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Tesla vs Lucid: Lessons for Data Companies

When Tesla started manufacturing and selling cars in 2011, people lined up to buy them. The cars had one main selling point: the electric drivetrain. Everything else about the car was akin to early-stage technology; creating their reputation as well-intentioned but poorly fitted and built cars. It had low range, interiors were plastic for a $120K car, no self-driving, poor build quality, and the list goes on. But at the time, people still lined up to buy them.

Ten years later, in 2021, any company that wants to make and sell electric cars must meet the buyer’s expectations, which have skyrocketed. Lucid Motors’ car, Air, is the case in point. Buyers today want their car to be technologically superior to the Tesla, and for the manufacturing quality to be impeccable, they want an established charging infrastructure, and the list goes on. In short, the value proposition of an electric car does not lie in just being an electric car.

See a demo of Quaeris and how it's the industry leader in augmented BI

About 16 years ago when I first saw Tableau as a young analyst, I was fascinated, and I knew it was going to change the world. The world adopted Tableau with all its shortcomings and Tableau improved its product over 10 years. Tableau and Power BI is like the Teslas of the BI space, they came with the vision, but analytics now require much more than the dashboard of 10 years ago. The bar has been raised and the onus is on augmented analytics tools to prove that we are a superior product, much like the Lucid Air.

IT had Taxation without representation

When Tableau came out, business users flocked to swipe their credit cards and start their own BI shop – every department from sales to marketing, even HR had their own version of dashboards and reports and BI developers being hired. This was driven by the growing hunger for data, but soon enough, businesses realized that they required governance and standardization to gain meaningful insights.

IT had Taxation without representation

This mad rush to buy BI tools and set up shop was appropriately named ‘Shadow BI’. IT had no control, but they were blamed for the data issues. IT faced taxation for faults while lacking representation in system design. Microsoft saw this gap and designed Power BI to give control back to IT. Businesses would get curated dashboards from centralized Data teams.

Today’s BI exists as a compromise between business and central data teams.

Quaeris is not a compromise for anyone

    • IT should have the responsibility of enabling, managing, securing, and provisioning the data. 
    • Business analysts need to be able to get answers from their data seamlessly
    • BI developers should be relieved of repeated work