InetSoft Webcast: Self-service BI and Data Mashups

The DM Radio Webcast, “The Last Mile: Data Visualization in a Mashed-Up” from Information Management continues. The transcript of that Webcast, which was hosted by Eric Kavanagh and included InetSoft's Product Manager and BI consultants William Laurent and Malcolm Chisholm resumes below:

Eric Kavanagh (EK): That is a really good point. In fact, let’s do this. Let’s focus the roundtable on the evolving role of IT and what IT can take out of this, because things are changing, and you know the old rule of thumb is you can only withstand change so long before it steamrolls right over you.

This whole theme of the evolving role of IT really seems to come into focus here as we’re talking about self-service BI and dashboards and data mashups and so forth.

Alan, let’s talk about this. You have a lot of experience in IT. It is true. I think that a lot of IT people are getting more business savvy, and a lot of business people are getting more IT savvy, and I think also this whole emergence of software as a service is enabling business users to get functionality that they need and start getting things done.

So there does seem like there is an evolution in the role of IT, what’s your take on that and what advice can you give to both sides to come together?

Wille: I don’t know if can give advice, but there definitely are some things that we see consistently, and also best practices that we try share with some of customers. IT is definitely the right place to start as far as making sure the data is connected properly, the performance and the security is handled properly.

But there is always somewhat of a disconnect between the dashboard module that IT develops and how business has to slice and dice and analyze the data. And I don’t think there is a right or wrong, but there is a happy medium where IT can provide not a fire hose, but a partial data feed that then has the logic in it to allow some non technical users to slice and dice the data without a lot of training.

And I think that actually ties back, and maybe that is the way forward for mashups. We were saying that for self-service BI, it just doesn’t seem to be fulfilling the dream, but on the technical side it is moving forward. So maybe it is paying attention to how do we offer these mashable pieces that do allow them to be attached visually to other data pieces, or allows the business end user to slightly modify the data so that they can see the right time portion, the right context, the right overlay, the right drill-down level, et cetera. So maybe there is a happy medium in there somewhere.

Byron Igoe (BI): Eric, I would love to give you a demo. I hear people talking about, oh, the technology is there, but the self-service isn’t. Our whole paradigm is built around the maximum amount of self-service to the end users. And that starts at the mashup level and goes all the way up to the dashboard level. And IT’s role in all of this is around the initial setup of the underlying sources, the raw data sources, establishment of security best practices and governance, and then making sure performance is right. And essentially they are building this meta data layer where the users can accomplish anything they want to. And it’s provided with drag and drop, point and click interfaces that don’t require any programming, any APIs, nothing technical at all. So either the business users or the business analysts, essentially anyone who is at all facile with Excel, can really play around in their own sandbox and do whatever they want.

Wille: Yeah, I think that works very well if you have got a user that is into the data. But an occasional user, or if you are talking about pervasive BI throughout the entire organization, does it work for them as well, or do they need something that is a little more locked down?

What Are the Pros and Cons of Locking Down Self-Service for the Occasional User of BI Dashboards?

Locking down self-service for occasional users of business intelligence (BI) dashboards can have significant implications for organizational efficiency, user satisfaction, and data governance. Below is an in-depth exploration of the pros and cons of such an approach:

Pros of Locking Down Self-Service BI for Occasional Users

1. Enhanced Data Governance and Security
   • Controlled Access: Limiting self-service reduces the risk of unauthorized access or inadvertent exposure of sensitive data.
   • Standardized Reporting: Prevents data inconsistency by ensuring that occasional users rely on pre-approved reports and dashboards.
2. Improved Dashboard Integrity
   • Prevention of Errors: Non-expert users may unintentionally create flawed reports or dashboards that lead to incorrect decisions. Locking down self-service minimizes this risk.
   • Uniform Design: Keeps dashboard formats consistent, which aids in better interpretation and decision-making.
3. Reduced IT Support Burden
   • Focused Assistance: By limiting self-service, IT can focus on creating a smaller number of high-quality, validated dashboards rather than troubleshooting user-created issues.
   • Streamlined Training: Occasional users require less training if they only consume rather than create content.
4. Efficiency Gains for Power Users
   • Reduced Noise: Power users or analysts can work with cleaner, well-curated datasets without dealing with mismanaged inputs from occasional users.
   • Optimized Resources: IT can allocate resources more effectively to those who need advanced tools and capabilities.

Cons of Locking Down Self-Service BI for Occasional Users

1. Reduced Flexibility
   • Delayed Insights: Occasional users might face delays in obtaining the specific data or reports they need, as they must wait for IT or data teams to generate them.
   • Stifled Innovation: Preventing occasional users from exploring data independently might limit innovative problem-solving and trend discovery.
2. Decreased User Engagement
   • Frustration and Disengagement: Users may feel alienated or frustrated if they cannot access the tools needed to perform basic analyses independently.
   • Lower Adoption Rates: The lack of self-service may lead to reduced usage of BI tools overall, as users perceive them as too restrictive or cumbersome.
3. Higher IT Workload
   • Bottlenecks in Reporting: IT teams may become overwhelmed with requests for reports and dashboards, slowing down organizational responsiveness.
   • Resource Drain: Customizing dashboards for every request consumes IT resources that could be spent on more strategic initiatives.
4. Loss of Empowerment and Agility
   • Dependent Users: Locking down tools can discourage a culture of data literacy and empowerment, fostering dependency on IT teams.
   • Missed Opportunities: Occasional users who could generate actionable insights on their own may miss critical opportunities due to lack of access.

Finding the Balance

The ideal approach often lies between full lockdown and unrestricted self-service. Here are strategies for balancing control and empowerment:

• Role-Based Access: Provide self-service capabilities based on user roles, enabling occasional users to access simplified, curated tools while giving power users full access.
• Governed Data Catalogs: Offer predefined, IT-approved datasets and templates for occasional users to minimize errors while enabling exploration.
• Training and Education: Invest in training to upskill occasional users, equipping them to use self-service tools responsibly and effectively.
• Automated Workflows: Implement tools that allow occasional users to request and receive customized reports through automated processes.

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