Summary Bullets:
• Domopalooza focused on the key themes of data agility, data literacy, and intelligent action.
• Domo announced multiple new products and features, including native integration with Amazon Redshift, availability of natural language generation, DDX Bricks, and Domo Everywhere.
Domo held its annual Domopalooza customer conference at the end of March, hosting a high energy event that outlined three key themes: data agility, data literacy, and intelligent action. Data agility refers to the need for organizations to respond quickly and easily to shifts in data demand and to make data accessible to all (including employees, partners, and customers). It requires a data architecture that integrates disparate data sets into a unified view, enabling the seamless flow of information. Data literacy is about empowering knowledge workers with analytical confidence, so they feel comfortable making data driven decisions. Intelligent action relates to the need to make data easy to use and engage with (such as via visualizations), so that line of business users can quickly use the insights to guide decisions.
To support customers in their advanced analytics journeys, Domo announced over 100 new products and features at Domopalooza. One of the most noteworthy (and tied to the theme of data agility) was the announcement of native integration with Amazon Redshift, making it easier for customers to access their data from a single interface. The move acknowledges enterprises’ preference for a multi-cloud environment and builds on Domo’s March announcement of native integration with Snowflake. In support of greater data literacy, Domo announced it was going to incorporate natural language generation technology into its Narrative Cards to communicate data findings in a more compelling format that can be easier for non-data specialists to understand. And to promote intelligent action, Domo announced DDX Bricks, which offers a drag and drop interface for creating applications with analytics, and Domo Everywhere, which facilities external sharing of data. Domo also plans to bring to market additional tools to help improve data science practices, such as Fix It suggestions, Key Influencer identification (what factors impact outcomes), What-If analysis, and real time drift detection, as well as features to help with data literacy.
Creating a data-centric culture can be challenging. Analytics must be made available to all parts of an organization and to multiple types of team members. Decisions aren’t made only by managers; almost all employees are making decisions. Domo’s focus on data agility, data literacy, and intelligent action broadens the company’s vision and demonstrates an understanding of the key challenges facing enterprises as they move to embrace advanced analytics. The transition isn’t as easy as it sounds. Many enterprises don’t have a data management strategy in place that enables them to make connections quickly and easily among data sets. Data often resides in silos, and one business unit may not be aware of, or have access to, the data that resides in other parts of their organizations. However, creating a strong data management foundation is essential to scaling analytics engagements and to better leveraging the wealth of information that is generated today. And then, despite the availability of features that better communicate data findings, lines of business users have been slow to adopt self-service tools that enable them to perform their own analytics or drill deeper into findings. Implementing a more data-centric corporate culture requires a change in mind-set from the top down, as well as a sizeable investment in role-appropriate training. Investment in tools is essential, but it must be complemented by investment in people.
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