture; areas for implementing self-service features. The focus here ison the contrary, this checklist shows that IT has an important to begin at the beginning: evaluate user requirements. If yourrole to play in guiding users and provisioning enterprise data organization plans to expand BI and needs to address diverseresources. Users are more productive when personal, self-service user requirements, the best practice is to evaluate tools that canBI and analytics technologies are well integrated with enterprise- integrate with enterprise BI and data warehousing systems to takelevel systems. the load off of IT and give users the choice of features they need.2  TDWI RESE A RCH tdwi.org
  4. 4. TDWI CHECKLIST REPORT: SE VEN STEPS TO ACTION A BLE PERSON A L A N A LY TICS A ND DISCOVERY NUMBER TWO NUMBER THREE INCREASE USERS’ PERSONAL PRODUCTIVITY WITH PROVIDE USERS WITH COMPLETE VIEWS OF DATA ENTERPRISE BI MANAGEMENT. USING ENTERPRISE INTEGRATION.“Self-service” BI and analytics should not translate into “going Life would be simpler if BI and analytic applications users needed toit alone” for users. Otherwise, users will remain dissatisfied and access only one data source, but in reality, life is complex. In mostwill miss out on the productivity benefits of more sophisticated organizations, data integration problems are a significant source ofBI and analytics. Indeed, most of the 75 to 85 percent of users cost and delay in getting information flowing to users so that theywho have not been implementing BI have been going it alone for can gain complete views of data about customers, product lines,some time; they have been using spreadsheets and application- territories, and more. Data integration projects never happen withoutspecific reporting tools with data limited to departmental silos, a reason; usually a critical business need exists for complete andspreadsheets, and specialized application databases. These users consistent views of data. Business environments can be dynamic,often employ manual, custom-coded methods to pull in data from with mergers and acquisitions, divisional or territorial restructuring,popular sources such as Salesforce.com. Both business users and regulatory compliance, and more creating a continuous need for newIT can do without yet more chaos bought about by unmanaged and data integration solutions.poorly integrated tool implementations. Business users often require a mix of different types of data,Productive, “personal” BI and analytics requires a managed including structured, detailed data, aggregate or dimensionalenvironment. Personal BI and analytics users need IT’s ability to data, and semi-structured or unstructured content. They also needprovision users with quality data that adheres to governance and access to external sources provided by third parties. In addition,regulatory requirements for access and sharing. IT can help users since spreadsheets are commonly used, personal BI and analyticsacross the enterprise collaborate more effectively by looking for systems cannot ignore the need to import or export data and cubesredundancy and consolidating data, as well as cutting down on the to and from spreadsheets. It can become highly time-consumingnumber of “shadow” data systems where possible. Then, with more and error-prone for users to map dimensions into hierarchies, orshared sources, users will waste less time trying to determine who map dimensions and measures into cubes, on their own. Searchhas the correct data. and index capabilities for finding semi- or unstructured content can vary from user to user, leading to inconsistency with these types ofIT can use its unique view of how users throughout the organization information.are working with data to improve workload performance on sharedservers. IT can monitor which sources are under- or over-utilized Organizations typically need tools for data integration, profiling,to address hot spots, take unneeded sources offline, and plan quality, and data relationship discovery to provide single viewsfor future growth. If some users are working with the same data of all data that is physically located in multiple sources. Datasources or are building similar reports and dashboards, IT can warehousing, transformation, and content management tools candevelop managed reports and dashboards that relieve users of also provide the unified structure, metadata, hierarchy management,having to build them on their own. If available, IT can implement and search taxonomies that are critical to simplified user access.enterprise BI platforms to help users publish and share their reports Master data management (MDM) systems can play a unifyingas well as online analytical processing (OLAP) cubes that support role, providing reference sources for all data relevant to particulargreater overall productivity for all users while ensuring data quality. business objects such as customers.Establishing the right balance between self service and IT The key deliverable with this step is to provide an enterprise datamanagement is vital to the success of personal BI and analytics. integration infrastructure to address the variety of users’ dataThe deliverable in this step is to foster a beneficial working needs. An important success factor for personal, self-service BI andrelationship between IT and business users to support independence analytics is to provide this access without requiring users to getbut avoid chaos. under the hood with the details of getting to each source; this is what enterprise data integration can manage.3  TDWI RESE A RCH tdwi.org
  5. 5. TDWI CHECKLIST REPORT: SE VEN STEPS TO ACTION A BLE PERSON A L A N A LY TICS A ND DISCOVERY NUMBER FOUR NUMBER FIVE STRENGTHEN PERFORMANCE MANAGEMENT WITH CAPITALIZE ON IN-MEMORY COMPUTING FOR PERSONAL BI AND ANALYTICS. ADVANCED BI AND ANALYTICS.Performance management goals focus on improving the alignment One of the most important technology developments today is theof daily decisions and actions with the organization’s high-priority falling cost and expanding real estate of addressable computerstrategic goals. Performance management metrics, including memory. Adoption of 64-bit operating systems has made it easierkey performance indicators, can be a significant advance over for developers and users of BI and analytics systems to exploitvoluminous “data dumps” or reports that force managers and very large memory and bring powerful functions closer to the data.executives to hunt for what’s important. Large memory allows users to perform functions against much larger data sets.Often tied to business management methods such as BalancedScorecard, Toyota Production System, or Six Sigma, metrics can With in-memory computing, the traditional I/O bottleneckbe vital for monitoring how well the organization is progressing constraint—where queries have to read information from tablestoward enterprise goals that involve more than one business stored on disk—becomes less of a factor. Users can perform, onoperation or function, such as higher customer satisfaction. TDWI their own, analyses that would be too slow with disk-dependentResearch has found that performance management is a highly systems and limited in scope because not enough data isimportant objective for mobile BI, as it gives executives and available. Algorithms can run faster in memory, making real-time,managers access to metrics while on the go. “speed of thought” analysis a reality. Processes that stand to benefit from in-memory computing include:Performance management can sometimes have a mixed reputationbecause initiatives do not always help users understand what is • Predictive analytics. Organizations can score models“actionable.” This is often due to the lack of integration between locally against data for better performance. Models canthe metrics and BI systems, which could provide critical drill- be deployed against large data volumes that are refresheddown analysis, reporting, and collaboration capabilities. Without through continuous loading and transformation. Speed isthis integration, performance management can become a silo critical to making predictive insights relevant in real timeunto itself—if not separated into multiple silos owned by finance for online customer interaction, fraud detection, and more.and business operations, each implementing separate and • hat-if scenario building and write-back capabilities. Wincompatible metrics. This can frustrate the very cross-functional Traditional BI and analytics systems make it prohibitivelycollaboration that performance management is meant to foster. costly and slow to develop what-if scenarios for planningOrganizations should seek technology that can support common and forecasting. For users of tools that support thesemodels, hierarchies, and dependency mapping, so that while processes, in-memory computing can enable them to writemetrics may be different depending upon the business function back changes to the data to see the potential impact ofor objectives, there is a way to understand how they relate their analysis and share the data with other users.to each other, how they roll up, and how they share common • mproved OLAP performance and scalability. OLAP Idefinitions. This is critical for connecting higher-level performance users can employ more and bigger dimensions andmanagement with underlying data sources. Organizations should slice and dice through larger volumes of detailed dataevaluate whether they can integrate metrics mapping with their with less need to build cubes and design aggregateMDM processes to ensure that business object definitions are tables to work around the I/O bottleneck.shared across metrics. The deliverable in this step is to evaluate how in-memoryThe deliverable in this step is to ensure integration of performance computing can enable users to explore data with far less concernmanagement metrics with personal BI and analytics. Critical areas from IT about what iterative, ad hoc styles of investigation mightto examine include (1) whether the enterprise data integration mean for performance. In-memory computing is not a silver bullet;infrastructure is properly supporting users’ performance organizations should evaluate how systems manage and refreshmanagement data sharing requirements, and (2) whether users data in memory and synchronize it with data on disk. However,have adequately powerful data servers to perform deeper analysis in-memory’s potential is enormous for faster BI and analytics.behind the metrics, including what-if scenarios and calculations.4  TDWI RESE A RCH tdwi.org
  6. 6. TDWI CHECKLIST REPORT: SE VEN STEPS TO ACTION A BLE PERSON A L A N A LY TICS A ND DISCOVERY NUMBER SIX NUMBER SEVEN ENABLE USERS TO REALIZE THE POWER OF MAKE COLLABORATION A PRIORITY IN THE DEPLOYMENT DASHBOARDS AND VISUAL ANALYSIS. OF PERSONAL BI AND ANALYTICS.Pictures can be worth thousands of data points, especially for Most users do not work alone, nor do they make decisions alone. Thus,nontechnical users who need to grasp the importance of information it is critical for personal BI and analytics applications to make it easychanges quickly and easily. Dashboards are already critical to many for workgroups to share reports and analysis, including visualizations.BI and analytics applications as single interfaces for consolidating The simplest way that users collaborate is by e-mailing reports andKPIs, scorecards, alerts, reports, graphs, charts, and visual drill- spreadsheets to each other. However, while integration between BIdown analysis through levels of aggregate and detailed data. TDWI and collaborative e-mail applications is important, this method canResearch has found that the rapid adoption of mobile platforms introduce security, data, and versioning errors that proliferate assuch as tablets is driving even stronger interest in data visualization users share reports, spreadsheets, and BI artifacts. In addition, thisand dashboards. Clear and compelling data visualization makes it method does not enable sharing of the full user workspace, includingeasier for users on the go to connect insights to choices for action dashboards; the sharing is piecemeal.based on the data. A better course is to take advantage of technologies that supportPersonal BI and analytics applications deployed in memory can sharing of dashboards and workspaces. Personal BI and analyticsgive users more intensive data visualization experiences beyond tools that are Web-based rather than desktop-based can makesimple graphs and charts. Enhanced graphics, animation, real-time it easier to assign role privileges to broad user communities.data feeds into graphics, and collaboration with others through Dashboards can then be managed and updated centrally, with accessgraphics are some of the more advanced capabilities that in-memory provided via the Web. Users should also be able to publish their workcomputing can support. These types of visualization can burn to a central BI and analytics hub so that others can view and workprocesser cycles, making large memory (plus compression) ideal with their content. This way, user communities that are distributedfor supporting visual analysis. The evolving visualization features globally can all be working on shared materials over the Web on aof in-memory BI and analytics applications may someday cause daily basis.users to look back on older BI dashboards and be amazed that Another key resource for collaboration is having a shared glossary,visualization options were once so primitive. dictionary, or other reference for standard definitions of data,The key deliverable in this step is to give users more control business objects, and terms. Earlier, this report discussed MDM as aover their dashboards and visualizations so they can personalize process and platform for developing and sharing common businessexperiences based on their roles and information needs. Frontline definitions; glossaries and dictionaries can be important resourcessales, service, and support personnel, for example, can benefit from for higher-level MDM definitions, so it is important that they aresingle views of customer data presented in a compelling visual well integrated. However, even if the organization has not deployedfashion rather than through tabular data reports. Organizations MDM, establishing a shared resource is vital for user communitiesshould evaluate BI and analytics tools that enable users to easily to work well together without losing productivity due to confusiondetermine the look and feel they want, including which charts, data, over definitions. Such resources are also valuable for tracking dataand text feeds they need in their dashboards. External, Web-based lineage, which is becoming important to organizations for datacontent—including feeds coming from both internal and external governance and regulatory compliance.social media networks—are popular if available. The deliverable in this step is to make collaboration a priority.With users free to personalize their visualization, however, IT will Organizations should evaluate technology resources that help usersneed to provide guidance so that users do not get lost in the “eye to share their work and stay coordinated on definitions to avoidcandy.” Simpler is often better; organizations should encourage confusion and data inconsistency.clear, actionable information delivery over clutter.5  TDWI RESE A RCH tdwi.org
  7. 7. TDWI CHECKLIST REPORT: SE VEN STEPS TO ACTION A BLE PERSON A L A N A LY TICS A ND DISCOVERY ABOUT OUR SPONSOR ABOUT THE AUTHOR David Stodder is director of TDWI Research for business intelligence. He focuses on providing research-based insight and best practices for organizations implementing BI, analytics, performance management, data discovery, data visualization, andIBM Business Analytics software delivers the actionable insights related technologies and methods. He is the author of a TDWI Bestdecision makers need to achieve better business performance. IBM Practices Report on mobile BI and analytics and Checklist Reportsoffers a comprehensive, unified portfolio of business intelligence, on data discovery and information management. He has chairedpredictive and advanced analytics, financial performance and TDWI conferences focused on BI agility, BI innovation, and bigstrategy management, governance, risk and compliance, and data analytics.analytic applications. With IBM software, companies can spot Stodder has provided thought leadership on BI, analytics,trends, patterns, and anomalies, compare what-if scenarios, information management, and IT management for over two decades.predict potential threats and opportunities, identify and manage Previously, he served as vice president and research director withkey business risks, and plan, budget, and forecast resources. With Ventana Research. He was the founding chief editor of Intelligentthese deep analytic capabilities, our customers around the world can Enterprise and served as editorial director for nine years. You canbetter understand, anticipate, and shape business outcomes. reach him at dstodder@tdwi.org.Please visit www.ibm.com/business-analytics. To request a call orask a question, go to www.ibm.com/business-analytics/contactus.An IBM representative will respond to your inquiry within twobusiness days. ABOUT TDWI RESEARCH TDWI Research provides research and advice for business ABOUT THE TDWI CHECKLIST REPORT SERIES intelligence and data warehousing professionals worldwide. TDWI Research focuses exclusively on BI/DW issues and teams up with industry thought leaders and practitioners to deliver both broadTDWI Checklist Reports provide an overview of success factors for and deep understanding of the business and technical challengesa specific project in business intelligence, data warehousing, or surrounding the deployment and use of business intelligence anda related data management discipline. Companies may use this data warehousing solutions. TDWI Research offers in-depth researchoverview to get organized before beginning a project or to identify reports, commentary, inquiry services, and topical conferences asgoals and areas of improvement for current projects. well as strategic planning services to user and vendor organizations.6  TDWI RESE A RCH tdwi.org

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