Why the Best Data Mining Tools Are Automated

Many things are involved for businesses to succeed with their data initiatives.

We’ve discussed what data fluency is and how it helps companies cultivate data-driven cultures and improve communication and collaboration.

This isn’t just because everyone speaks numbers in a data-fluent organization, but also that it’s the same numbers. In a digital economy that’s experiencing a growth in the number of knowledge workers, data experts can’t keep up. Automated data mining tools help relieve the burden on data teams by consolidating data sources into one analytics search bar for everyone to use.

While automated data mining tools yield innumerable benefits to companies, let’s focus on three reasons why the best data mining tools are automated:

Unlimited Ad-Hoc Questions without the Report Backlog

Data scientists and analysts are some of the most coveted hires in today’s digital economy. As such, they command strong salaries. Data professionals are needed in every organization — whether they have a data mining tool or not — but mistakes occur when they’re merely used to fulfill report requests from around the company.

When employees have to submit report requests to find an answer, they can’t move quickly in their workflows or make timely decisions. Waiting days to weeks for a report to come back slowly erodes employees’ curiosities and strips them of autonomy.

ThoughtSpot’s commercial tools for data mining keep companies leaner. Instead of hiring more data professionals to keep pace with reporting demands, employees can find their own answers in real-time through relational search and ad-hoc analytics.

Accelerated Knowledge Discovery

The instant insights of ThoughtSpot wouldn’t be possible without several features complementing each other beautifully. However, it’s distributed cluster management and in-memory calculation that serve as the basis of our architecture.

• Distributed Cluster Management

  No matter the size of a company, ThoughtSpot can accommodate unlimited users and data sources without compromising the analytics experience. Ongoing system utilization and performance monitoring ensure data clusters are always in good health and repaired when needed without draining the data and IT team’s bandwidth.

• In-Memory Calculation

  Now that all those data sources are integrated, they need to be accessible to all end users. ThoughtSpot’s in-memory calculation engine allows a single, speedy analytic caching on dozens of data sources and billions of rows of data.

• AI-Driven Insights with SpotIQ

  Speedy insights from an entire data warehouse are helpful, but it pales in comparison to the power of artificial intelligence (AI) and machine learning (ML).

  SpotIQ does the work of one thousand data analysts in just a few seconds by building ad-hoc reports, indicating hidden trends, uncovering anomalies, isolating key performance indicators, segmenting data and more.

  SpotIQ learns more about its users as they search, but never takes complete control of the experience. Users can select a “thumbs-up” “thumbs-down” after each insight and even look at the source of the finding since SpotIQ presents its calculations transparently.

Organizations that leverage ThoughtSpot’s data mining tools and features like SpotIQ see their employees take more control of their roles, drive new innovations and make better decisions.

Experience what different data mining tools have to offer. Watch our SpotIQ demo video today.