Be honest, how do you really feel about your business intelligence (BI) solution? BI has always held the promise of delivering faster access to data and better insights into business performance. But what does your solution actually offer you right now? Newer visualization tools have improved the user experience, making access faster and easier. But this has been primarily for technical experts and BI power users, not for the masses.
These innovations have followed the long-standing assembly line delivery process of BI access. IT and analyst teams create dashboards and reports, and non-technical business users wait in line to consume them. When users do get reports, they offer no opportunity to drill down, customize, or do real-time analysis. There’s no way to ask the “next question.” This process is in stark contrast to what’s being demanded of business users—to make data-driven decisions, in the moment.
Everyday users, frustrated by this process, end up regressing and using spreadsheets to do their ad-hoc analyses. Less than 25% of employees actually use the BI tools their company has implemented. The result is dashboard and spreadsheet sprawl, resulting in multiple versions of the truth.
Enter Search for BI
In a recent TDWI webinar, “Faster BI for the Masses: How Search Can Make Analytics More Accessible” David Stodder, TDWI Research Director, examines why this process is broken and what can be done about it. He suggests that if analytics is going to become the “brain and central nervous system” of the enterprise, then the old top-down way of approaching BI must be disrupted.
Outside of work, our frustrated business users use search every day. Anyone can easily and intuitively search for anything and receive results instantly. What if this familiar, intuitive technology could be used at work for analytics? Having faster access to data and the the ability to drill down, customize, and explore would enable our business users to make the informed, actionable decisions the are asked to.
But not all search is created equal. Search technology ranges in granularity. Intuitive keyword matching produces a broad range of results that meet the basic criteria of included words. Natural language processing interprets intent and predicts an answer. Relational search calculates a precise result. Its relational search that can help our frustrated business users—with this they could independently explore their data and calculate precise answers to their questions.
Relational search analytics makes finding and querying data a faster and easier experience for everyone. Simply put, a relational search engine gives users the ability to use search to calculate answers on the fly across all of you company’s relational data.
With search-driven analytics, anyone can easily build their own reports and dashboards to find the answers they need when they need them. The business user doesn’t need to know how to write any code or understand how the data is related—she can simply type “sales region monthly last year” into the search bar and immediately get back an answer with an automatically generated best fit chart.
This true self-service means the BI team doesn’t have to sit around building reports and tweaking them for the business—reports can be built on the fly, without delay. A search-driven analytics approach also helps organizations as a whole by building a reusable knowledge base about their data and how their teams use it.
Search-driven analytics is already helping communications providers reduce churn, retailers reduce manual hours spent create reports, and financial services organizations increase sales. To find out more about how search is disrupting traditional BI, as well as David Stodder’s best practices for implementing, make sure to watch the on-demand TDWI webinar.