Seemingly everywhere you look in tech, the cloud has been a revolutionary force. It wasn’t always this way, however. Single use SaaS applications like Salesforce and Workday were the first true foray into the cloud.
While this was great for specific teams, it failed to transform the use of data at the enterprise level. Most data warehouses were on-premise and most BI and Analytics solutions were architected with their own persistence or semantic layer. Companies were bringing their cloud app data stores back to these on-premise warehouses or BI persistence layers - defeating the entire purpose of moving to the cloud in the first place.
However, the wholesale movement of data into cost effective storage in the cloud has led to the rise of Snowflake, Amazon Redshift, and Google BigQuery. Today, data warehouses have moved to the cloud and they are faster, more scalable, and more agile than on-prem for doing so.
This is all setting-up the next big cloud transformation, this time for BI & analytics apps. It’s important to note data in the cloud is fundamentally different. It’s larger, and more fragmented. The volume and variety of data has increased as data comes from more sources and applications. The speed at which data is created, and by extension becomes outdated, means it has a shorter shelf life than ever.
Traditional business intelligence tools required developers and trained analysts to create and then publish visualizations and dashboards that business counterparts, clients, and customers could view. It is clear today that this legacy model cannot keep up with our clients’ need to leverage cloud data.
The cloud provides a massive opportunity for everyone in the data ecosystem to rethink how and where we can maximize data consumption. And this consumption must go beyond simple dashboards and visualizations. Our customers need to tap into their cloud data like never before to capitalize on this opportunity.
That’s where search & AI are changing the game and delivering an entirely new experience for data. Inspired by the best of the consumer world, search and AI analytics are making insights truly accessible to non-technical business people for the first time.
These business people aren’t just internal business counterparts. By bringing search and AI-driven analytics to wherever data is created, you can open new potential users by giving them direct access to information, make experiences stickier, and ultimately drive immense value.<br><br>Cloud analytics are already transforming businesses. To truly leverage this power, however, requires embedded analytics. With ThoughtSpot Everywhere, you can easily embed Search & AI-driven analytics into your app - in the cloud. The advantages are numerous.
Cloud vs. Physical.
Easy to pilot, easy to deploy, with low touch/support costs
Time to Market.
Instantly available versus months to deploy
Elasticity and Agility.
Scale up - scale down; right size costs based on demand/capacity
Lower TCO and Higher Margins.
Lower cost hardware, support, cost of delivery, and streamlined operations
Speed of Innovation.
Add and test new features more quickly; version control
Focus engineering resources on core applications versus building point solutions that need to be supported and updated internally.
ThoughtSpot Everywhere is cloud native and allows app builders to quickly and easily create and deploy applications that are dynamic on the front end as well as the back end, allowing the apps being built to be more resilient while allowing new features to be added more quickly. ThoughtSpot Everywhere empowers companies to embed the power of search to design a consumer app-like experience to create data applications that are dynamic, engaging, and sticky. Search drives higher user engagement and ultimately, the business value produced by the app.
Get started: Transform data into data apps at cloud scale