## Challenges
With a data stream of billions of events per day, having the right solution in place to analyze customer data and share trusted insights is key to Branch’s continued success. 

Given the company’s hypergrowth, different teams ended up leveraging different SQL editors and IDEs in silos, so there wasn’t a unified, cross-department solution to easily understand and interpret data to inform business decisions. This meant that Branch’s technical teams, across engineering, data, and product, each had their own way of writing queries – leading to different insights to the same business questions.

“My team operates like a startup within Branch. Our challenge was mostly data and technology-driven” says **Fabi Prabhakar, Senior Director of Engineering at Branch**. “We look at data all day long to answer questions around customer engagement, revenue, conversion, etc.  We used DBeaver, which was helpful, but it was hard to share and discuss results across teams.”

As a fast, nimble team within a growing organization, Fabi was looking for a unified, collaborative SQL editor in which they could easily discover the data in their schemas, centralize and standardize their queries, and foster a more thorough understanding of business insights across the organization. Other than these challenges around silos and data hygiene, not having a unified solution also ate up precious employee time and productivity.

Ultimately, not having a standardized way to share queries caused friction between technical and business teams. Fabi explains, “because we didn’t have a shared common language or common queries across teams, the first 15 minutes of every data meeting was spent figuring out who had the right query.”  
Senior Data Scientist Ling Li shares these sentiments with Fabi, citing the potential for SQL collaboration and governance as an opportunity for the company to improve data accuracy and productivity. “If everyone could easily access the same query, they’d be less likely to make mistakes as a whole. That means time savings on shipping the right insights and data products.”

Fabi and team boiled down their needs to find a data collaboration tool that could help them: 

- Easily find standardized data that would correctly inform business decisions 
- Improve cross-departmental collaboration, communication, and strategy
- Accurately report findings to stakeholders 
- Improve self-service by onboarding new team members faster with readily available queries
- Rely less on tools that create silos to reduce collaboration overhead
- Provide line of sight into what data was being analyzed by whom, so that cross-departmental team members could leverage each others’ queries and collaborate in real time to improve insight throughput

## Solution
“A colleague of mine discovered PopSQL and told me he thought it could solve our problems,” Fabi recalls. “We wanted a formalized way to look at data, share it, and have internal stakeholders trust it.” 

Shortly after evaluating PopSQL, Fabi shares,  “I couldn't find another tool that was as pricing friendly _and_ did what we needed the way PopSQL does. We couldn’t find a comparable solution to PopSQL with regard to the collaboration either.”

During their evaluation of PopSQL, several functions within the organization used PopSQL to learn more about their customers. This included individuals in sales, business development, product owners, and data scientists, so everyone could get on the same page.  They answered questions like: 

- Are customers successful or not?
- What do click-through rates (CTR) look like on each site and each link?
- Why is the click-through rate lower or higher in this country or state?
- Are customers integrating our solutions properly?

Each department was now able to more easily understand the underlying data and share their findings. With PopSQL, visibility into data manifested in big ways for productivity and data trust.

## Results

Fabi estimates at least a **25% savings in time and resources**, due to easier navigation of data sets, more productive meetings, less time spent searching for queries, and better trust. The ability to collaborate in one unified workspace has created better cross-functional alignment with fewer hiccups.

Ling estimates with this streamlined collaboration workflow “analysts save several hours a day with PopSQL by not having to rewrite queries or waste time searching for a query in docs, email, or on Slack.  We also save time by not having to jump on unnecessary Zoom calls to screen share queries.”

The one critical benefit that PopSQL unlocked for Branch as a whole was faster data discovery by having an immediate lens into customer data, identifying skewed data, and acting on it quickly. 

“We might get a note from a customer like ‘Is this CTR off?’. Our team can now immediately dive in and look at it in PopSQL”, shares Fabi. “The most useful thing is having a strong starting point on what we think is the right way to look at the data. Sometimes seeing who wrote the query in PopSQL’s UI is a good validator. Having a source of truth to start with is so important. We now always know where to start with PopSQL.”

## 


How Branch Builds Data Trust with PopSQL

Senior Director of Engineering

Senior Data Scientist

Because we didn’t have a shared common language or common queries across teams, the first 15 minutes of every data meeting was spent figuring out who had the right query.

## **Challenges**
In late 2020, Mike Doll, Udacity’s Head of Data & Analytics, invited his team to solve a challenge that had bubbled up around SQL collaboration, namely the proliferation of tools on local machines. 

When he first joined the company at the tail end of 2019, his data team of scientists, analysts and engineers were using a range of separate freeware SQL editors including [Chartio](https://www.trustradius.com/products/atlassian-chartio/reviews), Dbeaver, and editors that were strictly for Mac or that only supported a handful of databases the company used across its business. It was clear to Mike and his team that the company needed to improve their data stack.  

Anima Sharma, Udacity’s Director of Analytics, recalls that “it was difficult having everyone in different tools: Jupyter for data science, Chartio for analysts, Dbeaver for data engineers”. Furthermore, the tools themselves each had their own limitations. “Jupyter was a bit too advanced for analysts, Dbeaver’s UI was not friendly or easy to use, and Chartio didn’t provide the ability to show tables and columns within the schemas across our three databases (Redshift, Postgres, Athena),” she continues. 

Put together, this fragmentation made SQL development at Udacity slow and difficult as it also led to a lack of consistency and efficiency in querying data. Individual teams and users were writing SQL on their own, getting different answers, and often wasting time rewriting redundant queries that other teammates had already written. 

The situation came to a head when Mike saw a lot of copy/pasting of SQL queries in his data team’s Slack channel and repeat questions such as: 

- _Is this the latest query? _
- _I found a similar query, but with different results – which is correct?_
- _I need help with this query, can someone hop on a Zoom call and show me what I’m doing wrong? _

Mike’s team had played a critical role to date in building a culture of consistency, accuracy, and trust around data at Udacity. So as soon as he caught early signs of that trust eroding, he saw an opportunity to build and consolidate a more efficient and effective data culture by thinking strategically about what tool his team _should_ be using to stay on the same page. 

## **Solutions**
Mike decided to move forward with PopSQL in early 2021. “There weren’t any tools on the market with a comparable solution,” he recalls.

From a collaboration perspective, PopSQL’s core features around ​​folders, charting, autosave, version history, easy-share URL links, and comments have been critical in helping support his growing data team’s need to get insights and ship data products fast. 

To support the enterprise-level needs of Udacity’s IT team, PopSQL’s single sign-on (SSO) integration has enabled their data team to securely log into their workspace, while also leveraging the “shared credentials” feature to provide them with instant access to the database connections they need, without spending days hunting for and receiving said credentials to simply do their work. 

Additionally, every user could now leverage PopSQL’s Data Catalog feature to easily find and search for data across their schemas, tables and columns, with rich metadata around table and column popularity like “Top Users” for tables, and common joins to improve team productivity and output. 

## **Results**
After a little over 1 year of leveraging PopSQL, Udacity’s data team has been able to:

- Save 20-25% of Data Science, Data Analyst, and Data Engineers’ time
- Ship their data layer rebuild to the entire company in one quarter, instead of two or more
- Enable end users with an immaculate and comprehensive understanding of their databases and data sources
- Increase throughput of insights by answering more critical business questions faster 

“Testing our latest Datamart product has been super quick with PopSQL. We were able to consolidate data from 1,000 production tables to a set of 150 curated tables in a single quarter, thanks to PopSQL,” shares Anima Sharma. In addition, PopSQL enables Udacity’s data teams to quickly run ad hoc analyses and get deep into the data to help inform better decision making. 

For Anima’s team, which focuses on the learner’s experience and the enterprise side of the business, PopSQL has been instrumental in understanding learner outcomes and improving their overall experience in Udacity. In one specific instance, the insights generated using PopSQL even helped _prevent_ raising false alarms on usage data. 

“Recently we were looking at a metric to understand product utilization rate. We saw that the overall trend was down and were wondering if this was a red signal that needs to be raised to our executive team. However, before raising alarms, we looked at this data in PopSQL, and quickly figured out that it was only two test accounts that were impacting the overall trend negatively, and therefore, there wasn’t a utilization issue across all customers.”



How Udacity streamlined their SQL development time by 25% with PopSQL

Head of Data & Analytics

Software Engineer, Data

Director of Analytics

There weren’t any tools on the market with a comparable solution

## Challenges
Darwin Homes’ business relies on the foundational queries built by a few core power SQL users to guide product, operational, and day to day decisions for their 40+ employees. Their prior business intelligence solution, Mode, was helpful for visualizations, but had several limitations due to its dashboards-focused approach:

- There was no great way to share queries and collaborate in real time
- They had limited access to governance and version control
- Mode’s pricing model was not scalable

“We came across several visualization solutions that were great for reporting, but they didn’t have a great SQL editor experience, or collaboration features. The more complex tools, like Tableau and Looker, don’t work for us.”
Darwin Homes found that while many of the business intelligence tools on the market today are helpful for end business users, they are too rigid for rapid data exploration, and typically require a dedicated employee to integrate and maintain the tool.

## Solutions
Darwin Homes' technical and business requirements were clear from the start: their COO and Co-Founder, Zachary Kinloch, needed a robust data visualization tool, a collaborative SQL editor for their core analysts, and a low-friction way for business users to consume data through email, Slack, and self-serve reports using customizable parameters. The goal was to find a solution with all three capabilities without sacrificing resources and productivity.

## Results
After a two-week trial, Darwin Homes’ core evaluation team were able to confirm that their business and technical requirements would be met by PopSQL. After 5 months of using the solution, they have:

- Lowered their costs 50% by switching from Mode
- Improved productivity and decreased time to insight
- Created a culture of data trust with wide adoption of dashboards

**“Scheduled reports with PDF attachments give our local Portfolio Managers a snapshot view of action items on their properties -- whether it’s repairs, vacancies, or price adjustments -- while they’re on the go. This has been the most efficient way for them to access data on the fly.”**

With regard to SQL editing and collaboration, the core power users have found several valuable features:

**“Version history has made it easy to go back and see what changes were made. If you see issues with the SQL statement or results, you can easily go back and revert.”**
**“Shareable queries and real time in-app collaboration are a game changer. In Mode, you would have to send a dashboard, which could have 50 queries in it. Once you find the right query, you would also have to describe where you are in your code as you’re making edits, which made it difficult to collaborate.”**



Darwin Homes improves operational efficiencies and user experience with PopSQL

Product Ops

Business Ops

COO & Co-Founder

Business Operations

Shareable queries and real time in-app collaboration are a game changer. In Mode, you would have to send a dashboard, which could have 50 queries in it. Once you find the right query, you would also have to describe where you are in your code as you’re making edits, which made it difficult to collaborate.

## Challenges
Customer data and product analytics have been critical to FactoryFix’s roadmap, customer success, and revenue growth; however, only 8 out of 40 employees had access to data due to several constraints:

- Adding more users to their previous vendors, Chartio and Mode, was cost-prohibitive: about5x the cost of PopSQL.
- Chartio and Mode didn’t quite meet the needs of two distinct user groups: SQL savvy technical users and non-technical business users.
- Both Chartio and Mode are dashboard-centric tools which made their editor challenging to use for rapid SQL iteration and collaboration.

**“Exploratory analysis in Chartio and Mode didn't happen because everything is centered around dashboards. If you want to look at a query you have to first find the dashboard and then dig in -- you can’t just search for your desired query and share it with the stakeholder you’re working with.”**

The FactoryFix team found that provisioning access to their databases was difficult, and even if stakeholders got access via MySQL Workbench, it wasn’t intuitive to use. Since access was restricted to a few users, there was a significant burden on their shoulders to answer everyone else’s questions; and in many instances, these were repeat questions.

**“The standard process was for employees to post their questions on Slack, which created bottlenecks and delays in getting questions answered.”**

## Solutions
Upon evaluating PopSQL through a free trial, [FactoryFix](https://www.factoryfix.com/) found that PopSQL was the best-fit platform to finally democratize data access for all. With PopSQL, end-users had instant access to the company’s databases, easily searched for, collaborated on, and customized queries, and had all the mission-critical dashboards at their fingertips.

PopSQL’s easy-to-use interface, coupled with its core features -- folders, advanced search, query variables, scheduled reports, version history, Slack integration, shareable queries -- made it easy for all users to get their “foot in the door” with SQL and make smarter decisions fast.

“It’s clear when using the product that it was built by people who spend a lot of time writing queries and digging into data -- it's an ergonomic experience to explore data and share insights with others.”

## Results
FactoryFix initially piloted a paid plan for their core 8 users. After a successful pilot, the team decided to expand to 30+ users just one month later. “There was a lot of excitement for other teams to get onboarded, which was dirt simple in PopSQL. Within a day, 30 people had access, knew how to navigate PopSQL and how to answer their own questions. It was painless,” explains Scoptur.

The benefits FactoryFix has received have significantly reduced costs, improved productivity, decreased time to insight, and increased the amount of data-driven product decisions:

- 5x cost savings by PopSQL instead of expensive dashboard-centric tools.
- 2-4 hours savings per analyst per week, allowing more time on strategic insights.
- Actionable, company-wide insights delivered in real time through Slack and email.
- Sales and Success can autonomously answer questions and drive positive business outcomes.

**“What makes PopSQL great is the ability to write a query, Slack it to the person who would be excited about the data, and then they can fork that query into their own and be inspired to find additional insights."**

**"Recently, a Customer Success rep received a PopSQL query from a teammate, forked the query, did their own analysis in PopSQL, and found a drop in interview acceptance rates, a key customer health metric, which wasn’t on our radar. With that new insight, we prioritized several product features to improve interview acceptance rates and decrease an account churning risk.”**


FactoryFix democratizes data access across their entire company with PopSQL

VP Product

PopSQL’s collaboration features have been game-changing and have really helped our non-technical users get comfortable with SQL and answer their own questions. It’s personally saved me 2-4 hours a week since they can now self-serve.

Meet our Customers

How Udacity streamlined their SQL development time by 25% with PopSQL

"There weren’t any tools on the market with a comparable solution"

Darwin Homes improves operational efficiencies and user experience with PopSQL

FactoryFix democratizes data access across their entire company with PopSQL

"PopSQL’s collaboration features have been game-changing and have really helped our non-technical users get comfortable with SQL and answer their own questions. It’s personally saved me 2-4 hours a week since they can now self-serve."

"Query variables make it easier for people to have access to data that matters without knowing SQL."

"With the team now all working remotely, we found it so much easier to use Shared Connections via SSH."

"No more emailing CSVs of data or wasting time re-running the same query."

"I especially love PopSQL’s UI. New users don’t find it frightening or intimidating."

"Looker has a lot of predefined things, but PopSQL gives me more flexibility for writing SQL and visualizing it straight away."

"Sharing queries saves time. We use PopSQL to write queries and pull data quickly."