Berlin-based y42 (formerly known as Datos Intelligence), a data warehouse-centric business intelligence service that promises to give businesses access to an enterprise-level data stack that’s as simple to use as a spreadsheet, today announced that it has raised a $2.9 million seed funding round led by La Famiglia VC. Additional investors include the co-founders of Foodspring, Personio and Petlab.

The service, which was founded in 2020, integrates with over 100 data sources, covering all the standard B2B SaaS tools from Airtable to Shopify and Zendesk, as well as database services like Google’s BigQuery. Users can then transform and visualize this data, orchestrate their data pipelines and trigger automated workflows based on this data (think sending Slack notifications when revenue drops or emailing customers based on your own custom criteria).

Like similar startups, y42 extends the idea data warehouse, which was traditionally used for analytics, and helps businesses operationalize this data. At the core of the service is a lot of open source and the company, for example, contributes to GitLabs’ Meltano platform for building data pipelines.

y42 founder and CEO Hung Dang.

“We’re taking the best of breed open-source software. What we really want to accomplish is to create a tool that is so easy to understand and that enables everyone to work with their data effectively,” Y42 founder and CEO Hung Dang told me. “We’re extremely UX obsessed and I would describe us as no-code/low-code BI tool — but with the power of an enterprise-level data stack and the simplicity of Google Sheets.”

Before y42, Vietnam-born Dang co-founded a major events company that operated in over 10 countries and made millions in revenue (but with very thin margins), all while finishing up his studies with a focus on business analytics. And that in turn led him to also found a second company that focused on B2B data analytics.

Image Credits: y42

Even while building his events company, he noted, he was always very product- and data-driven. “I was implementing data pipelines to collect customer feedback and merge it with operational data — and it was really a big pain at that time,” he said. “I was using tools like Tableau and Alteryx, and it was really hard to glue them together — and they were quite expensive. So out of that frustration, I decided to develop an internal tool that was actually quite usable and in 2016, I decided to turn it into an actual company. ”

He then sold this company to a major publicly listed German company. An NDA prevents him from talking about the details of this transaction, but maybe you can draw some conclusions from the fact that he spent time at Eventim before founding y42.

Given his background, it’s maybe no surprise that y42’s focus is on making life easier for data engineers and, at the same time, putting the power of these platforms in the hands of business analysts. Dang noted that y42 typically provides some consulting work when it onboards new clients, but that’s mostly to give them a head start. Given the no-code/low-code nature of the product, most analysts are able to get started pretty quickly  — and for more complex queries, customers can opt to drop down from the graphical interface to y42’s low-code level and write queries in the service’s SQL dialect.

The service itself runs on Google Cloud and the 25-people team manages about 50,000 jobs per day for its clients. the company’s customers include the likes of LifeMD, Petlab and Everdrop.

Until raising this round, Dang self-funded the company and had also raised some money from angel investors. But La Famiglia felt like the right fit for y42, especially due to its focus on connecting startups with more traditional enterprise companies.

“When we first saw the product demo, it struck us how on top of analytical excellence, a lot of product development has gone into the y42 platform,” said Judith Dada, General Partner at LaFamiglia VC. “More and more work with data today means that data silos within organizations multiply, resulting in chaos or incorrect data. y42 is a powerful single source of truth for data experts and non-data experts alike. As former data scientists and analysts, we wish that we had y42 capabilities back then.”

Dang tells me he could have raised more but decided that he didn’t want to dilute the team’s stake too much at this point. “It’s a small round, but this round forces us to set up the right structure. For the series, A, which we plan to be towards the end of this year, we’re talking about a dimension which is 10x,” he told me.

Fetcher, a startup that promises to make the recruiting process easier while also diversifying the candidate pool, is announcing that it has raised $6.5 million in Series A funding.

Originally known as Scout, the New York startup was founded by CEO Andres Blank, CPO Chris Calmeyn and engineering directors Javier Castiarena and Santi Aimetta.

Blank told me that Fetcher automates parts of recruiters’ jobs, namely finding job candidates and sending the initial outreach emails. When I wondered whether that just leads to more spammy recruiting messages, he said that Fetcher emails actually result in “a very good response rate” because they’re targeted at the right candidates.

“The reality is that if you’re looking for a job, you don’t need an email to be so amazing, and if you’re a recruiter, you don’t want to spend 10 minutes thinking about what to write to each candidate,” he said.

He also described Fetcher’s approach as a “human in the loop” approach. Yes, the initial outreach is automated, but then the recruiter handles the conversations with candidates who respond.

Image Credits: Fetcher

“By automating both the sourcing [and] outreach sides of recruiting, Fetcher reduces the amount of time a recruiter spends in front of a computer searching for candidates, making a recruiter’s job more balanced, strategic and impactful, all while continuing to build a robust, diverse pipeline for the company,” Blank wrote in a follow-up email.

He also suggested that automated sourcing allows recruiters to reach a much more diverse candidate pool than they would through traditional methods. For example, he sent me a case study in which Fetcher helped video collaboration startup Frame.io hire 11 new employees in less than 12 months, nine of whom were women and/or underrepresented minorities.

“Fetcher has freed up time and given us the capacity to diversify our pipeline more organically,” said Anna Chalon, Frame.io’s senior director of talent and diversity, equity and inclusion, in a statement. “This has allowed us to make some incredible hires, mostly from underrepresented groups, over the last year.”

Blank added that after Fetcher has seen its revenue increase every month since July of last year, owing to shrinking recruiting teams needing to be able to do more with fewer resources, as well as a greater corporate focus on the aforementioned diversity, equity and inclusion.

Fetcher has now raised a total of $12 million. The Series A was led by G20 Ventures, with participation from KFund, Slow Ventures and Accomplice. Blank said he’s planning to double the employee count (currently 80) by the end of the year and to build out additional analytics (including diversity analytics) and CRM tools.

Organizations spend ungodly amounts of money — millions of dollars — on business intelligence (BI) tools. Yet, adoption rates are still below 30%. Why is this the case? Because BI has failed businesses.

Logi Analytics’ 2021 State of Analytics: Why Users Demand Better survey showed that knowledge workers spend more than five hours a day in analytics, and more than 99% consider analytics very to extremely valuable when making critical decisions. Unfortunately, many are dissatisfied with their current tools due to the loss of productivity, multiple “sources of truth,” and the lack of integration with their current tools and systems.

Throughout my career, I’ve spoken with many executives who wonder why BI continues to fail them, especially when data discovery tools like Qlik and Tableau have gained such momentum. The reality is, these tools are great for a very limited set of use cases among a limited audience of users — and the adoption rates reflect that reality.

Data discovery applications allow analysts to link with data sources and perform self-service analysis, but still come with major pitfalls. Lack of self-service customization, the inability to integrate into workflows with other applications, and an overall lack of flexibility seriously impacts the ability for most users (who aren’t data analysts) to derive meaningful information from these tools.

BI platforms and data discovery applications are supposed to launch insight into action, informing decisions at every level of the organization. But many are instead left with costly investments that actually create inefficiencies, hinder workflows and exclude the vast majority of employees who could benefit from those operational insights. Now that’s what I like to call a lack of ROI.

Business leaders across a variety of industries — including “legacy” sectors like manufacturing, healthcare and financial services — are demanding better and, in my opinion, they should have gotten it long ago.

It’s time to abandon BI — at least as we currently know it.

Here’s what I’ve learned over the years about why traditional BI platforms and newer tools like data discovery applications fail and what I’ve gathered from companies that moved away from them.

The inefficiency breakdown is killing your company

Traditional BI platforms and data discovery applications require users to exit their workflow to attempt data collection. And, as you can guess, stalling teams in the middle of their workflow creates massive inefficiencies. Instead of having the data you need to make a decision readily available to you, instead, you have to exit the application, enter another application, secure the data and then reenter the original application.

According to the 2021 State of Analytics report, 99% of knowledge workers had to spend additional time searching for information they couldn’t easily locate in their analytics solution.

Confluence, Atlassian’s wiki-like collaborative workspace, has been around for more than 15 years, and is often a core knowledge-sharing tool for the companies that implement it. But for the most part, Confluence is a business tool and looks like it, with walls of text and the occasional graph, table or image. But user expectations have changed, and so it’s maybe no major surprise that Atlassian is now bringing a stronger emphasis on design to the service.

Today’s update, for example, brings to the service features like cover images, title emojis and customizable space avatars (that is, “icons that denote a ‘space’ or section of Confluence”). The team also recently introduced smart links, which allow you to paste links from services like YouTube and Trello and have the service immediately recognize them and display them in their native format. Other new features include the ability to schedule when a new page is published and the ability to convert pages to blog posts (because, as it turns out, Atlassian has seen a bit of a resurgence in corporate blogging — mostly for internal audiences — during the pandemic).

Image Credits: Atlassian

“We ended up doing something that we called ‘love sprint,’ where we prioritize about 30 features for the enhancements, which are all — if you think about the themes — about how you design information in this world where you have to read more, where you have to write more,” Natalia Baryshnikova, the head Of Product Management for Atlassian’s Confluence Experience Group, told me. “And there’s the attention span that’s kind of pushing its limits. So how do you design for that situation? How do you discover our content?”

Baryshnikova tells me that the team took a close look at how content production, management and delivery works in the social media world. But some of the new features are also purely a reaction to a changing work environment. Take the ability to schedule when pages are published, for example. Employees who work from home may work especially late or early right now, for example, in order to prioritize childcare. But they still want the content they produce to be seen inside the company, and that can be hard when you would otherwise publish it at 11 p.m., for example.

Image Credits: Atlassian

And having your content get noticed is getting harder because Confluence usage has dramatically increased in the last 12 months. As Atlassian noted today, more than 60,000 companies are now using the service. And inside those companies, those users are also far more active than ever before. The number of Confluence pages created from March 2020 to March 2021 increased by more than 33%. The average user now creates 11% more pages, but the product’s superusers have often doubled or tripled their output.

The use of Confluence has also helped many companies reduce their number of meetings, but as Baryshnikova noted, “not only are pages competing with meetings — but pages are competing with pages.” So using good graphics, for example, is a way for a user’s content to stand out in the noise of corporate content production. Which, I have to admit, strikes me as a somewhat strange dynamic. But I guess that just like on the web, in order to stand out in a corporate environment, you have to make the documents you produce stand out in order to get noticed. Maybe that — as well as the lack of watercooler conversations — is also the reason corporate blogging is seeing an uptick right now.