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
    composable analytics
    How Composable Analytics Unlocks Modular Agility for Data Teams
    9 Min Read
    data mining to find the right poly bag makers
    Using Data Analytics to Choose the Best Poly Mailer Bags
    12 Min Read
    data analytics for pharmacy trends
    How Data Analytics Is Tracking Trends in the Pharmacy Industry
    5 Min Read
    car expense data analytics
    Data Analytics for Smarter Vehicle Expense Management
    10 Min Read
    image fx (60)
    Data Analytics Driving the Modern E-commerce Warehouse
    13 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: How to Achieve Equilibrium Between Business Users and IT
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 > How to Achieve Equilibrium Between Business Users and IT
Best PracticesBusiness IntelligenceCollaborative DataData ManagementData VisualizationData Warehousing

How to Achieve Equilibrium Between Business Users and IT

Editor SDC
Editor SDC
5 Min Read
SHARE

A geochemist named James Lovelock once theorized that a fundamental characteristic of all life is not just the need to consume energy and discard waste. It’s also the use of the planet’s atmosphere as a medium for this cyclic exchange.

A geochemist named James Lovelock once theorized that a fundamental characteristic of all life is not just the need to consume energy and discard waste. It’s also the use of the planet’s atmosphere as a medium for this cyclic exchange.

Finding that, unlike Earth, the atmosphere of Mars is not in equilibrium with the planet’s surface, he concluded that living organisms make their environment suitable for life. This notion of planetary homeostasis — that Earth is a unified, cooperating system — challenged just about everyone’s thinking.

Substitute a few words and Lovelock’s theory – named the Gaia hypothesis, after the Greek goddess of Earth – becomes a useful metaphor for understanding why today’s business intelligence (BI) initiatives tend to face a significant amount of internal conflict, preventing them from delivering actionable insights that drive competitive advantage and overall business success as effectively as possible. Simply put, many organizations have yet to transform their BI environments into any semblance of a unifying, cooperating system.

More Read

Image
Most enterprises have a digital transformation strategy, but few have completed it
Enterprise Data World 2009
The Cloud and Physical Security
EMC Survey Differentiates BI and Data Science
At-a-Glance Guide to Analytics at SAPPHIRE NOW Madrid

Just as colliding asteroids, platonic shifts and geochemical reactions transformed Earth and Mars over time, myriad forces are collectively reshaping the world of business intelligence. These forces have been at work for a number of years now, driven by several interrelated phenomena. Among them: the proliferation of both structured and unstructured data, the explosion of mobile networks and devices for accessing the data, and the advent of a new breed of cloud-based, self-service web interfaces. These interfaces enable business users to use the data to dynamically generate actionable insights on an ad hoc basis via dashboards that contain a variety of interactive visualization and in-memory reporting tools.

The Gaia hypothesis metaphor speaks to the importance of equilibrium, which in this case means significantly reducing the amount of tension that exists between the IT organization and business users that has long been the hallmark of traditional BI initiatives.

According to the new Gleanster benchmark report Agile Business Intelligence, 59% of Top Performers cite the need to empower non-IT professionals with the ability to gain direct access to data as a primary reason for investing in new BI initiatives. This need for empowerment should guide the selection of tools that give the business user the ability to define data requirements. Self-service reporting can alleviate the inherent tension that exists, by putting data access and interactivity in the hands of business users so they can become more independent and self-reliant.

The question is: What is the right mix of data access and who should drive reporting? While some organizations place this responsibility squarely on the shoulders of the IT department, others are attempting to place it within business departments, viewing IT as little more than another vendor to supply data to existing tools. Both approaches invite failure.

Top Performers understand the paradox of capability and cost. If IT is disconnected from the business completely, then it will not be in a position to deliver data that drives strategic decisions. Likewise, if the business is disconnected from the realities of managing and integrating complex data, then it runs the risk of producing invalid results.

At the same time, given “too much” access to the underlying data infrastructure, business users may create performance challenges in operational systems. With too little access, they may feel stymied and constantly subjected to unnecessary bureaucracy.   

So, what is the right answer? Is it to deploy a full data exploration sandbox environment? Or to embrace a data funnel approach “with guardrails” – i.e., an approach that aims to provide the right mix of capability and constraint with carefully-orchestrated levels of data access?

A new Deep Dive analyst report, from which this article is partly excerpted, suggests that there’s a great deal of merit in the latter approach – that is, giving the business user the ability to configure and generate custom reports within a limited set of parameters. Ideally, it allows business users to interact with the data without opening up a veritable can of worms.

 

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

composable analytics
How Composable Analytics Unlocks Modular Agility for Data Teams
Analytics Big Data Exclusive
fintech startups
Why Fintech Start-Ups Struggle To Secure The Funding They Need
Infographic News
edge networks in manufacturing
Edge Infrastructure Strategies for Data-Driven Manufacturers
Big Data Exclusive
data mining to find the right poly bag makers
Using Data Analytics to Choose the Best Poly Mailer Bags
Analytics Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

8 Suggestions for Every Data Protection Strategy [VIDEO]

1 Min Read

BI Business Requirements: When Perfect is the Enemy of Good

2 Min Read

The Secrets to Big Data and Information Optimization Revealed in 2013 Research Agenda

11 Min Read

Giant Brains: Did Edmund Berkeley Predict Email, the Internet, ERP Systems and the iPhone in 1949?

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 chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots
ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

Quick Link

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

Sign in to your account

Username or Email Address
Password

Lost your password?