We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
    cybersecurity efforts
    How Behavioral Analytics and AI Are Redefining Cybersecurity for Boca Raton Businesses
    14 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: What Should Companies Consider Before Investing in a BI Solution?
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > What Should Companies Consider Before Investing in a BI Solution?
Business IntelligenceCommentary

What Should Companies Consider Before Investing in a BI Solution?

Peter James Thomas
Peter James Thomas
2 Min Read
What Should Companies Consider Before Investing in a BI Solution?
Photo by Uli-W on Pixabay (https://pixabay.com/photos/internship-company-business-work-3157269/)
SHARE

  

 
The following is a lightly edited transcript of a reply I posted to a question asked on the LinkedIn.com Business Intelligence Group. This was entitled What should companies consider before investing in a BI solution?.

I suggest some of the following:

  1. What business problems would a BI solution address?
  2. Within these, what questions do people want to ask and what action will the answers lead to?
  3. Why can’t these people get the answers today, or – if they can – what is wrong with them (incomplete, inaccurate, not detailed enough etc.)?
  4. What is the business impact of the lack of these answers (poor decision-making, missed opportunities, inefficient processes, poor monitoring, lack of tools to manage people’s performance)?
  5. If these questions were to be answered, broadly speaking, which different data sources would need to be brought together (assess different country / divisional systems and different types of systems – sales, Finance, manufacturing, distribution, marketing, complaints, external data, others)?
  6. How aligned are the various different elements within these (e.g. customer records, products, territories etc.)?
  7. To what level is the data required to answer the questions identified above captured (are there gaps and does new data need to be entered)?
  8. How accurate is this data (does it actually reflect business events)?
  9. What is the overall quantity of both historical and current data that needs to be looked at and how much of this regularly changes?
  10. How frequently will users need to ask questions and how up-to-date does the answer need to be?
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Synthetic Data vs Real Web Data: Comparison, Limitations, and Collection Methods  -- AI-generated illustration
Synthetic Data vs Real Web Data: Comparison, Limitations, and Collection Methods 
Big Data Exclusive
Illustration of mobile analytics dashboards with ad performance charts connected to backend databases
11 Best Sisense Alternatives for Embedded Analytics
Business Intelligence Exclusive
Analyst points at colorful circular data dashboard on screen - information technology business metrics
How Fragmented Workplace Tech Undermines Reliable Business Metrics and Reporting
Cloud Computing Exclusive Infographic IT
Using Multi-Source Data and Analytics to Detect Operational Drift Across Franchise Networks -- AI-generated illustration
Using Multi-Source Data and Analytics to Detect Operational Drift Across Franchise Networks
Exclusive Infographic

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Advanced Analytics
Business IntelligenceData VisualizationPredictive Analytics

Advanced Analytics

10 Min Read
Google+, Does it have Potential for Business Use?
Best PracticesCloud ComputingKnowledge ManagementNew ProductsSocial Data

Google+, Does it have Potential for Business Use?

9 Min Read
Shining Some Light on Collaborative BI
Business Intelligence

Shining Some Light on Collaborative BI

3 Min Read
Criteria for Determining Which SaaS Platform to Choose
Big DataCloud ComputingCRMData QualityExclusiveSoftware

Criteria for Determining Which SaaS Platform to Choose

2 Min Read

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

The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?