Seesaw Studying Inc. supplies a number one on-line pupil studying platform utilized by greater than 10 million Ok-12 academics, college students and members of the family within the U.S. each month. The San Francisco firm has grown steadily since its founding in 2013, with its hosted service in use in 75% of American colleges and in one other 150 international locations.
After all, when COVID-19 hit in early 2020 and compelled colleges to abruptly change to full-time distant studying, the necessity for Seesaw’s platform skyrocketed. So did Seesaw’s development, in line with co-founder and Chief Product Officer, Carl Sjogreen.
“On account of distant studying, most of our key metrics grew by 10X,” Sjogreen stated in a video interview with SiliconANGLE’s theCUBE as a part of the AWS Startup Showcase in September 2021.
Wealth of Knowledge, Little Observability
These metrics included the info generated by current and new Seesaw customers as they interacted with the service. Storing all of that knowledge was not an issue. Seesaw was capable of scale up its essential database, an Amazon DynamoDB cloud-based service optimized for giant datasets. Seesaw’s database holds a number of billions of data.
Nevertheless, making any of that knowledge prepared for analytics, after which sharing these insights in a well timed vogue, was a unique matter. And academics and principals had been clamoring for knowledge resembling which college students had been having hassle ending classes on time. Whereas Seesaw workers had been begging for inside software utilization knowledge to enhance the shopper expertise.
“We had a lot knowledge that any query you requested instantly introduced up 5 others,” Sjogreen stated.
In different phrases, Seesaw desperately wanted 360-degree real-time observability of its operations. And that was solely attainable if each inside and exterior customers might drill down into the freshest knowledge attainable with a view to get the solutions they wanted.
Nevertheless, Seesaw’s DynamoDB database saved the info in its personal NoSQL format that made it straightforward to construct purposes, simply not analytical ones. And the batch-oriented analytical instruments that Seesaw was utilizing, resembling Amazon Athena, had been lower than the duty.
“A number of our knowledge infrastructure was customized constructed and cobbled collectively over time,” Sjogreen stated. “We had a really disorganized knowledge infrastructure that, as we’ve grown, was getting in the way in which of serving to our gross sales and advertising and marketing and assist and buyer success groups actually service our clients in the way in which that we needed to.”
To repair this, Seesaw regarded into constructing a standard knowledge warehouse paired with a set of ETL pipelines on high of DynamoDB, however concluded that it might take an excessive amount of engineering work and never fulfill its high-performance wants.
Seesaw turned to Rockset, deploying our real-time analytics database in early 2021 on high of DynamoDB. Like DynamoDB, Rockset can ingest, retailer and question large quantities of information. For real-time analytics, the cloud-native Rockset improves upon DynamoDB by having the ability to concurrently ingest large knowledge streams, indexing that knowledge so it’s accessible for queries inside two seconds, after which enabling a excessive variety of concurrent SQL queries. Outcomes, even for advanced queries, could be returned in milliseconds.
Rockset works effectively with all kinds of information sources, together with streams from databases and knowledge lakes together with MongoDB, PostgreSQL, Apache Kafka, Amazon S3, GCS (Google Cloud Service), MySQL, and naturally DynamoDB.
“Rockset comes with all batteries included, together with real-time knowledge connectors with Amazon DynamoDB,” stated Venkat Venkataramani, Rockset CEO. “You possibly can simply level Rockset at any of your Dynamo tables, though it’s a NoSQL retailer, and Rockset will in real-time replicate the info and routinely convert it into quick SQL tables so that you can do analytics on.”
In consequence, Seesaw was capable of deploy Rockset very quickly.
“One of many key benefits of Rockset was that it was principally plug and play for our Dynamo occasion,” Sjogreen stated. “We had been ready, inside hours, to start out querying that knowledge in ways in which we hadn’t earlier than.”
Actionable Insights for Educators and Seesaw Staff Alike
As soon as Seesaw started utilizing Rockset to generate analytics and make product utilization knowledge accessible by SQL queries, it grew to become more and more difficult to maneuver knowledge out of Rockset and into enterprise techniques like Salesforce for his or her gross sales staff to make use of. To work round this downside, the info staff was pressured to make numerous API calls and add CSVs.
This guide course of was extraordinarily time-consuming, taking two days of developer time simply so as to add a single discipline inside Salesforce. Seesaw wanted one thing less complicated in order that their knowledge staff might give attention to high-priority duties.
This led Seesaw to Hightouch. Hightouch is a reverse ETL answer that syncs knowledge from numerous knowledge sources to particular goal locations. Utilizing Hightouch to sync the Rockset-powered insights on to Salesforce, Seesaw’s gross sales and advertising and marketing groups can now view product utilization knowledge instantly inside Salesforce, enabling them to establish product certified leads (PQLs), customers with low engagement, and potential new clients. As a substitute of taking days to ship knowledge from Rockset to Salesforce, Seesaw now syncs knowledge in minutes.
That is extraordinarily precious to Seesaw. As a product-led-growth firm, Seesaw provides a bottom-up gross sales mannequin the place academics can use the service totally free, and can solely method college districts when a essential mass of academics and college students have adopted the service. By utilizing Rockset to run queries in real-time on their large knowledge shops and Hightouch to sync Rockset analytics knowledge to Salesforce, Seesaw can arm its gross sales representatives with up-to-date insights about how broadly and deeply used Seesaw is particularly inside a district when reaching out to its IT officers.
Rockset and Hightouch additionally work in parallel to assist Seesaw’s product staff slender down the most-needed options. This led to the creation of a pupil progress dashboard. After lower than six months, Seesaw determined to maneuver all of its analytics to Rockset, whereas sustaining DynamoDB as its database of document and utilizing Hightouch to operationalize the info.
- Buyer utilization knowledge is generated in Seesaw and saved in DynamoDB.
- Rockset’s native DynamoDB connector routinely ingests and indexes all knowledge inside seconds, with out ETL, to allow sub-second SQL queries.
- Question outcomes are pushed seamlessly into Salesforce utilizing Hightouch, a reverse ETL software, to arm the gross sales staff with up-to-date insights about their clients.
- Question outcomes are additionally pushed to Retool to assist the product and management groups visualize their analytics.
Seesaw Is dependent upon Rockset and Hightouch To Speed up Development
As colleges reopen, Rockset serves a key position in offering Seesaw key insights into how educators and college students are dealing with the return to school rooms. Hightouch helps Seesaw’s customer-facing groups leverage this info to extend development and product adoption.
“The extra we are able to perceive how they [schools] are utilizing Seesaw, the place they’re battling it as a part of that transition, the extra we is usually a good associate to them and assist them get essentially the most worth out of Seesaw on this new world that we’re dwelling in.”
For Rockset, working with Seesaw has given us precious insights into the way to enhance our service. Our Function-Based mostly Entry Controls (RBAC) safety characteristic was initially a request by Seesaw.
For Rockset’s CEO Venkataramani, working with Seesaw has had its personal private advantages — bringing him nearer to his two elementary-aged kids who’re each customers of Seesaw.
“After I advised them that Seesaw was contemplating utilizing Rocket for analytics, they had been thrilled, they had been overjoyed as a result of lastly they understood what I do for a dwelling,” Venkataramani stated. And by working so carefully with Seesaw, “for the primary time I really understood what [my] children do in school.”
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