In the old days, storing data was was a fairly trivial task. Simply create some tables with rows and columns and you were set. By structuring your data in this manner, few well-crafted SQL statements could locate just about anything you needed in a few seconds. But data has been evolving, and the volume, velocity and variety of enterprise data today demands not only new tools but also a new way of thinking.
Traditional data warehouse products were only built to handle traditional types of structured data. Over time, they’ve become OK at dealing with the first two “V’s” of volume and velocity, but they often struggle to keep up with a company’s growing data needs. Additionally, they’ve long struggled with the third “V”, variety. Companies still generate a ton of structured data, but more and more this data is joining a mountain of semi- and unstructured data.
For example, collecting feedback is becoming more important to the enterprise. Whether you’re polling customers, suppliers or employees, there’s a high likelihood you’ll be getting semi-structured data back from your surveys and forms that includes branching or attachments that need to be stored.
Semi-structured data is also prevalent throughout Internet services. Whether you’re shopping online, checking-in on social media or leaving a review for your favorite restaurant, you’re likely generating semi-structured data that companies need to store and analyze.
In our modern world, it’s not only humans that are generating data, companies are increasingly using all sorts of digital systems and sensors that are collecting all sorts of machine data, including logs, images, audio, video and more. Data warehouse technology was never designed to handle this wide variety of data, which is why Qrvey has created the Data Powerhouse.
The Data Powerhouse mantra is simple, all data is accepted. Based on Elasticsearch, a Qrvey Data Powerhouse will gladly accept all of your structured data, from simple spreadsheets all the way up to your largest SQL solutions. But that’s just the beginning, because Qrvey can also ingest files, documents, images, audio, video and more. Semi-structured and unstructured data is no longer a problem.
There’s a lot more to a Data Powerhouse than just connecting to your data however. Qrvey automatically applies AI tools to your data to provide smart analysis. Text fields are automatically analyzed to gauge sentiment, while images are scanned with either text recognition or object detection to catalog people, objects and themes. Audio and video files will also be instantly transcribed so they can be properly searched and categorized.
A Qrvey Data Powerhouse can not only serve as a single, high-performance repository for all of your enterprise data, but thanks to its intelligent analysis, it can then provide self-service analytics and automation to your entire organization, finally breaking free of the constraints of a traditional data warehouse.
David is the Chief Technology Officer at Qrvey, the leading provider of embedded analytics software for B2B SaaS companies. With extensive experience in software development and a passion for innovation, David plays a pivotal role in helping companies successfully transition from traditional reporting features to highly customizable analytics experiences that delight SaaS end-users.
Drawing from his deep technical expertise and industry insights, David leads Qrvey’s engineering team in developing cutting-edge analytics solutions that empower product teams to seamlessly integrate robust data visualizations and interactive dashboards into their applications. His commitment to staying ahead of the curve ensures that Qrvey’s platform continuously evolves to meet the ever-changing needs of the SaaS industry.
David shares his wealth of knowledge and best practices on topics related to embedded analytics, data visualization, and the technical considerations involved in building data-driven SaaS products.
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