When I was working at Google back in the mid 2000’s, we dealt with tens of billions of ad impressions a day, trained several machine learning models on years worth of historic data, and used frequently-updated models in ranking ads. The whole system was an amazing feat of engineering and there was no system out there that was even close to handling this much data. It took us years and hundreds of engineers to make this happen, today, the same scale can be achieved in any enterprise.

A little over a year ago, I found myself feeling stuck in my role as a data engineer. I had majored in business in college and was looking to connect more with that side of things. I enjoyed my tasks as a data engineer but I wanted more flexibility and creativity. I wanted to be involved in business decisions rather than my tasks already being decided for me.

Two years ago, we announced our Databricks partnership—including the launch of ThoughtSpot for Databricks, which gives joint customers the ability to run ThoughtSpot search queries directly on the Databricks Lakehouse without the need to move any data. Since then, we’ve empowered teams at companies like Johnson & Johnson, NASDAQ, and Flyr to safely self-serve business-critical insights on governed and reliable data.

The most successful organizations today know they need to use business analytics to make decisions and drive outcomes. Often, however, these decisions must be driven by insights that can remain hidden in data. That’s where data mining comes into play. Data mining is a powerful tool to help extract meaningful insights from even the largest, most complex data sets.

We’ve established that we’re living in the defining decade of data. Data underpins the seismic technology shifts of the past few years, transforming the way we buy, work, make business decisions, even value our companies. As ThoughtSpot’s co-founder Ajeet Singh said, “Once in a generation, the opportunities to create a legacy increase massively. It happens when truly tectonic shifts happen in the ecosystem. We’re living through one of those times.”

Analytics engineer is the latest role that combines the technical skills of a data engineer with the business knowledge of a data analyst. They are typically coding in SQL, building dbt data models, and automating data pipelines. You could say they own the steps between data ingestion and orchestration. Whether you are a seasoned analytics engineer or new to the field, it’s important to continually learn new things and improve the work you’ve already done.

Recently, I published a blog on whether self-service BI is attainable, and spoiler alert: it certainly is. Of course, anything of value usually does require a bit of planning, collaboration, and effort. After the article was published, I began having conversations with technical leaders, analysts, and analytics engineers, and the topic of data modeling for self-service analytics came up repeatedly.

Data plays a profound role in finance. In fact, some might argue that finance professionals are some of the most data-driven individuals in an organization. That’s because finance data, and the insights you draw from it, can literally make or break a company. This is especially true in times of economic uncertainty, when businesses are trying to make data-driven decisions about where to invest and cut resource allocation.

Data is everywhere–driving the evolution of technology, changing the way we do business, transforming what it means to be a customer. Yet, too many businesses are still operating in a data-aware state and not truly adapting to a data-driven mentality. According to Deloitte Insights, just 1 in 10 executives believe that their employees can actually use data to make decisions.

We’re in the defining decade of data. Data underpins the technologies transforming how we work, communicate, socialize and buy. If you want to take part in the revolution, you need to become—or hire—a data leader. But what does that even mean? What sets data leaders apart from the average data-aware professional? And how can we become data leaders?