dashboards as easy to use as google

7/30/2019 Dashboards as Easy to Use as Google

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Dashboards

as Easy to Use

as Google

CITO ResearchAdvancing the Craft of Technology Leadership

March 2012

Sponsored by QlikView


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ContentsIntroduction 1

Te Diference Between Searching the Web andraditional Dashboards 2

What Google-Like Qualities Must be Kept 6

Whats Diferent? 7

Te Results 9

QlikView:

Helping You Google-ize Your Dashboards 10


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1Dashboards as Easy to Use as Google


IntroductionIn our personal lives, when we want to nd inormation, our rst stop is Google. We

enter search terms and a list o documents appears. We look at the documents. I they

are not what we want, we change the search terms. I another question arises, we

search or related inormation. The eeling we get rom this experience is satisying,

smooth, and eortless.

Technologist George Gilder once explained Googles success in the context o what he

calls Gilders Law: it wastes what is abundant (as determined by rapidly alling prices)

and conserves what is scarcetime. Google places a premium on peoples time, aim-

ing to return search results in as little as a twentieth o a second. Such perormance

not only demands peta-scale server arms, but also an utterly simple interacestart-

ing with its amously uncluttered homepageand the interactive elegance seen in

applications like Google Maps. Users are able to answer any questions they ask.

In the business world, we are oten rustrated because nding inormation, searching

or answers, and perorming analysis is so unlike Googles simplicity. Instead o an

intuitive, straightorward user experience, we are oered a conusing, cumbersome

menu o precomputed answers rom which to choose. I we want to explore on ourown, we are let struggling with even more complicated tools or antiquated spread-

sheets. The IT sta wants to do better, but their hands are tied by traditional busi-

ness intelligence systems hardwired limitations that deliver predetermined, inexible

query output to users.


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The business equivalent o the Google search interace is the dashboard, which is a

collection o inormation and analysis tools that are ocused on providing detailedbusiness answers specic to an end users role and needs. Compare Googles intuitive,

accessible approach to the numbingly detailed reports and mind-bending queries o

business intelligence (BI). To make the world o BI provide the same ease and reedom

in asking and answering questions that Google provides consumers, we must nd a

way to Google-ize dashboards. This means creating simple, intuitive yet powerul

tools that are both customizable and scalablea tall order or most BI systems. It will

require abandoning the SQL1 query mindset and adopting new orms o interactivity,

such as using in-memory associative search, which allows users to pull answers to-

ward them rather than accept whatever IT pushes at them. The result is whats known

as living dashboardsapplications that can help identiy leading indicators and allowusers to share them throughout the organization.

How can we adapt qualities o Google to build better dashboards? This paper explains

the similarities and dierences between Google searches and traditional BI and why

Google-izing BI is the rst step toward creating living dashboards.

Te Diference Between Searching theWeb and raditional DashboardsComparing Google with traditional dashboards requires more analysis than it might

seem at rst. Google does a great many things well, starting with searches, but the one

thing it does not do well is actually answer questions. Unlike BI, which sits through

data and runs calculations, Googles keyword searches return the entire Internet as

their answer, albeit sorted by relevancy determined in large part by analyzing which

pages are the targets o links. The reason this works in practice is because the Web is

text and document based. But corporate data is typically numerical and highly dimen-

sionalanswers are hidden in the numbers and must be computed, not searched.

Corporate data has no network o links to help tools gure out whats important.

1 SQL (Sequel; sometimes reerred to as Structured Query Language) is a programming language designed

or managing data in relational database management systems.


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A simple example illustrates the dimensionality o business data. I a dashboard

returned a list o unpaid invoices due a company, that wouldnt answer the questiono the total accounts receivable in the next 30, 60, or 90 days. The total o the receiv-

ables is one dimension, the date due is another, and both are linked in the invoice

inormation.

Traditional BI is less a search engine than a computation engine. Most o BI inrastruc-

ture is aimed at computing answers to narrowly predened questions rom a set o di-

mensional data. The answers are not pulled by users based on their emerging interests

but pushed according to a predetermined set o needs (see Figure 1 or a comparison

o Google and traditional BI). The architecture o traditional BI is let over rom an era

in which computing power was the scarce resource to be conserved. But everything

has changed. Repeated cycles o Moores Law2 have made memory cheap and hard-

ware exponentially more powerul. The number o 64-bit cores on an Intel processor

is doubling every eighteen months while the cost per gigabyte o solid-state memory

is plummeting. Now its possible to load entire databases into memory on comput-

ers o any size or instant in-memory analysis, something that was once prohibitively

expensive or even impossible. Traditional BI tools dont reect this. Their architecture

was designed to cope with resource bottlenecks; today, BI itsel is the bottleneck.

2 Moores law is a rule o thumb in the history o computing hardware whereby the number o transistors that

can be placed inexpensively on an integrated circuit doubles approximately every two years.


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Figure 1: Google Searches Compared with Traditional Dashboards

Google searches are aboutthe relevancy of documentsdetermined by links

Traditional BI searches are aboutcomputing the value of queriesagainst dimensional data

Using Google is like having a dynamicconversation that goes in new directions

Using traditional dashboards is like havinga predened conversation with the samequestions answered over and over again

The Google search engine compares thekeywords to the index of all documents onthe Internet

Traditional dashboards show the results ofseveral queries specied at the time thedashboard was built

The page rank algorithm uses the popularity oflinks on the Internet and other techniques tosort the documents by relevance

The predened queries are executed againstdimensional data: many tables of dataorganized by temporal, spatial, logical, orother relationships

At design time, experts use SQL to craft queriesto express relationships between data anddene aggregate measures

The results answer predeterminedquestions using tables of data, aggregates,and graphical displays that change as queryterms are changed

The result is a list of documents that can beinspected and used to formulate new questions

A Google search consists of keywords to answerthe questions the user has right now


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Whats needed is a usion o the two approaches that oers BIs computational abilities

through a dashboard as simple and as scalable as Google. A Google-ized dashboardwould allow you to discover associated dimensional data in an interactive, responsive

way that allows the conversation to go where the business users ideas take it.

For example, in the unpaid invoice scenario described earlier, a Google-ized dash-

board would allow the invoices to be sorted by criteria other than those planned.

New aggregate measures and graphics could be added and incorporated into the

dashboard. New data could be added by the business user, such as a database show-

ing credit ratings, the last 30 days stock price, or delays in SEC lings.

To understand what a Google-ized dashboard is we must be specic. Here is a sur-

vey o aspects o Googles interace that must be retained and the new capabilitiesneeded to make this vision a reality.


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What Google-Like Qualities Must BeKept?To create a Google-ized dashboard, we need to retain the ollowing Google qualities:

User control o the analysis. Users should control the back and orth ow o

questions and answers. Users should pull the answers out o the data, not have

predened answers pushed at them.

Sel-service. No one needs setup or training to use Google. A Google-ized dash-

board should work the same way.

Simplicity and ease o use. What could be simpler than a search box? Or more

ubiquitous? Googles interace is querying stripped to its essence. Everything else

is clutter and complications.

Speed o response. Google returns results in as little as a twentieth o a second

because users do not want to wait. Speed is everything. Nothing is more precious

than time.

Able to quickly see and inspect results. Google may do a poor job o answering

questions, but it does a antastic job o ranking, sorting, and presenting results. It

gives you everything you need to decide the relevance o a resultnothing more.

Able to quickly refne questions. Didnt nd what you were looking or? Type

something else into the search box and try again. Theres no need to construct an

elaborate query.

No penalty or volume.Theres no such thing as too broad a Google search. Typethe letter A into the search eld, and instead o returning an error, Google in-

stantly lists the rst o 15,490,000,000 results (starting with the entry or A in

Wikipedia). This is a ar cry rom BI, where too broad a query can bring the system

to its knees. A Google-ized dashboard doesnt penalize you or thinking big.


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Whats Diferent?The obvious, or starters: searching or a string o text is a wholly dierent propositionthan computing metrics rom relational databases. To understand database records

through visual inspection in the same way that web pages are understood is next to

impossible. You need to aggregate data and graph it to see the story told by tens o

thousands o records. In addition, instead o just looking at one document at a time,

dimensional data involves connecting many tables. An invoice or a company may

be connected to the database showing payments using a company identier as a

key. A Google-ized dashboard would make connecting tables together much easier,

automatically providing a list o associations between data sets loaded into its own

memory. Users can dene the dimensions o data, that is, collections o related tables,based on the needs o their analysis.

A Google-ized dashboard o the type described in Figure 2 would solve BIs enduring

dilemma: BI can tell you known unknownscommon, dependable metrics such as

sales and customers by regionbut it cant tell you unknown unknowns, the ques-

tions you havent thought to ask. The ormer is the province o traditional dashboards

and KPIs; the latter is where insights are ound. We call this Business Discovery.

A Google-ized dashboard would be able to change search criteria on a users whim

and track down answers pronto. I the starting point or a sales dashboard showed

products sold by region, a Google-ized dashboard would quickly allow examination

o aggregated data or groups o regions or inspection o the individual invoices or

each product by region. One reason Googles interace is so simple is because its re-

sults are simple. But a Google-ized dashboard would oer users more options, such

as the ability to easily aggregate sums, averages, statistical unctions, and equations

with a ew clicks so that custom metrics can be created, saved and reapplied. Being

able to choose rom many dierent ways o displaying data enables the dashboard

to be simple, to show only what is needed or a particular situation. In other words, a

dashboard would have dozens o dierent charts, tables, graphs, and other dynamic

visualizations available.


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Figure 2: A Google-ized Dashboard

A business discoverydashboard starts with dataand tools for analysis, butallows for changes andadditions

Queries are replaced bypoint-and-click navigation andselection of in-memory data

Users direct the path of theanalysis based on aconversational exploration ofdata. New data is added whenneeded

Results (data, aggregates,and visualizations) areupdated instantaneouslyas selection criteriachange

Business Discovery

The ease of use of Google is preserved in an environmentfor understanding dimensional data


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Te ResultsAs Google and so many others have ound, the real value lies in empowering users tocontrol the means o analysis. No IT department is as scalable as all o the colleagues

it serves. What they need isnt Google, per se, but what we are calling a living dash-

board, a dashboard that preserves the direct simplicity o Googles interace, but has

the mechanisms needed to handle dimensional data and that enables Business Dis-

covery easily and at scale.

Unlike traditional BI and its predened analytics a living dashboard applies the best

practices o Google to exploring dimensional data. Living dashboards enable Busi-

ness Discovery by allowing business users to:

Ask and answer questions themselves, without complicated queries or IT

middlemen

Add new data sources at will, in any combination required or the task at hand

Get answers quickly, almost instantly. No more waiting or reports to run

Change the dashboard themselves on the y without the help o IT

Share the dashboard with others. Because whats the use o creating new met-

rics i you cant share them?

Living dashboards nd results in time to matter, and this newound visibility increases

accountability. Seeing the outcome o decisions increases the understanding o what

works and what does not. Ineective behavior and successul practices can be moreeasily identied. As processes are better understood, leading indicators o problems

or opportunities come to light. With the right metrics in place, a manager can hold his

team accountable or what matters in an open and transparent manner, improving

everyones perormance. I good metrics change awareness, then awareness invari-

ably changes behavior. And this awareness can emerge anywhere in the company

an individual, a team, a divisionand quickly propagate via their dashboards.

Over time, a virtuous circle is created. Because these dashboards are prototyped,

improved, and shared by individual users, they no longer require the attention and

resources o IT. As the speed and ease o conguration increase, the cost o implemen-

tation alls and ROI rises accordingly. The speed o adoption becomes paramount. AsGoogle has ound, the aster it scales, the greater and more rapid the ROI. The cheaper

and easier it becomes, the more willing people are to experiment with itto discover

more leading indicators and more previously hidden insights.


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The virtuous circle picks up speed. Resources once pushed to the business users by a

central committee are pulled by the users themselves, who have the best understand-ing o how to deploy them and a real appreciation o their benets. In the end, the en-

tire notion o BI is ipped upside down: its undamentally about business discovery,

not delivery; its bottom-up, not trickle-down; and its putting the tools or innovation

in everyones hands, not just the experts. It s simplicity itsel.

QlikView: Helping You Google-ize YourDashboardsQlikView is a new kind o business intelligence sotware that lets you stop guess-

ing and start knowing how to make aster, smarter decisions. Figure 3 shows how

QlikView creates a living, Google-ized dashboard.


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Figure 3: A QlikView Google-ized Dashboard

List boxes allowdata to be selectedwith a few clicks

What is selected andnot selected is shown

instantly

Graphics are updated

instantly as selecteddata changes

Users canchangethe list

boxesand

graphics

QlikView returns results immediately

because all data is stored in memory

Because all data is inmemory and related,it can be explored ina hands-on way, by

inspection andexperimentation,

not by queries

Each table isconnected to the

other tables relatedto it when the data

is loaded

Users can add tableson their own

without the help ofIT


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QlikViews goal is simple: to provide the tools or living dashboards, helping custom-

ers explore and visualize data that enables them to personally nd answers and driveinnovation. QlikView takes an alternative view o BI that can be summarized in three

steps:

Consolidate: Identiy related data sets, map the associations between them, and

load it all into memory

Search: Explore the data using point-and-click controlled list boxes, which dis-

play selected and deselected data as well as aggregates. Inormation is displayed

and updated instantly as selection criteria change

Visualize: Maps, charts, and assorted graphics can be created and instantly

updated

QlikView aims to increase your chances o making genuine business discoveries andeliminates much o the grind:

No complicated queries, no middleman: You click to select data and click again

to deselect it

Matching and non-matching data are displayed: You can see what is highlight-

ed, and what is not highlighted. You can see which data was excluded and see

what happens when you mix it in

No waiting:The answers are right in ront o you

The idea behind QlikView is that a simple process or asking questions and encourag-

ing individual exploration leads to better answers, insights, and innovations. It does

this by replacing database queries and cubes with its associative in-memory architec-ture. Rather than precalculating answers, the sotware loads data sets into memory

and maps the associations between them. The users job is to understand the data,

not to grapple with the technology. You can ask as many questions as you like un-

til you discover important insights. Because its all done in-memory, the answers are

returned instantly and updated continuously. Your BI is no longer as good as your IT

departments last cubeits as good as the questions you ask.

This paper was sponsored by QlikView and created by CITO Research

CITO Research

CITO Research is a source o news, analysis, research, and knowledge or CIOs,

CTOs, and other IT and business proessionals. CITO Research engages in a

dialogue with its audience to capture technology trends that are harvested,

analyzed, and communicated in a sophisticated way to help practitioners solve

difcult business problems.

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