Feb
18
2021
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Census raises $16M Series A to help companies put their data warehouses to work

Census, a startup that helps businesses sync their customer data from their data warehouses to their various business tools like Salesforce and Marketo, today announced that it has raised a $16 million Series A round led by Sequoia Capital. Other participants in this round include Andreessen Horowitz, which led the company’s $4.3 million seed round last year, as well as several notable angles, including Figma CEO Dylan Field, GitHub CTO Jason Warner, Notion COO Akshay Kothari and Rippling CEO Parker Conrad.

The company is part of a new crop of startups that are building on top of data warehouses. The general idea behind Census is to help businesses operationalize the data in their data warehouses, which was traditionally only used for analytics and reporting use cases. But as businesses realized that all the data they needed was already available in their data warehouses and that they could use that as a single source of truth without having to build additional integrations, an ecosystem of companies that operationalize this data started to form.

The company argues that the modern data stack, with data warehouses like Amazon Redshift, Google BigQuery and Snowflake at its core, offers all of the tools a business needs to extract and transform data (like Fivetran, dbt) and then visualize it (think Looker).

Tools like Census then essentially function as a new layer that sits between the data warehouse and the business tools that can help companies extract value from this data. With that, users can easily sync their product data into a marketing tool like Marketo or a CRM service like Salesforce, for example.

Image Credits: Census

Three years ago, we were the first to ask, ‘Why are we relying on a clumsy tangle of wires connecting every app when everything we need is already in the warehouse? What if you could leverage your data team to drive operations?’ When the data warehouse is connected to the rest of the business, the possibilities are limitless,” Census explains in today’s announcement. “When we launched, our focus was enabling product-led companies like Figma, Canva, and Notion to drive better marketing, sales, and customer success. Along the way, our customers have pulled Census into more and more scenarios, like auto-prioritizing support tickets in Zendesk, automating invoices in Netsuite, or even integrating with HR systems.

Census already integrates with dozens of different services and data tools and its customers include the likes of Clearbit, Figma, Fivetran, LogDNA, Loom and Notion.

Looking ahead, Census plans to use the new funding to launch new features like deeper data validation and a visual query experience. In addition, it also plans to launch code-based orchestration to make Census workflows versionable and make it easier to integrate them into an enterprise orchestration system.

Nov
12
2020
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Databricks launches SQL Analytics

AI and data analytics company Databricks today announced the launch of SQL Analytics, a new service that makes it easier for data analysts to run their standard SQL queries directly on data lakes. And with that, enterprises can now easily connect their business intelligence tools like Tableau and Microsoft’s Power BI to these data repositories as well.

SQL Analytics will be available in public preview on November 18.

In many ways, SQL Analytics is the product Databricks has long been looking to build and that brings its concept of a “lake house” to life. It combines the performance of a data warehouse, where you store data after it has already been transformed and cleaned, with a data lake, where you store all of your data in its raw form. The data in the data lake, a concept that Databricks’ co-founder and CEO Ali Ghodsi has long championed, is typically only transformed when it gets used. That makes data lakes cheaper, but also a bit harder to handle for users.

Image Credits: Databricks

“We’ve been saying Unified Data Analytics, which means unify the data with the analytics. So data processing and analytics, those two should be merged. But no one picked that up,” Ghodsi told me. But “lake house” caught on as a term.

“Databricks has always offered data science, machine learning. We’ve talked about that for years. And with Spark, we provide the data processing capability. You can do [extract, transform, load]. That has always been possible. SQL Analytics enables you to now do the data warehousing workloads directly, and concretely, the business intelligence and reporting workloads, directly on the data lake.”

The general idea here is that with just one copy of the data, you can enable both traditional data analyst use cases (think BI) and the data science workloads (think AI) Databricks was already known for. Ideally, that makes both use cases cheaper and simpler.

The service sits on top of an optimized version of Databricks’ open-source Delta Lake storage layer to enable the service to quickly complete queries. In addition, Delta Lake also provides auto-scaling endpoints to keep the query latency consistent, even under high loads.

While data analysts can query these data sets directly, using standard SQL, the company also built a set of connectors to BI tools. Its BI partners include Tableau, Qlik, Looker and Thoughtspot, as well as ingest partners like Fivetran, Fishtown Analytics, Talend and Matillion.

Image Credits: Databricks

“Now more than ever, organizations need a data strategy that enables speed and agility to be adaptable,” said Francois Ajenstat, chief product officer at Tableau. “As organizations are rapidly moving their data to the cloud, we’re seeing growing interest in doing analytics on the data lake. The introduction of SQL Analytics delivers an entirely new experience for customers to tap into insights from massive volumes of data with the performance, reliability and scale they need.”

In a demo, Ghodsi showed me what the new SQL Analytics workspace looks like. It’s essentially a stripped-down version of the standard code-heavy experience with which Databricks users are familiar. Unsurprisingly, SQL Analytics provides a more graphical experience that focuses more on visualizations and not Python code.

While there are already some data analysts on the Databricks platform, this obviously opens up a large new market for the company — something that would surely bolster its plans for an IPO next year.

Jun
30
2020
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Fivetran snares $100M Series C on $1.2B valuation for data connectivity solution

A big problem for companies these days is finding ways to connect various data sources to their data repositories, and Fivetran is a startup with a solution to solve that very problem. No surprise then that even during a pandemic, the company announced today that it has raised a $100 million Series C on a $1.2 billion valuation.

The company didn’t mess around, with top flight firms Andreessen Horowitz and General Catalyst leading the investment, with participation from existing investors CEAS Investments and Matrix Partners. Today’s money brings the total raised so far to $163 million, according to the company.

Martin Casado from a16z described the company succinctly in a blog post he wrote after its $44 million Series B in September 2019, in which his firm also participated. “Fivetran is a SaaS service that connects to the critical data sources in an organization, pulls and processes all the data, and then dumps it into a warehouse (e.g., Snowflake, BigQuery or RedShift) for SQL access and further transformations, if needed. If data is the new oil, then Fivetran is the pipes that get it from the source to the refinery,” he wrote.

Writing in a blog post today announcing the new funding, CEO George Fraser added that in spite of current conditions, the company has continued to add customers. “Despite recent economic uncertainty, Fivetran has continued to grow rapidly as customers see the opportunity to reduce their total cost of ownership by adopting our product in place of highly customized, in-house ETL pipelines that require constant maintenance,” he wrote.

In fact, the company reports 75% customer growth over the prior 12 months. It now has more than 1,100 customers, which is a pretty good benchmark for a Series C company. Customers include Databricks, DocuSign, Forever 21, Square, Udacity and Urban Outfitters, crossing a variety of verticals.

Fivetran hopes to continue to build new data connectors as it expands the reach of its product and to push into new markets, even in the midst of today’s economic climate. With $100 million in the bank, it should have enough runway to ride this out, while expanding where it makes sense.

Sep
24
2019
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Fivetran hauls in $44M Series B as data pipeline business booms

Fivetran, a startup that helps companies move data from disparate repositories to data warehouses, announced $44 million Series B financing today, less than a year after collecting a $15 million Series A round.

Andreessen Horowitz (a16z) led the round with participation from existing investors Matrix Partners and CEAS Investments. As part of the deal, Martin Casado from a16z will join the Fivetran board. Today’s investment brings the total raised to more than $59 million, according to Crunchbase.

Company co-founder and CEO George Fraser said they raised a little sooner than expected, but they needed a cash infusion to keep up with the steady growth they have been seeing. He said the company also wanted to get the funding done while the capital markets were still strong. “If we wait four months or six months, the terms are not going to be that much better — and, who knows, there could be a recession. You never know how long the sun shines, and we had interest from some really good firms that we liked, and that’s a big factor too obviously,” he said.

He added that it’s not purely an economic decision. “We’re really happy with where we landed with Martin [Casado] joining the board and Andreessen Horowitz on the cap table, but [the economic outlook] was definitely part of our calculus.”

And Casado is happy to have invested in Fivetran. Writing in a blog post today about the investment, he sees a company that’s solving a big problem in a modern context. “Fivetran is a SaaS service that connects to the critical data sources in an organization, pulls and processes all the data, and then dumps it into a warehouse (e.g., Snowflake, BigQuery or RedShift) for SQL access and further transformations, if needed. If data is the new oil, then Fivetran is the pipes that get it from the source to the refinery,” he wrote.

He said that the company already has over 750 customers and a16z is included among them. It certainly doesn’t hurt when your lead investor uses your product.

The company was founded in 2012 and has been growing steadily. Last year it had 80 employees at the time of its Series A; today it has 175. Fraser expects that to double again over the next year, and it’s all driven by business needs. He says that over the last 12 months revenue has grown 3x.

With 150 connectors today, the company wants to continue to expand its array of data connection tools and cover more data requirements. But he says the connectors are complicated and that will take an investment in more engineering talent. Today’s announcement should help in that regard.

Dec
04
2018
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Fivetran announces $15M Series A to build automated data pipelines

Fivetran, a startup that builds automated data pipelines between data repositories and cloud data warehouses and analytics tools, announced a $15 million Series A investment led by Matrix Partners.

Fivetran helps move data from source repositories like Salesforce and NetSuite to data warehouses like Snowflake or analytics tools like Looker. Company CEO and co-founder George Fraser says the automation is the key differentiator here between his company and competitors like Informatica and SnapLogic.

“What makes Fivetran different is that it’s an automated data pipeline to basically connect all your sources. You can access your data warehouse, and all of the data just appears and gets kept updated automatically,” Fraser explained. While he acknowledges that there is a great deal of complexity behind the scenes to drive that automation, he stresses that his company is hiding that complexity from the customer.

The company launched out of Y Combinator in 2012, and other than $4 million in seed funding along the way, it has relied solely on revenue up until now. That’s a rather refreshing approach to running an enterprise startup, which typically requires piles of cash to build out sales and marketing organizations to compete with the big guys they are trying to unseat.

One of the key reasons they’ve been able to take this approach has been the company’s partner strategy. Having the ability to get data into another company’s solution with a minimum of fuss and expense has attracted data-hungry applications. In addition to the previously mentioned Snowflake and Looker, the company counts Google BigQuery, Microsoft Azure, Amazon Redshift, Tableau, Periscope Data, Salesforce, NetSuite and PostgreSQL as partners.

Ilya Sukhar, general partner at Matrix Partners, who will be joining the Fivetran board under the terms of deal sees a lot of potential here. “We’ve gone from companies talking about the move to the cloud to preparing to execute their plans, and the most sophisticated are making Fivetran, along with cloud data warehouses and modern analysis tools, the backbone of their analytical infrastructure,” Sukhar said in a statement.

They currently have 100 employees spread out across four offices in Oakland, Denver, Bangalore and Dublin. They boast 500 customers using their product including Square, WeWork, Vice Media and Lime Scooters, among others.

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