AWS Startups Blog
Tag: Big Data
SaaS Founder Series: Clumio CEO on Steering the Startup that Raised $11M Pre-Product
The growing customer preference for software-as-a-service (SaaS) puts enterprise software startups in a rare position of advantage compared to established firms. AWS SaaS Factory invited Poojan Kumar, CEO and Co-founder of Clumio, to share the early successes and learnings from steering the startup that is disrupting a segment with numerous corporate behemoths.
SaaS Founder Series: Dremio’s Journey to Unicorn Status
The AWS SaaS Factory team invited Founder and Chief Product Officer of Dremio, Tomer Shiran, to discuss Dremio’s journey to software-as-a-service and to share key learnings for businesses building SaaS and platform-as-a-service (PaaS) offerings on AWS.
How Datacoral Uses AWS to Automate Data Pipelines and Create Fast, Easy Insights From Any Source
Learn how the winner of the 2020 AWS Startup Architecture Challenge, Datacoral, is leveraging AWS to change the data game.
Mistplay: Improving Business Analytics with Amazon S3 & Amazon Athena
In this post, gaming startup Mistplay will explain why and how they migrated from Firebase and BigQuery to Amazon S3 and Amazon Athena, and how this improved their analytics capability, cost structure, and operations.
Explorium Leverages AWS to Power Its Data Enrichment for ML Platform
Finding the right data, both internally and externally, for your ML can be a huge pain, though. It’s often dirty, hidden behind paywalls, or just not enough to give a full view of a situation. This is where Explorium comes in.
Yewno Uses AWS and ML to Analyze Vast Amounts of Data
The mass digitization of information has made finding the right thing online difficult to say the least. This is precisely the problem Yewno was founded to solve. Leveraging sophisticated AI, built with AWS, the startup analyzes millions of information sources in real-time. Rather than simply hunting for keywords, the startup’s algorithms read text, understand context and meaning, and explain why things are connected.
Accelerate Drug Discovery in Pharma R&D with Stardog
The only way for pharmaceutical companies to counteract today’s unprecedented changes is to extract better insight from their existing data and to develop systems that allow for more rapid decision making. Making better use of data up front will help these companies access data from across silos and then more quickly decide which therapies to pursue in the drug development process.
redBus: Building a Data Platform with AWS & Apache Software Foundation
As future data requirements cannot always be planned much ahead of time, data warehousing effort is generally subdued by first creating a data lake, which is a pool of centralized data ready to be transformed based on use cases. A means for accessing and analyzing this data makes it easier for knowledge workers to make good informed decisions. Here’s how Indian bus ticketing platform Redbus does it.
A Data Lake as Code, Featuring ChEMBL and OpenTargets
AWS Startup Solutions Architect Paul Underwood believes that a data lake is just another complex and heterogeneous infrastructure problem. In this post, he illustrates how you might build a data lake-as-code using the AWS Cloud Development Kit (CDK). Underwood will outline the strategy, core data lake services used, associated costs, and how you can tie it all together with code.
The Simplest, Yet Most Powerful Trait: Trust
Data practically runs through the veins of Steven Mih, CEO of opensource data orchestration startup Alluxio. He’s a serial startup CEO with more than two decades in the distributed data world. We recently sat down with him on the What Works podcast to learn more.