Seesaw Studying Inc. offers a number one on-line pupil studying platform utilized by greater than 10 million Okay-12 lecturers, college students and relations 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 faculties and in one other 150 international locations.
After all, when COVID-19 hit in early 2020 and compelled faculties to abruptly change to full-time distant studying, the necessity for Seesaw’s platform skyrocketed. So did Seesaw’s progress, in accordance with co-founder and Chief Product Officer, Carl Sjogreen.
“Because 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 Information, Little Observability
These metrics included the info generated by current and new Seesaw customers as they interacted with the service. Storing all of that information was not an issue. Seesaw was in a position to scale up its essential database, an Amazon DynamoDB cloud-based service optimized for big datasets. Seesaw’s database holds a number of billions of data.
Nonetheless, making any of that information prepared for analytics, after which sharing these insights in a well timed trend, was a distinct matter. And lecturers and principals have been clamoring for information similar to which college students have been having bother ending classes on time. Whereas Seesaw staff have been begging for inside utility utilization information to enhance the client expertise.
“We had a lot information 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 doable if each inside and exterior customers may drill down into the freshest information doable with a view to get the solutions they wanted.
Nonetheless, Seesaw’s DynamoDB database saved the info in its personal NoSQL format that made it straightforward to construct functions, simply not analytical ones. And the batch-oriented analytical instruments that Seesaw was utilizing, similar to Amazon Athena, have been lower than the duty.
“Lots of our information infrastructure was customized constructed and cobbled collectively through the years,” Sjogreen stated. “We had a really disorganized information infrastructure that, as we’ve grown, was getting in the best way of serving to our gross sales and advertising and assist and buyer success groups actually service our clients in the best way that we wished to.”
To repair this, Seesaw seemed into constructing a standard information 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 huge quantities of information. For real-time analytics, the cloud-native Rockset improves upon DynamoDB by with the ability to concurrently ingest huge information streams, indexing that information so it’s obtainable for queries inside two seconds, after which enabling a excessive variety of concurrent SQL queries. Outcomes, even for complicated queries, can be returned in milliseconds.
Rockset works properly with all kinds of information sources, together with streams from databases and information 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 information connectors with Amazon DynamoDB,” stated Venkat Venkataramani, Rockset CEO. “You may 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 mechanically convert it into quick SQL tables so that you can do analytics on.”
In consequence, Seesaw was in a position to 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 have been ready, inside hours, to begin querying that information 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 information obtainable by way of SQL queries, it turned more and more difficult to maneuver information out of Rockset and into enterprise programs like Salesforce for his or her gross sales workforce to make use of. To work round this downside, the info workforce was compelled to make varied API calls and add CSVs.
This handbook course of was extraordinarily time-consuming, taking two days of developer time simply so as to add a single subject inside Salesforce. Seesaw wanted one thing easier in order that their information workforce may deal with high-priority duties.
This led Seesaw to Hightouch. Hightouch is a reverse ETL answer that syncs information from varied information sources to particular goal locations. Utilizing Hightouch to sync the Rockset-powered insights on to Salesforce, Seesaw’s gross sales and advertising groups can now view product utilization information immediately 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 information from Rockset to Salesforce, Seesaw now syncs information in minutes.
That is extraordinarily precious to Seesaw. As a product-led-growth firm, Seesaw affords a bottom-up gross sales mannequin the place lecturers can use the service without spending a dime, and can solely method faculty districts when a crucial mass of lecturers and college students have adopted the service. By utilizing Rockset to run queries in real-time on their huge information shops and Hightouch to sync Rockset analytics information 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 workforce 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 information is generated in Seesaw and saved in DynamoDB.
- Rockset’s native DynamoDB connector mechanically ingests and indexes all information 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 workforce 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 determined by Rockset and Hightouch To Speed up Development
As faculties 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 data to extend progress and product adoption.
“The extra we will perceive how they [schools] are utilizing Seesaw, the place they’re scuffling with it as a part of that transition, the extra we generally is a good accomplice to them and assist them get probably the most worth out of Seesaw on this new world that we’re residing in.”
For Rockset, working with Seesaw has given us precious insights into tips on how to enhance our service. Our Position-Primarily based 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 youngsters who’re each customers of Seesaw.
“After I instructed them that Seesaw was contemplating utilizing Rocket for analytics, they have been thrilled, they have been overjoyed as a result of lastly they understood what I do for a residing,” Venkataramani stated. And by working so intently with Seesaw, “for the primary time I really understood what [my] youngsters do at college.”
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