AutoQL for BI & Analytics Field & Job Site Users
~4 minute read
Many of today’s jobs are moving out of the office and into the realm of remote work, but in many industries, operating with workers in the field, employing drivers and other mobile workers , or sending employees out to observe and collect data at the job site has been a longstanding reality.
Critical business decisions are often made out in the field. It’s more important than ever to mandate that data is factored into these decision-making processes. Data access empowers derivation of insights based on a single source of truth, contributing to better-informed decisions and a higher degree of strategic planning and problem solving.
Typically, reports and dashboards are accessed in the office, and communication between individuals out in the field and those back at headquarters ensues. This can take a lot of time and resources as team members rely on each other to search for and share the right data. Business Intelligence (BI) and analytics tools need to adapt to better serve employees who do their job away from their computer.
Gaps in this back-and-forth communication are inevitable, and can lead to reporting bottlenecks or even stall entire projects for significant periods of time.
While mobile apps are increasingly being developed or improved to facilitate the function of many BI and analytics tools, conversational AI can rapidly speed up the deployment and adoption of data-centric initiatives across entire user groups and business settings.
Where field workers may have previously been unable to include data into their off-site workflows, a conversational AI solution like AutoQL, enables immediate data access anywhere, at any time. Users benefit from seamless access to meaningful data that can help them take action as quickly as possible. This data would otherwise only be accessible via desktop-optimized applications, proving less-than-helpful for workers who don’t spend their days in an office setting.
With AutoQL, your users can access their data in seconds and analyze it in real time on their mobile device, no matter where they are.
Leveraging a conversational user interface (which can easily fit on a smaller screen, much like a messenger window), users are able to find the data they need to get the job done, even if they are a thousand miles away from both their database and the experts who they would otherwise call on to access it.
Comprehensive dashboards and reports take up a lot of screen real estate and are cumbersome to scroll through on a mobile device. Additionally, any custom ad hoc reports or last-minute updates often need to be requested from a technical team, and retrieving this information can take hours, if not days or even weeks.
With conversational AI technology embedded in the BI and analytics tools that they already rely on, users can easily access the valuable insights in their data from wherever they are, whenever they need, simply by asking questions in their own words.
For example, a researcher out in the field might be inspecting a contaminated plot of land, taking follow-up soil samples. They want to quickly reference what the toxicity levels have been over the past several months, especially since putting new cleanup measures in place just three months prior.
Rather than scrolling through a PDF spreadsheet they downloaded before leaving the office, or calling their team members in the office to inquire about toxicity trends , they can just open their mobile app and request “Toxicity level average for site X by month over the last nine months”.
They can quickly select a graph or a table that shows them this information and derive insights about the effectiveness of the cleanup measures to date, based on their observations of the data at hand.
Adding this kind of data-on-demand functionality allows users to experience more value from their BI tools, well beyond the walls of the office.
This gives BI and analytics solution providers an opportunity to widen their value proposition to include powerful and user-friendly mobile access to data that enables more people to leverage the system more frequently, thereby leading to heightened customer loyalty and increased reliance on the product, as users experience the benefits and results of frictionless access to data.