Rockset announces $40M Series B as data analytics solution gains momentum


This post is by Ron Miller from Fundings & Exits – TechCrunch

Rockset, a cloud-native analytics company, announced a $40 million Series B investment today led by Sequoia with help from Greylock, the same two firms that financed its Series A. The startup has now raised a total of $61.5 million, according to the company.

As co-founder and CEO Venkat Venkataramani told me at the time of the Series A in 2018, there is a lot of manual work involved in getting data ready to use and it acts as a roadblock to getting to real insight. He hoped to change that with Rockset.

“We’re building out our service with innovative architecture and unique capabilities that allows full-featured fast SQL directly on raw data. And we’re offering this as a service. So developers and data scientists can go from useful data in any shape, any form to useful applications in a matter of minutes. And it would take months today,” he told me in 2018.

In fact, “Rockset automatically builds a converged index on any data — including structured, semi-structured, geographical and time series data — for high-performance search and analytics at scale,” the company explained.

It seems to be resonating with investors and customers alike as the company raised a healthy B round and business is booming. Rockset supplied a few metrics to illustrate this. For starters, revenue grew 290% in the last quarter. While they didn’t provide any foundational numbers for that percentage growth, it is obviously substantial.

In addition, the startup reports adding hundreds of new users, again not nailing down any specific numbers, and queries on the platform are up 313%. Without specifics, it’s hard to know what that means, but that seems like healthy growth for an early stage startup, especially in this economy.

Mike Vernal, a partner at Sequoia, sees a company helping to get data to work faster than other solutions, which require a lot of handling first. “Rockset, with its innovative new approach to indexing data, has quickly emerged as a true leader for real-time analytics in the cloud. I’m thrilled to partner with the company through its next phase of growth,” Vernal said in a statement.

The company was founded in 2016 by the creators of RocksDB. The startup had previously raised a $3 million seed round when they launched the company and the $18.5 million A round in 2018.

Resilience and Vibrancy: The 2020 Data & AI Landscape


This post is by mattturck from Matt Turck

In a year like no other in recent memory, the data ecosystem is showing not just remarkable resilience but exciting vibrancy. When COVID hit the world a few months ago, an extended period of gloom seemed all but inevitable.   Yet, as per Satya Nadella, “two years of digital transformation [occurred] in two months”.  Cloud … Continue reading Resilience and Vibrancy: The 2020 Data & AI Landscape

Resilience and Vibrancy: The 2020 Data & AI Landscape


This post is by mattturck from Matt Turck

In a year like no other in recent memory, the data ecosystem is showing not just remarkable resilience but exciting vibrancy. When COVID hit the world a few months ago, an extended period of gloom seemed all but inevitable.   Yet, as per Satya Nadella, “two years of digital transformation [occurred] in two months”.  Cloud … Continue reading Resilience and Vibrancy: The 2020 Data & AI Landscape

Resilience and Vibrancy: The 2020 Data & AI Landscape


This post is by mattturck from Matt Turck

In a year like no other in recent memory, the data ecosystem is showing not just remarkable resilience but exciting vibrancy. When COVID hit the world a few months ago, an extended period of gloom seemed all but inevitable.   Yet, as per Satya Nadella, “two years of digital transformation [occurred] in two months”.  Cloud … Continue reading Resilience and Vibrancy: The 2020 Data & AI Landscape

How to Fight Discrimination in AI


This post is by Andrew Burt from HBR.org

Tackling one of the toughest questions about algorithmic bias.

A Data-Driven Approach to Addressing Racial Disparities in Health Care Outcomes


This post is by Karthik Sivashanker from HBR.org

Lessons from Brigham Health.

It’s Time for a New Kind of Electronic Health Record


This post is by John Glaser from HBR.org

We need to shift from reactive to preventative care.

Is Your Marketing Strategy Based on the Right Data?


This post is by Gregg Johnson from HBR.org

The pandemic is changing consumers’ habits.

Approach Your Data with a Product Mindset


This post is by Jedd Davis from HBR.org

Keep end users top of mind.

Your Organization Needs a Proprietary Data Strategy


This post is by Thomas C. Redman from HBR.org

Protect your competitive advantage.

Buying Consumer Data? Tread Carefully.


This post is by Catherine Tucker from HBR.org

Information sold by data brokers varies greatly in quality.

Bringing an Analytics Mindset to the Pandemic


This post is by Nico Neumann from HBR.org

How to collect, weigh, and report complex data.

Fishtown Analytics raises $12.9M Series A for its open-source analytics engineering tool


This post is by Frederic Lardinois from Fundings & Exits – TechCrunch

Philadelphia-based Fishtown Analytics, the company behind the popular open-source data engineering tool dbt, today announced that it has raised a $12.9 million Series A round led by Andreessen Horowitz, with the firm’s general partner Martin Casada joining the company’s board.

“I wrote this blog post in early 2016, essentially saying that analysts needed to work in a fundamentally different way,” Fishtown founder and CEO Tristan Handy told me, when I asked him about how the product came to be. “They needed to work in a way that much more closely mirrored the way the software engineers work and software engineers have been figuring this shit out for years and data analysts are still like sending each other Microsoft Excel docs over email.”

The dbt open-source project forms the basis of this. It allows anyone who can write SQL queries to transform data and then load it into their preferred analytics tools. As such, it sits in-between data warehouses and the tools that load data into them on one end, and specialized analytics tools on the other.

As Casada noted when I talked to him about the investment, data warehouses have now made it affordable for businesses to store all of their data before it is transformed. So what was traditionally “extract, transform, load” (ETL) has now become “extract, load, transform” (ELT). Andreessen Horowitz is already invested in Fivetran, which helps businesses move their data into their warehouses, so it makes sense for the firm to also tackle the other side of this business.

“Dbt is, as far as we can tell, the leading community for transformation and it’s a company we’ve been tracking for at least a year,” Casada said. He also argued that data analysts — unlike data scientists — are not really catered to as a group.

Before this round, Fishtown hadn’t raised a lot of money, even though it has been around for a few years now, except for a small SAFE round from Amplify.

But Handy argued that the company needed this time to prove that it was on to something and build a community. That community now consists of more than 1,700 companies that use the dbt project in some form and over 5,000 people in the dbt Slack community. Fishtown also now has over 250 dbt Cloud customers and the company signed up a number of big enterprise clients earlier this year. With that, the company needed to raise money to expand and also better service its current list of customers.

“We live in Philadelpha. The cost of living is low here and none of us really care to make a quadro-billion dollars, but we do want to answer the question of how do we best serve the community,” Handy said. “And for the first time, in the early part of the year, we were like, holy shit, we can’t keep up with all of the stuff that people need from us.”

The company plans to expand the team from 25 to 50 employees in 2020 and with those, the team plans to improve and expand the product, especially its IDE for data analysts, which Handy admitted could use a bit more polish.

Fighting Coronavirus with Big Data


This post is by Julie Shah from HBR.org

We need to direct computing power toward finding a solution.

How to be a great data storyteller?


This post is curated by Keith Teare. It was written by Claire Wang. The original is [linked here]

It is as much a science as it is an art

Data storytelling seems to be the buzz words these days. Interestingly, even among the very experienced analysts I know, this is one area where people continue to show a lack of confidence. This is something I am also learning and discovering every day. However, let me share with you my approach, and hope that it gives you some ideas to apply to your work.

The essential components of a good story

To be a great storyteller, it is worthwhile to spend some time to understand the essential components of a good story: A setting, a twist, and a resolution. Pretty much every story you read follows this format. Let’s take Cinderella for example.

The setting

Cinderella lives a very happy life with her mom, dad and some animal friends. One day, Mom passed away. Dad re-married an evil stepmother with two evil stepsisters.

The twist

Unfortunately, Dad passed away too.

The resolution

Met a prince. Married him and live happily ever after.

Let’s keep this in mind and park it temporarily for now. I want to briefly talk about the essential components of a good business recommendation.

The essential components of a good business recommendation

Unlike the essential components of a good story, which is quite universally agreed upon. Depending on who you talk to, you might get a slightly different version of what one thinks makes up a good business recommendation. In my view, there are only two things that matter: A clear problem Continue reading “How to be a great data storyteller?”

What’s the Best Approach to Data Analytics?


This post is by Tom O’Toole from HBR.org

There are five ways companies tend to think about it. One is better than the others.

Use Data to Answer Your Key Business Questions


This post is by Kevin Troyanos from HBR.org

Activating your analytics should be a cross-team effort.

Use Data to Answer Your Key Business Questions


This post is by Kevin Troyanos from HBR.org

Activating your analytics should be a cross-team effort.

The importance of customer segmentation in SaaS

Why cherry-picking is sometimes OK and why you can’t shave everything over a comb. 😉

Do You Understand the Variance In Your Data?

Analytics has to be about more than averages.