In 2018, many organizations are looking to enable the business with self-service data. A successful strategy will set a strong foundation that empowers business users to be self-sufficient in all ways they interact with enterprise data. In this webinar, John O’Brien, principal advisor at Radiant Advisors, shared the latest research on enterprise self-service data and discussed the six pillars that are necessary for success.

When all six capabilities are present in a single platform, the result is improved speed and agility in solving business needs. Business users directly benefit from this balance of freedom with end-to-end governance, individual work with community collaboration and insight with the assistance of artificial intelligence recommendations.

Read below for answers to questions asked during this webinar.

Question: If I only need one piece of the platform right now (Catalog or Prep, for instance) why should I spend the money on a platform? Won’t it be more expensive?

Answer: No matter what tool a company’s data journey begins with – catalog or prep, eventually the need for governance, collaboration, and workflow automation – for example, all become important for helping to solve business challenges.

The Unifi platform is a much more affordable option – even more cost-efficient than standalone catalog or prep tools on the market today. Trying to integrate tools as you go can take years and an inordinate amount of person-hours, and still not work as well as our integrated platform.


Question: Is one pillar more important than the others?

Answer: No one pillar is any more or less important than another – it’s why we’ve integrated all of them into a unified platform. A company’s data journey may begin at a different starting point though. In many instances, we’re seeing companies start with a data catalog because it’s really hard to have a complete view of all your company data – and to know what’s important, relevant and accurate.


Question: Why do you need to address all six pillars from the onset of a self-service data initiative?

Answer: Working in a single pillar hinders a company’s ability to work effectively with data and to innovate as a company.

Take governance as one example, businesses need to ensure that all data – wherever it’s used and whoever accesses it – is governed and secured. Compliance needs to happen across every pillar. The same is true of data quality – if you can’t access metadata or track data lineage it’s hard to know the real value of a dataset. The value of community collaboration is also critical for gaining faster insights to data.


Question: How can I convince my organization of the importance of the others as well? (My organization has been pushing self-service for a while now, but mostly from the data catalog / discovery / prep perspective without much emphasis on the other pillars.)

Answer: Both business and IT should be part of the conversation. For IT, when the right tools are in place they can be less interrupt driven in their work and business users get the information they need much more quickly.

It’s important to understand what your business challenges are – what problem are you trying to solve at an organizational level. Are you trying to understand your customer’s buying behaviors, decrease churn, or create a more effective marketing campaign to generate sales leads for a new product launch?

Asking the right questions can be the starting point to bring IT and LOB users together to understand how a data-driven culture with the right platform can help everyone succeed.

Want to learn more?

If you attended the webinar, you saw a demo of the Catalog pillar of the Unifi platform. To read more about all six pillars of the Unifi Platform, a seamlessly integrated suite of self-service data tools, download the Definitive Guide to Self-Service Data. In this guide, you’ll read:

  • What to look for and consider when implementing true Self-Service Data
  • Case studies showing data problems solved for Global 2000 companies
  • A vision for the future of Self-Service Data