visual discovery perceptions and market trends

Visual Discovery: Perceptions onsM rketsTreonn BI Leadership Benchmark Report

By Cl uni sImhiff June 2013

Vinu lsDincivery:sPerceptiions onsM rketsTreonn 2

T blesifsCioteotn Overview ...................................................................................................... 3

What is Visual Discovery? ................................................................... 3

Market Trends and Adoption Rate ..................................................... 4

Business Benefits ................................................................................ 4

Challenges .......................................................................................... 5

Perceptions ......................................................................................... 7

Survey Results .............................................................................................. 8

Adoption Rate ..................................................................................... 8

Scope .................................................................................................. 9

Deployments .................................................................................... 10

Integration ........................................................................................ 11

Data Sources ..................................................................................... 12

Standardization ................................................................................ 13

Users ................................................................................................. 14

Features ............................................................................................ 15

Satisfaction ....................................................................................... 16

Purchasing Drivers ............................................................................ 17

Challenges ........................................................................................ 18

Future Plans ...................................................................................... 19

Why Not? .......................................................................................... 20

Recommendations ........................................................................... 21

Summary .................................................................................................... 22

BENCHMARK REPORT

Visual Discovery: Perceptiions onsM rketsTreonn 3

Overview AsPICTUREsISsWORTHsA THOUSANDsWORDS—or in the case of business intelligence (BI), it is worth a thousand or more data points. Afer all, human beings are visual creatures. This is how we perceive and make sense of our surroundings. So doesn’t it make sense for us to use visually oriented techniques to perceive and make sense of our business world as well? But creatng a preet picture is onlt part o the eaele. Visual discovery must also enable the business user to discover new things and interact with the data. Visual discovery tools allow the business user to get a quick understanding of a eusiness situaton and then oom in, lter out, and obtain details on demand—basically to allow the data to tell the businessperson its story. It is a dynamic form o a narratie or persuasion—all occurring with minimal IT interienton.

Wh tsinsVinu lsDincivery? THEREsSEEMSsTOsBEsAsLOTsOFsCONFUSION regarding traditonal BI and visual discoiert. Here are two standard de nitons or these diierent sttles o BII

Tr nitio lsBIstiilnsare predominantly controlled, driven and implemented et corporate IT. The outputs tend to ee mostlt statc dashboards, tabular reports, or simple OLAP analyses. The users have limited interacton, mostlt in the orm o drilling down through the leiels of summarized or aggregated data to the detailed data. Changes and enhancements to the eniironment generallt require IT interienton, which is why many people re er to this orm as “managed reportng..

Vinu lsninciverystiiln turn the data into iisual perceptons that the users can manipulate and interact with. Corporate IT mat stll ee iniolied, eut a large part o the creaton o diierent iisuali atons rests in the hands of the business user.

Visual discoiert, eecause o its improied ease o use and consumpton, means it is an ideal technology for business users who want to serve themselves. These users want the improved level of autonomy that self-seriice BI oiers them, and surveys have shown that this is a major driver for many implementatons o these technologies. Visuali aton techniques iart and include simple actons lile mouseoier or displating tps, metadata, or aiailaele unctons when the cursor rests over an

Visual discovery, because of its improved ease of use and consumptonn,means it is an ideal technology for business users who want to serve themselves.

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object; auto-suggestng or chart ttpes that t the data eeeere lassoing or selectng speci c data ialues in a chart et circling them with a cursore and animatons that show how the data ialues haie changed oier tme. .or more on iisuali aton techniques as well as in ormaton on eialuaton criteria, see “Vinu lsDinciverysTiiln:sM rketsSegmeot tios onsPrinuctsPinitioiog. et Wayne Eckerson. Finally, many visual discovery tools have some kind of proprietary data structure or storing and modeling the data. Mant tmes, eut not alwats, this is an in-memory and/or columnar database.

M rketsTreonns onsAniptiosR te VISUALsDISCOVERY HASsHADsAsCONSIDERABLEsIMPACT on oierall BI soluton sales. Mant companies todat consider its capaeilites as a mandatort part o their BI eniironment, ofen replacing the popular eut somewhat limited Ecel spreadsheet. It seems that once visual discovery lands on a business user’s desl, others tale notce and iisual discoiert eegins to spread rapidlt throughout the company. Also, BI vendors haie ound that aeractie dasheoards using iisual discoiert capaeilites male or easier sells to their prospects. When should visual discovery techniques be used? It turns out that these techniques are iert use ul in per orming iarious analttcal actiites lile tme-series and performance analyses. It is also useful in analyzing and monitoring prede ned metrics and conductng what-i scenarios, detectng outliers that mat indicate a new trend, and uncoiering new relatonships eetween eients, customers, products, campaigns, etc. The adopton rate or iisual discoiert tools is quite good. ur suriet shows that almost 50% o the respondents haie either ullt deploted or partallt deploted these tools in their organi atons. This increase indicates the compelling need o eusiness users to haie eeeer and aster wats to gain insight into unfolding business scenarios.

BunioennsBeoefitn THEsBENEFITSsFROMsDEPLOYINGsVISUALsDISCOVERYsIMPLEMENTATIONS are iaried and eroad. Beeer insight, aster tme to discoiery, and more analysis with less data manipulaton are some. The most popular eene ts areI

The,benefits,from deploying visual discovery implementatons,are varied and broad.

http://searchbusinessanalytics.techtarget.com/ebook/Visual-Discovery-Tools-Market-Segmentation-and-Product-Positioning

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Cimpreheoniio: Visuali atons o data communicate compleE data relatonships, such as paeerns, trends, outliers, etc., ar aster than a series of numbers in a taele, spreadsheet or a teEt-based report. It greatlt improies the tme to insight so mandatort in todatys compettie eniironment. Basicallt, iisual discoiert is iert eiectie at proiiding access to the right in ormaton at the right tme. Ioter ctio: Visual discovery allows the businessperson to determine what to manipulate, lter, select, and drill into iert quicllt. The sel -service environment fostered by visual discovery means business users can address unantcipated data needs in a ar more tmelt manner. The personys productiitt is greatlt enhanced and their lnowledge is signi cantlt increased through iisual discoiert. Discovery of uokoiwosrel tionhipn: Visual presentatons o data quicllt uncoier preiiouslt unlnown paeerns, trends and other relatonships eetween data and eients. This allows analtsts to spend more tme actuallt analt ing and thinling aeout wht these relatonships are occurring rather than grinding through endless spreadsheets, columns of numbers, and tabular reports. AniptiosifsBIs nnetn: Because iisual discoiert speeds tme to insight, it has also increased the numeer o eusiness users utli ing BI assets throughout the enterprise (see adopton rates aeoie). The resultng eiect is that companies are eecoming much more data-driven and analttcal in terms o their decision maling. Beterslever gesifsITsreniurcen: Because of the business user’s propensity for creatng a sel -service BI environment with visual discovery tools, IT resources are freed up to pursue more strategic actiites that haie greater eusiness ialue to the enterprise. These include deieloping new applicatons, eEpanding data in the data warehouse, improiing data qualitt processing, and incorporatng new technologies to improve performance. IT becomes more of a partner than a roadblock to business users wantng BI assets—which means that IT and the eusinesspeople haie an improied collaeoratie relatonship.

Ch lleogen ASsWITHsALLsNEWsIMPLEMENTATIONS, visual discovery projects have their own set o challenges or pitalls that can derail a success ul initatie. Here are a ew o the more common challengesI

As with all new implementatonsn,visual discovery projects have their own set of challenges.

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Bi nsiosvinu liz tion: Visuali aton should be designed to be devoid of bias—it should be based on what the data actually says, not on what the user wants it to say. You can create a misleading graph easily just by presentng a numeer that is tmes eigger than another one in a format. The 3D ormat males the numeer appear to ee nine tmes eigger. mitng outliers, using capped ialues, or areitrart temporal ranges can be fraught with peril in that the outliers or out-of-range ialues mat ee earlt warning indicators o new and perhaps deiastatng trends or paeerns. B nsnenigo:sThe iisual design is not a triiial maeer and much literature has eeen wrieen coiering the proper design of visual graphics. Something to keep mind is that you can bring balance to visual designs et simplt presentng the same data in alternatie representatons, labeling everything to avoid ambiguity, and using standardized measurements and units. And make sure you develop a variety of visual graphics—the much-maligned pie chart has many, ar more interestng relaties. Each user has his or her own way of viewing data so make sure tou match the right ttpe o iisuali aton to the eusiness user and the proelem at hand. A good practce is to create a protottpe and get feedback on the design. Vinu lsiverli n: Businesspeople are bombarded daily with images from a multtude o diierent sources. Constant eEposure to oierlt complicated, highly dimensionali ed iisuali atons can actuallt cause the eusinessperson to eecome “nume. to what he or she is seeing. A recommendaton is to ocus on haiing the iisuali aton eEplain the data, not decorate it. Secondly, to turn passive viewing into a dynamic and partcipatort eEperience, eusinesspeople must ee aele to interact with the in ormaton. Thet need to ee aele to iiew, touch, interpret and ident t trends or paeerns. The users retain the in ormaton eeeer and use fewer resources to make a decision when they can interact and discover. Successful visual discovery projects will empower their users without overwhelming them.

It is important to remember that visual discovery is meant to breathe life into datae it enhances a personys aeilitt to comprehend compleE relatonships quickly and to improve his or her business insight. Visual discovery has a story to tell. If you are unsure how to design your visual discovery environment, hire an eEpert in design. Thet can guide tou through the process.

Visual discovery is meant to breathe life into data; it enhances a person’s ability to improve his or her business insight.

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Perception AsPERCEPTIONsINsTHEsMARKETPLACE is that business departments, frustrated with their IT departments, purchase visual discovery tools predominantly. This may have been true 5 years ago; but more and more today, we are seeing enterprise-class solutons eeing rolled out by IT. Of course, these implementatons are stll quite diierent rom traditonal IT-driven BI environments. They are far more self-service oriented and give the business users much more freedom and access to their own data sources as well as IT-created data warehouses and marts. A second percepton is that iisual discoiert will replace traditonal BI. It is important to aclnowledge that traditonal BI stll has its role and is the appropriate wat to communicate certain ttpes o data. .or eEample, ranlings (top 10, eoeom 10%, etc.) o sales, customers, salesperson per ormance, etc. are easilt and eest displated in a teEt-eased ormat. Traditonal BI technology is suitaele or situatons where the eEact numeer or ialue o a metric or measurement is required or where there is a need to proiide routne in ormaton quicllt and eecientlt. Third, many people believe that visual discovery tools are implemented by indiiidual departments or eusiness units in their aeempts to create a sel -seriice BI eniironment. ur suriet dispels this percepton. hen asled which best describes the scale and scope of their visual discovery deployments, the highest respondent answer (39%) was for the enterprise. Respondents selected eusiness unit 29% and departmental 25% o the tme. It seems that organi atons want iisual discoiert tools to reside in a centrali ed ashion much lile their traditonal BI eniironments. This is further reinforced by our respondentsy response to the queston, “ hich data sources are accessed et tour iisual discoiert tools?. An oierwhelming 72% answered the enterprise data warehouse. .inallt, there is a percepton that iisual discoiert tools belong solely to the business users and IT either does not have a role or does not need to know aeout them. Neither o these is correct. Corporate IT has a signi cant role in monitoring this environment, ensuring that security and privacy policies are in place, and eEpanding the sources o data and maling them accessiele to the business community. The savvy IT department will embrace these technologies and truly become the business partner they should be. The eoeom line is that iisual discoiert tools are complementart to BI tools, not alternaties to them. Thet enhance the oierall user eEperience or certain

The,botom,line,is,that visual discovery tools are complementary to BI tools, not alternaties,to,them.

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types of BI analyses, thus improiing the oierall adopton o BI assets in most organi atons. Thet improie the adopton o BI assets throughout the organi aton, thus moiing it to a more analttcallt saiit enterprise.

SurveysRenultn THEsREMAINDERsOFsTHISsREPORTsPROVIDESsMARKETsPERSPECTIVESson visual discovery tools. The following charts are based on a survey of 192 BI professionals conducted in April 2013 by the BI Leadership Forum, a LinkedIn group for BI directors and their teams. Two-thirds (66%) of the respondents are BI professionals, 19% are BI consultants, 8% are business users or sponsors, and 7% are “other.. ( e discarded responses rom iendors and academics.) About half (46%) come from large companies with more than $1 billion in revenue, while another third (33%) are medium-size companies with between $100 million and $1 billion in revenue, and 21% are small companies with less than $100 million in revenue. Slightly more than half (51%) rated their BI maturity as “intermediate. while 25% rated their maturitt as “adianced. and 2 % said thet were “eeginners..

AniptiosR te VISUALsDISCOVERYsTOOLSsHAVEsBUILTsQUITEsAsFOLLOWING in the past decade, and it is safe to say that they are mainstream BI tools. Almost half (49%) o respondents haie deploted iisual discoiert tools ( ullt or partallt), while another 18% are under development. One-third (34%) have yet to take the leap, saying that they either haie “no plans. or haie a project “under consideraton.. ((ee .igure 1.)

Figure 1: What,is,the,status,of,iisual,discoiery,tools,at,your,organizatonn

Visual discovery tools have built quite a following in the past decade, and it is safe to say that they are mainstream BI tools.

10%

24%

18%

30%

19%

No plans

Under consideration

Under development

Partially deployed

Fully deployed

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Scipe MOSTsVISUALsDISCOVERYsVENDORSsSELLsTHEIR PRODUCTS to business unit and department heads, not IT. As such, the products haie a reputaton as eeing departmental BI tools. However, our data shows that 39% of companies have deployed visual discovery tools on an enterprise basis. This could mean that either they’ve standardized on a visual discovery toolset or that visual discovery tools haie proli erated independentlt throughout the organi aton. More than hal (54%) said that the scope o their deplotments is con ned either to business units or departments. (See Figure 2.)

Figure 2: Which best describes the scale and scope of your visual discovery deploymentn

Our data shows that 39% of companies have deployed visual discovery tools on an enterprise basis.

3%

25%

29%

39%

5%

Not deployed

Departmental

Business unit

Enterprise

Other

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Depliymeotns WHENsASKEDsHOWsMANYsSEPARATEsINSTANCES o iisual discoiert tools eEist in their organi aton, respondents were split into two camps. Almost hal (49%) said they only had one or two instances, which suggests either an enterprise deployment or a limited departmental deployment. Another 28% said they had more than 10 separate instances, with 12% citng more than 21 instances. These laeer results reeect the “land and eEpand. strategt o iisual discoiert vendors in which a single department purchases a tool and, when word gets out, other departments jump on board with their own purchase and implementaton. When we drilled into the respondents with enterprise deployments, the results were not dissimilar. .ift-one percent of enterprise customers said they had one or two instances (versus 49%) and 31% said they had 10 or more instances (iersus 28%) with 20% citng more than 21 instances. So, it appears that “enterprise deplotment. means that the tools haie proli erated independentlt to the point that they have become a default enterprise standard.

Figure 3: How many separate instances of visual discovery tools exist in your organizatonn

“Enterprise deployment” means that the tools have proliferated independently to the point that they have become a default enterprise standard.

2%

49%

14%

7%

10%

6%

12%

0

1 to 2

3

4 to 5

6 to 10

11 to 20

21+

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Iotegr tios THEsMAJORITYsOFsDEPARTMENTSsANDsBUSINESS UNITS generally deploy visual discovery tools independently and don’t do much to integrate them. Almost two-thirds (64%) said that some or all of their instances of visual discovery tools are not linked. However, the remainder (36%) said either most or all their instances share data and de nitons. rgani atons with enterprise deplotments haie done a much eeeer joe o integratng multple instances o visual discovery tools. More than half (53%) said that either most or all of their instances are integrated (iersus 6% or all respondents.) As weyll see in the neEt queston, most o this integraton comes rom querting integrated data in a data warehouse rather than source systems directly.

Figure,4:,To,what,degree,has,your,organizaton,linned,separate,instances,of,iisual,discoiery,toolsn

Organizatons,with,enterprise deployments have done,a,much,beter,job of integratng,multple,instances,of visual discovery tools. 19%

45%

15%

20%

None – Instances are not linked; each is an island of information

Some – Some instances share data and definitions, but most don't

Most – Most instances share data and definitions, but not all

All – All instances share data and definitions

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D t sSiurcens THEsIDEALsWAYsTOsDEPLOYsAsVISUALsDISCOVERYsTOOL to aioid creatng departmental data silos is to point the tool at the enterprise data warehouse. Com ortnglt, almost two-thirds (72%) o organi atons tale this approach. But they also populate the visual discovery tool with data from many other sources, especially local les (58%), which is a legitmate wat to enhance corporate data. Less com ortng is that more than hal o respondents (52%) said thet use iisual discoiert tools to quert enterprise applicatons, which is a sure re recipe or creatng stoiepipe analttcal systems.

Figure,5:,What,data,sources,does,your,iisual,discoiery,tool,accessn

The ideal way to deploy a visual discovery tool to aioid,creatng,departmental data silos is to point the tool at the enterprise data warehouse.

72%

58%

52%

49%

44%

31%

12%

10%

5%

Enterprise data warehouse

Local iles (e.g., Ecel)

Enterprise applications (e.g., ERP)

Departmental data mart

Departmental applications (ERP/CRM)

Eternal data

Web services

Hadoop/NoSQL

Other

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St on rniz tios AsMAJORITYsOFsCOMPANIESsHAVEsESTABLISHED STANDARDS governing the use of visual discovery tools, but those standards vary widely. (About one-third (35%) have no corporate policies or standards for visual discovery tools.) More than one-third ( 8%) haie standardi ed on the tools or creatng enterprise dashboards, while slightly less than one-third (32%) standardize on the tools for eusiness analtsts. Another 0% also standardi e on the tools or creatng departmental dashboards. Only 14% prohibit departments from purchasing the tools. (Good luck with that!)

Figure 6: What is the corporate policy regarding the use of visual discovery toolsn

A majority of companies have established standards governing the use of visual discovery tools.

38%

35%

32%

30%

14%

13%

Standardize on the tools for creatingenterprise dashboards

No corporate policy needed

Standardize on the tools for businessanalysts

Standardize on the tools for creatingdepartmental dashboards

Prohibit departments from purchasingthe tools

Require the departments to point thetools at the EDW

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Unerns VISUALsDISCOVERYsTOOLSsSERVEsMULTIPLEsAUDIENCES. Although the desktop tools are designed for power users to analyze data, they can also be used to author Web-based dashboards that can be used by casual users. Accordingly, 47% of companies say that both casual and power users are the primary users of visual discovery tools. However, 44% say their tools are used primarily by power users only. Not surprisingly, in companies that have standardized on visual discovery tools for business analysts (see Figure 6 above), a larger percentage say their primary users are power users (54% versus 44% for all companies).

Figure,7:,Who,are,the,primary,users,of,your,iisual,discoiery,toolsn

Forty-seven percent of companies say that both casual and power users are the primary users of visual discovery tools.

9%

44%

47%

Casual users

Power users

Both equally

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59%

55%

49%

37%

37%

33%

21%

21%

20%

24%

15%

22%

37%

11%

7%

4%

4%

4%

Connect to, eEplore, and analt e a singledata source

Connect to, eEplore, and analt e multipledata source

Analyze predefined metrics

Monitor predefined metrics

Conduct what-if analysis

Author and publish dashboards

Enter or update data

Transform, clean, and/or combine data

Apply data mining algorithms (e.g.,regressions)

Power User Casual User

Features WHENsITsCOMESsTOsFEATURES,sPOWERsUSERSsAREsMOREsACTIVEsUSERS of iisual discoiert tools. A majoritt use the tools to connect to a single or multple data sources and analyze prede ned metrics. More than one-third use the tools to monitor prede ned metrics ( 7%), conduct what-if analyses (37%), and author and publish dashboards (33%). The top feature used by casual users is to “monitor prede ned metrics. ( 7%), ollowed et connectng to a single data source (24%).

Figure,8:,To,what,degree,do,your,users,use,the,following,functons,in,the,iisual,discoiery,tooln,(Percentages,based,on,responses,equal,to,“high”),

The top feature used by casual users is to “monitor predefined,metrics,” followed by,connectng,to,a,single data source.

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S tnf ctios AsMAJORITYsOFsBUSINESSsUSERSsRATEsVISUAL DISCOVERYsTOOLS either “eeeer. or “much eeeer. than their eEistng BI tools. The most enthusiastc users are business users (81%), followed by department heads (68%) and eEecuties (67%). Least enthusiastc are IT managers (45%), which is not surprising since most implementatons are not initated or cleared et them. Nonetheless, 45% is stll a large percentage. And 49% o IT managers are neutral about the tools, leaving only 5% who rate them less favorably than eEistng BI tools.

Figure,9:,The,ialue,of,iisual,discoiery,tools,is,beter,or,much,beter,than,other,BI tools in use at our,organizatonn

A majority of business users rate visual discovery tools either “beter”,or,“much,beter”,than,their,existng, B,toolsn

81%

68%

67%

45%

Business users

Business department heads

Eecutiies

IT department heads

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Purch niogsDrivers THEsPRIMARYsREASONSsFORsPURCHASING a iisual discoiert tool are “eeeer iisuali aton. (78%), “easier to use. (77%), and “sel -seriice analtsis. (66%). This was followed by “fast-changing eusiness requirements. (5 %), “sel -service authoring. (51%), “quicler to deplot. (51%) and “ aster queries. (45%).

Figure 10: What,droie,the,decision,to,purchase,a,iisual,discoiery,tooln

The primary reasons for purchasing a visual discovery tool are “beter,iisualizatonn”,“easier to use” and “self-service analysis.”

78%

77%

66%

53%

51%

51%

45%

33%

25%

Better visualization

Easier to use

Self-service analysis

Fast-changing business requirements

Self-service authoring

Quicker to deploy

Faster queries

Faster data integration

More affordable

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Ch lleogens NOsTECHNOLOGYsISsWITHOUTsITSsCHALLENGES, and that holds true for visual discovery tools. About one-third o respondents eEperience signi cant diecultt with the ollowing our issuesI

1. (ourcing data rom compleE RP/CRM ststems (compleEitt) 2. Maintaining data consistency across environments (consistency) 3. Getng eEecuties to und the installaton or eEpansion o the sofware

(funding) 4. Ident ting and Eing data quality issues (data quality) 5. Maintaining performance as number of users and volume of data

increases (scalability). Thet haie slightlt ewer issues with meetng per ormance commitments and integratng the tools with other eniironments, such as dataease management systems.

Figure 11: “To what degree have you experienced the following challenges with,iisual,discoiery,toolsn”,(Percentages,based,on,responses,equal,to,“high.”),

No technology is without its challenges, and that holds true for visual discovery tools.

33%

33%

32%

31%

27%

21%

21%

CompleEitt

Consistency

Funding

Data quality

Scalability

Performance

Integration

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FuturesPl ons DESPITEsTHEsCHALLENGES above, companies are bullish on visual discovery tools—in act, iert eullish. The iast majoritt (84%) plan to eEpand their deployments, while just 2% will decrease the scope of their deployments. This is the best reference for the value and quality of visual discovery tools as any since it involves spending hard-earned dollars on a technology.

Figure,12:,What,are,your,future,plans,for,deploying,iisual,discoiery,toolsn

Despite the challenges, companies are bullish on visual discovery tools.

84%

13%

2%

Epand deplotment

Maintain, eut not eEpand

Decrease deployment

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35%

29%

27%

25%

19%

18%

18%

12%

Our budget is tapped out

We already have suitable BI tools

Not a corporate standard

Fear of proliferating spreadmarts

Don't know enough about visual discovery tools

Performance and scalability issues

Other

Not enough value for the price

WhysNit?s SOsFAR,sOURsDATAsHAS FOCUSED on those users who have deployed visual discovery tools. It’s clear that they are very pleased with the tools. However, one-third of survey respondents have yet to deploy a visual discovery tool. Among this group, there are various reasons or holding oi a purchase. The primary reason is lack of budget to buy the tools (35%), followed by the fact that thet are adequatelt seried et their eEistng BI tools (29%), the tools are not part o the corporate standard (27%) and, perhaps most signi cant o all, there is a fear that the tools will proliferate spreadmarts (25%).

Figure,13:,What,preients,you,from,deploying,iisual,discoiery,toolsn

One-third of survey respondents have yet to deploy a visual discovery tool.

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Recimmeon tions OURsSURVEYsRESPONDENTSsOFFEREDsLOTSsOFsADVICE about how to get the most out o iisual discoiert tools while aioiding its pitalls.

Cimplemeot ry. Many said visual discovery tools complement their BI standard, not replace it. “Use the right tool for the right situaton,. said one. Another said BI vendors could help here by allowing visual discovery tools to query enterprise BI tools. Met n t . Most respondents were adamant that visual discovery tools do not address eusiness metadata eut, in act, ofen undermine it. Thus, thet said it is imperatie or the BI team to euild the data later (i.e., consistent de nitons) that iisual discoiert tools can leierage. ne said, “I closed three instances last year because the business didn’t have control oier data qualitt or M M. Nice tool eut ueerlt useless i the underlting data isnyt under control.. ITsIovilvemeot. Most recommended getng the corporate BI team iniolied prior to deploting iisual discoiert tools to aioid creatng proelems down the road. Mant respondents worried aeout proli eratng spreadmarts, which they would eventually be asked to manage on an enterprise basis despite data quality, scalability and performance limitatons. “These tools are creatng a lot o low-value work for the BI team. said one. Another said, “The tools are power ul eut need to ee goierned.. Tr ioiog. Although visual discovery tools support self-service, most respondents insisted that users require lots of training to become pro cient users. In act, one who uses the tool or discoiert said, “.ew users haie the apttude and desire to eEplore data and tease out those nuggets o gold.. Another who uses the tool or dasheoard deielopment said, “These tools require highlt slilled people to euild solutons.. T rget. (ome respondents also said to picl target applicatons or iisual discovery carefully. One said, “Start small with a high value data set that is not currentlt eeing leieraged.. Another said, “Be speci c aeout what the tool deliiers and deplot it onlt or that.. (ome said the tools are great for prototyping dashboards prior to enterprise development. Another said that unless tou haie a “de ned deplotment model. tou are likely to be swamped with individual requests later on.

Most respondents recommended getng,the,corporate BI team involved prior to deploying visual discovery tools to avoid creatng,problems down the road.

BENCHMARK REPORT


Summ ry VISUALsDISCOVERYsTOOLSsAREsPOPULARsTODAY. Once they enter an organi aton, thet spread quicllt. Business users loie the tools eecause thet are highlt iisual, interactie, analttcal and aiordaele. Moreoier, thet can ee used to create departmental dashboards, so they serve both power and casual users. rgani atons get a lot o eang out o eiert dollar thet spend on iisual discovery tools. But visual discovery tools are not a panacea for every BI ill, despite what vendors claim. They are the newest low-cost, analttcal tool that power users can use to create data silos and spreadmarts. To gain the ull eene t o iisual discoiert tools, organi atons must ensure that tool users donyt independentlt source data that alreadt eEists in the corporate data warehouse. IT needs to get involved to ensure the consistency and quality of data. Finally, despite their self-service moniker, visual discovery tools are not easy to use as authoring tools. (ome, in act, require a great deal o data and programmatc slills.

To gain the full benefit,of,iisual,discovery tools, organizatons,must,ensure that tool users don’t independently source data that already exists in the corporate data warehouse.

ABOUT THE AUTHOR


CLAUDIAsIMHOFF Ph.D., is the president of Intelligent (olutons, a consultancy on business intelligence technologies and strategies. She is a speaker and internatonallt recogni ed eEpert and series as an adiiser to mant corporatons, uniiersites and leading technologt companies. She has co-authored ie eools and more than 100 artcles on these topics. (he is also the ounder o the

Boulder BI Brain Trust, a consortum o leading independent BI analysts, consultants and practtoners. Email her at [email protected].

Visual Discovery:,Perceptons,and, arnet,Trends

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