Analytics are only as good as the data going into the engine. In a previous post we discussed how search-driven analytics gives anyone the ability to build reports and dashboards to find the answers they need on the fly. This self-service approach to “BI for the masses” is becoming a reality, enabling analytics at the speed of thought, unthinkable just a few years ago. Though the value of self-service BI is already being realized, getting reliable insights from data is still a challenge because of slow, resource-intensive data preparation.
Friction in the Data Pipeline
According to TDWI, data quality problems cost U.S. businesses more than $600 billion each year. This comes in the form of bad decisions made from dirty or incorrect data and man hours spent manually finding and fixing these problems.
In fact, TDWI also found that data scientists are spending 80% of their time gathering requirements, preparing data, and building cubes and summary tables for business intelligence reporting. These data experts are often expensive resources with advanced degrees and would rather be spending their time on advanced analytics and other strategic initiatives.
And despite all this involvement, internal business consumers will still wait weeks, or even months, to see the reports. Often, by the time they receive their answers, the data is stale and the question is already obsolete.
Self-Service Data Prep
ThoughtSpot’s mission is to enable analytics at "human scale" by putting the power of search-driven analytics into the hands of millions of users. But we don’t think it makes sense to provide analytics that are as easy and intuitive to use as everyday search, if there's a complicated data preparation bottleneck along the way.
This is where self-service data preparation comes in. In Gartner’s 2016 Market Guide for Self-Service Data Prep, they define self-service data prep as “an iterative agile process for exploring, combining, cleaning and transforming raw data into curated datasets for data science, data discovery, and BI and analytics.”
In the early days of BI, data preparation tools were designed for BI developers. This required coding skills and a deep understanding of both data modeling and business logic. Then BI 2.0 entered the picture, empowering data scientists and technical analysts to prepare data from within advanced analytics tools without the need for extensive coding. Today, in the third wave of BI, data prep tools can be found in business intelligence and data discovery tools. And in this way, everyday business users can become their own citizen integrator to source and prepare their own data for analysis.
Enter ThoughtSpot Data Connect
ThoughSpot's Data Connect is a new product offering that allows anyone to become their own citizen integrator. With Data Connect anyone can connect, transform, and prepare terabytes of data from multiple data sources for Relational Search in minutes using a simple point-and-click interface. Users who are familiar with the business requirements of an organization’s data can actively take part in simplifying the analytics data pipeline, supporting a single version of the truth and eliminating the complications of data sprawl.
In a recent webinar, “Accelerate Your Analytics Pipeline with Self-Service Data Prep,” we reviewed effective self-service data prep strategies and show ThoughtSpot Data Connect in action. Watch it on-demand to learn how you can reduce the time-to-insight for your data consumers. With search-driven analytics now joined with self-service data prep, business users can have an immediate and positive impact on their business.