We have to credit Richard Miller Devens for coining the term “Business Intelligence”. He was intrigued by how Sir Henry Furnese, a banker in Victorian England used the information he gathered to create an action plan that led him to reap profits and stay ahead of the competition. Nobody could fathom that it was the beginning of the modern-day version of data-driven decision-making, an art and a science in itself, which turned the tide of businesses legacy and modern alike!
Business Intelligence, aka data analytics, has come a long way since. Right from physical methods to technology-involved digital methods, Right from internal IT team handling to specialized teams creating reports, the world of analytics had its fair share of changes in processes. However, the core requirement of data analytics remains the same. Help organizations, teams, and individuals make informed decisions with the help of data.
Search Driven Analytics (SDA) is the most recent methodology for deriving insights. A lot of companies are investing in search-driven analytics, but what is this technology and how can it help your business? In this post, we’ll explain what SDA is, why you should use it, and what makes it different from traditional BI self-service.
What is Search Driven Analytics and Why do We Need it?
Search-driven analytics is the next wave in BI self-service. BI self-service has been around for a long time, but it’s not always easy to use or understand. Search Driven Analytics is interactive and fast, making it easier than ever before to get answers from your data quickly. Search Driven Analytics is a new technology that allows you to access valuable intelligence from your data by searching for descriptive words, phrases, or questions.
The concept of search-driven analytics is not something that’s foreign to this world. How many of us whip out our phone and Google (or Bing) search for the nearest cafe, or for the attractions to see in a new place? The same idea has translated into becoming search-driven analytics. Instead of sifting through a barrage of overloaded metrics, imagine a Chief Human Resource Officer or Senior Vice President – Talent, opening a search bar and typing “What has been my attrition rate for Q1 for 2022?”
This question on data gets answers in different formats including but not limited to charts, numbers, and other forms. This effectively negates the concept of death by metrics and ensures that only the required information is shared with the user. To put this into more perspective, let’s look into the above example. The CHRO wants to know the attrition rate, not the number of interviews scheduled or the number of training conducted, which tends to sit in the monthly HR dashboard.
Differentiating from Self Service Analytics
It’s a form of self-service analytics and it’s the next step in the evolution of data analytics. Self Service Analytics is a form of business intelligence (BI) that enables users to access, manipulate and analyze data without needing to go through IT. The biggest difference between search driven analytics and self service analytics is the decrease in complexity to access insights. Of course, all search driven analytics are self service analytics but the vice versa is not true.
Looking Under the Hood of Search-Driven Analytics
Search Driven Analytics is powered by Natural Language Processing capabilities. If you would like to know about Natural Language Processing, head over to our Conversational Insights Glossary.
A rudimentary form of search driven analytics will have a platform to crunch data fed from different sources, the data pipeline, basically. The system will be trained to understand what attributes are identified as the dimensions and the measures of the loaded data. They will also be offered to assign synonyms to certain attributes. For eg: attrition rate, is assigned to the measure – percentage of employees exited, and so on. The platform is then trained on the synonyms so that the NLP algorithm running can pick up the words, the user tends to use. Once that’s done, the users can use the platform to ask data questions and derive their insights.
So the entire process can be summarized into three steps.
- Plugging the database
- Training the system
- Getting insights through Natural Language
Will Search-Driven Analytics Replace Traditional BI tools?
The short answe is no. Because, it doesn’t replace the need to know how to read and interpret reports—but SDA can help you discover new insights in your existing data that would be difficult or impossible to uncover using traditional BI techniques.
Search Driven Analytics enables users to find answers quickly by allowing them to search text in any document within seconds. For example, if you have an email list with 10,000 members and only want information about specific people who are interested in purchasing your product or service then using SDA will allow anyone on the team access this information without having any knowledge about how this works behind the scenes. Search driven analytics for the larger part resonates well with its twin, conversational insights, or Business Intelligence powered by Conversational AI. Like Conversational Insights, search driven analytics also improves
- Ease of use – The need to have technical skills or complete complex certification courses are removed.
- Accessibility – Anyone can use it, right from the front-end salesman to the CEO of the organization.
- Convenience – Since the data questions are being asked in English or other native languages, the convenience to use improves
- Relevant Visualizations/Metrics – Unnecessary metrics won’t be loaded into the screen, rather the required info will be displayed in multiple formats.
- Faster Information Access – The speed with which information is retrieved will be faster as compared to legacy practices where a dashboard will take 4-5 business days to be produced
Search driven analytics will act as a bridge for data analysts and tech users to shed their habit of depending on queries for data insights. It can be a great asset in driving change management amongst regular data users who have been dependent on spreadsheet driven data analytics or other legacy systems.
Interested to know more about the future of search driven analytics and what it will metamorphosize into? Check out this video.