Systems | Development | Analytics | API | Testing

So, did you invest in RPA? Did you buy into the dream of automation? How's it going? Are your bots running at 100% reliability and delivering amazing ROI? Or are you fighting bot breakdowns and struggling to justify the expense of costly RPA bots with poor reliability?

When was the last time you had all the data you needed to make a business decision? Hopefully, it was today. But if it wasn’t, you’re not alone. It’s increasingly difficult for people inside enterprise organizations to harness the power of their data. Even though good decisions are nearly impossible without good data, getting data into the right hands at the right time is easier said than done.

The days of waterfall and siloed teams are gone. QA now works alongside development to release products faster and find bugs sooner. Agile transformations changed how companies work, bringing development and testing together and prioritizing quality. However, the current market and consumers demand higher levels of quality and faster releases. Companies can’t afford bugs, vulnerabilities, or critical issues. Quality is no longer a vision - it’s a necessity.

For development teams aspiring to adopt shift-left testing, using Linux VMs can provide a secure and robust environment without the cost.

Today we’re excited to announce ThoughtSpot Sage, our new search experience that combines the power of GPT’s natural language processing and generative AI capabilities with the accuracy and security of our patented self-service analytics platform. With this new integration, data teams will be able to exponentially increase their impact across an organization as business users self-serve personalized, actionable, and trustworthy insights like never before.

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.

Every so often, different advocates across organizations ignore the Voice of the Customer. This may be due to changes in business priorities, redistribution of resources, focus on new trends, or that they clear a profit regardless. This brings the value of the customer's voice into question: should we still allocate time and effort towards listening to customers when following new trends is the norm? ‍ The short answer is a resounding yes.