anatomy of a modern bi dashboard

ANATOMY OFA MODERNDASHBOARDRyan Goodman@[email protected]

Modern dashboards contain summarized, interactive visualizations. The desired outcome to quickly and easily communicate performance has not changed since their rise in popularity over the last 10 years. However, the technology choices, features, and approaches have advanced. Mobility, cloud and data exploration technologies have helped expand the personas who can create and consume dashboards.

This presentation highlights modern approaches for delivering dashboards...

Copyright: Ryan Goodman

WHO will consume information in dashboards and who will create them?

WHY those personas need a dashboard?

WHAT action or outcomes occur from usage of the dashboard?

WHERE will they access the dashboard (desktop, mobile, inside of CRM, etc)?

WHEN: do you need the dashboard?

HOW does the dashboard and it’s contents support your key organizational objectives?

People Before FeaturesWithout clear answers to these questions, your approach does not matter...


Dashboard Approaches

Defined by data acquisition, design process, and results.

1. Component Based Dashboard Design

2. Report / Exploration Based Dashboards

3. Widget dashboard

4. KPI / tile dashboard

5. Embedded Analytics / Dashboards


Component Based Dashboard Design

Component based dashboard results provide a level of “self service” exploration, allowing business users to modify results with pre-defined data queries.

The result of many ad-hoc dashboards produce similar results as traditional enterprise reporting. Additionally some platforms require a deeper level of planning and specialized skills to ensure success.


Image Source: Antivia DecisionPoint

Component based dashboards provide a library of visualizations, input controls, and data connections / objects which can be composed into an interactive dashboard apps.

Report / Exploration Based Dashboards

Flexibility to manage data configuration and design workflow to explore data. Simplified workflow that is better for team based projects.

Limitation for customization and and typically missing opportunities and components for more complex workflows and user experience.


Image Source: Microsoft

A summary dashboard is assembled using existing BI reports or data exploration visuals as building blocks to assemble dashboard summaries.

Widget dashboard

Widget dashboards are benefit from best practices and powerful built-in features and eliminates the chance customer created defects and maximize adoption through applied best practices.

Widget based dashboards may be limited in data sources, form factors, or configurability, but that is typically by design to ensure fast design and deployment.


Image Source: Databox

Widget dashboards provide pre-packaged “ready-made” analysis capabilities and/or data-source specific modules which are rapidly assembled and deployed to business users.

KPI / tile dashboard

KPI tile dashboards are highly effective for management and executive dashboards and create fast navigation between a wide range of sources and subjects.

As the number of tiles grows so does the time required to navigate, explore, and trends and locate the most important figures.


Image Source: Domo

A new take on report / exploration dashboards are KPI tile dashboards, which provide an additional layer of summarization, and emphasizes for most important figures before drilling into supporting detailed analytics.

Embedded Analytics / Dashboards

Embedded dashboards put analytics in the hands of users where they work, which in many cases can be integrated closer to business workflows and activities.

Most embedded dashboard capabilities are limited in scope and ability to leverage data from outside of the platforms for which they are embedded.


Image Source: LogiAnalytics

Features are Moving Targets: Skills required (analyst, statistical, SQL, design, coding, scripting, CSS, etc)

Desktop or cloud design and deployment

Average time to create a dashboard (with data available)

Data Connectivity options Excel, web service, on premise, cloud

IT maintenance required Software footprint (memory, servers, cores)

Scalability impact on performance and footprint

Data volume restrictions client and server

Extendable: Client visualizations, data connections, logic, and platform

Multi-data source support, joining, blending.

Drillable to transactional data Support and learning resources from vendor.

Community size, and engagement model

Embeddable inside 3rd party apps and portals (Sharepoint, Salesforce.com, etc.)

Business logic and scripting requirements

End user filtering, ranking

Real-time alerts data OLAP data source support Public and private cloud options Security options and SSO. Built in security or generic SAML

Proprietary data connectivity Big data spark / hadoop Support for statistical languages like R Localization, language support

Geospatial functions and analytics Support for spatial data types and queries

Custom web services REST, SOAP, etc.

Data source joining, abilities.

Data preparation and blending Mobile phone and/or tablet support by OS

Collaboration features, email, annotation, sharing

Data filtering and analysis components

Sophistication of tabular data analysis (crosstab, vertical table)

Search - client and/or server Visualizations (too many to list) What if analysis calculations and user inputs

Completeness of feature and ease of implementation are inconsistent between tools.


What’s Next?

Check out AnalyticsonFire.com for the next article in my series.

http://bibrainz.com/aof/author/rmgoodm/

anatomy of a modern bi dashboard

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