Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    software developer using ai
    How Data Analytics Helps Developers Deliver Better Tech Services
    8 Min Read
    ai for stock trading
    Can Data Analytics Help Investors Outperform Warren Buffett
    9 Min Read
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
    financial analytics
    Financial Analytics Shows The Hidden Cost Of Not Switching Systems
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Top 10 Keys to a Successful Business Intelligence Deployment
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Best Practices > Top 10 Keys to a Successful Business Intelligence Deployment
AnalyticsBest PracticesBusiness IntelligenceExclusiveKnowledge Management

Top 10 Keys to a Successful Business Intelligence Deployment

Yellowfin
Yellowfin
5 Min Read
SHARE

At Yellowfin, we understand that implementing a Business Intelligence (BI) solution, particularly for the first time, can be a daunting process.  Getting it right from the beginning is critical for:

At Yellowfin, we understand that implementing a Business Intelligence (BI) solution, particularly for the first time, can be a daunting process.  Getting it right from the beginning is critical for:

  • Fostering a favorable business culture around reporting and analytics
  • Securing ongoing executive backing
  • Your career

We’ve compiled a shortlist of non-negotiable cultural and technical elements that must be practiced and adhered to to ensure success.

More Read

free access to BI…is business intelligence slowly becoming a commodity?
3 Major Reasons VPN Can Improve Data Security
Long Term Financial Planning with Financial Data Analytics
How Big Data is Changing the Face of the Global Marketplace
Demand for Data-Savvy Cybersecurity Professionals Grows In 2021

1. Identify potential issues before they become a reality:  Develop a comprehensive roadmap to success, carefully sign-posting potential project stumbling blocks, so that appropriate solutions can be devised.  Consider such issues as: Are your data sets complete and accurate?  Do you have a master data management framework in place?  Is your delivery team adequately staffed and appropriately skilled?  Do we have sufficient hardware to support our BI goals?

2. Start the evaluation process early: Most BI vendors will assert that their product contains all the latest technological wizardry and addresses the specific needs of your industry or organization flawlessly.  However, this will not be the case.  Taking the time to conduct a thorough proof of concept will reveal a myriad of underlying differences.  There is no such thing as “the best” BI tool – select the one that best suits your needs.

3. Let business users make the final purchase decision:  BI is designed to increase the capacity of business people to meet and exceed their workplace goals.  The BI solution that they perceive to be the most intuitive and helpful is the right one for your business. 

4. Fast, easy and seamless – select a single-integrated BI application:  Many BI tools are an amalgam of moving parts, creating a system that is difficult to integrate, manage and navigate.  Reduce user resistance and implementation timeframes by selecting a single-integrated BI solution.

5. Ensure your chosen BI vendor will/can support you:  Determine your vendor’s capability (and willingness) to deliver adequate services support and training throughout the implementation process.  Obtain documented agreement on the level of services, support and training incorporated in the initial purchase order as well as expected timeframes to resolve issues.

6. Define user groups and requirements:  Carefully divide your user community into definitive user groups (finance, marketing, sales, etc).  Project requirements can be driven and defined according to the most pressing/immediate reporting needs of each defined group.

7. Under promise and over deliver:  Create and follow a realistic delivery schedule – don’t try to do it all at once.  Promising analytics for all and then delivering a handful of inactionable reports for a few will reduce user confidence in the usefulness of the BI project as well as the likelihood of ongoing executive sponsorship.  To avoid this situation, develop reports for one user group at a time, say the sales team, moving onto the user group of next highest priority in a systematic fashion.

8. Secure support from data source owners:  Your BI tool will combine data from a range of different data sources.  For your BI project to deliver deep operational insight and the value of near real-time reporting, secure cooperation from all departmental or individual system data owners.

9. Incorporate representatives from defined user groups into the project delivery team: Let user demand drive product development to ensure that deliverables are always connected to business needs.  Not only will this collaborative approach ensure the continued usefulness of your BI project, doing so will nurture a feeling of ownership within your BI community, which will help you achieve sustained user adoption.

10. Ignore testing at your peril:  A thorough testing process prior to any, but particularly your first, phased rollout is essential.  If the project is launched with glitches and slow query response times user drop-off will swiftly follow.

Where to next?

Can you think of some other critically important factors to consider when deploying BI for the first time?

 

TAGGED:best practicesbusiness intelligenceBusiness Intelligence ROI
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

software developer using ai
How Data Analytics Helps Developers Deliver Better Tech Services
Analytics Big Data Exclusive
ai for stock trading
Can Data Analytics Help Investors Outperform Warren Buffett
Analytics Exclusive
data security issues with annotation outsourcing
Data Annotation Outsourcing and Risk Mitigation Strategies
Big Data Exclusive Security
NO-CODE
Breaking down SPARC Emulation Technology: Zero Code Re-write
Exclusive News Software

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

enterprise software development
Big DataExclusiveSoftware

The Effect of The Data Revolution in Enterprise Software Development

6 Min Read
big data in HR
Analytics

Data Analytics Can Bolster HR in Niche Industries

7 Min Read

Smart Business Intelligence Applications For the iPhone in 2016

5 Min Read

Alteryx 8.5 and the Data Artisan: Focusing on the User Experience of the “New Boss”

8 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?