Databricks launched its fifth open-source project today, a new tool called Delta Sharing designed to be a vendor-neutral way to share data with any cloud infrastructure or SaaS product, so long as you have the appropriate connector. It’s part of the broader Databricks open-source Delta Lake project.

As CEO Ali Ghodsi points out, data is exploding, and moving data from Point A to Point B is an increasingly difficult problem to solve with proprietary tooling. “The number one barrier for organizations to succeed with data is sharing data, sharing it between different views, sharing it across organizations — that’s the number one issue we’ve seen in organizations,” Ghodsi explained.

Delta Sharing is an open-source protocol designed to solve that problem. “This is the industry’s first-ever open protocol, an open standard for sharing a data set securely. […] They can standardize on Databricks or something else. For instance, they might have standardized on using AWS Data Exchange, Power BI or Tableau — and they can then access that data securely.”

The tool is designed to work with multiple cloud infrastructure and SaaS services and out of the gate there are multiple partners involved, including the Big Three cloud infrastructure vendors Amazon, Microsoft and Google, as well as data visualization and management vendors like Qlik, Starburst, Collibra and Alation and data providers like Nasdaq, S&P and Foursquare

Ghodsi said the key to making this work is the open nature of the project. By doing that and donating it to The Linux Foundation, he is trying to ensure that it can work across different environments. Another big aspect of this is the partnerships and the companies involved. When you can get big-name companies involved in a project like this, it’s more likely to succeed because it works across this broad set of popular services. In fact, there are a number of connectors available today, but Databricks expects that number to increase over time as contributors build more connectors to other services.

Databricks operates on a consumption pricing model much like Snowflake, meaning the more data you move through its software, the more money it’s going to make, but the Delta Sharing tool means you can share with anyone, not just another Databricks customer. Ghodsi says that the open-source nature of Delta Sharing means his company can still win, while giving customers more flexibility to move data between services.

The infrastructure vendors also love this model because the cloud data lake tools move massive amounts of data through their services and they make money too, which probably explains why they are all on board with this.

One of the big fears of modern cloud customers is being tied to a single vendor as they often were in the 1990s and early 2000s when most companies bought a stack of services from a single vendor like Microsoft, IBM or Oracle. On one hand, you had the veritable single throat to choke, but you were beholden to the vendor because the cost of moving to another one was prohibitively high. Companies don’t want to be locked in like that again and open source tooling is one way to prevent that.

Databricks was founded in 2013 and has raised almost $2 billion. The latest round was in February for $1 billion at a $28 billion valuation, an astonishing number for a private company. Snowflake, a primary competitor, went public last September. As of today, it has a market cap of over $66 billion.

Expensify may be the most ambitious software company ever to mostly abandon the Bay Area as the center of its operations.

The startup’s history is tied to places representative of San Francisco: The founding team worked out of Peet’s Coffee on Mission Street for a few months, then crashed at a penthouse lounge near the 4th and King Caltrain station, followed by a tiny office and then a slightly bigger one in the Flatiron building near Market Street.

Thirteen years later, Expensify still has an office a few blocks away on Kearny Street, but it’s no longer a San Francisco company or even a Silicon Valley firm. The company is truly global with employees across the world — and it did that before COVID-19 made remote working cool.

“Things got so much better when we stopped viewing ourselves as a Silicon Valley company. We basically said, no, we’re just a global company,” CEO David Barrett told TechCrunch. That globalism led to it opening a major office in — of all places —a small town in rural Michigan. That Ironwood expansion would eventually lead to a cultural makeover that would see the company broadly abandon its focus on the Bay Area, expanding from a headquarters in Portland to offices around the globe.

It makes sense that a company founded by internet pirates would let its workforce live anywhere they please and however they want to. Yet, how does it manage to make it all work well enough to reach $100 million in annual revenue with just a tad more than 100 employees?

As I described in Part 2 of this EC-1, that staffing efficiency is partly due to its culture and who it hires. It’s also because it has attracted top talent from across the world by giving them benefits like the option to work remotely all year as well as paying SF-level salaries even to those not based in the tech hub. It’s also got annual fully paid month-long “workcations” for every employee, their partner and kids.

Yet the real story is how a company can become untethered from its original geography, willing to adapt to new places and new cultures, and ultimately, give up the past while building the future.

On the heels of expanding its marketing call analytics platform last year to provide more insights to help those in sales, e-commerce and customer experience, Invoca is making its first acquisition to widen the net of companies that it targets. The company has acquired DialogTech, a startup that builds tools for marketers to analyze inbound phone calls and other contacts, in what TechCrunch understands to be a $100 million deal.

As part of the transaction, Santa Barbara-based Invoca will be divesting Swydo, a company that Chicago-based DialogTech acquired in 2018. Swydo — originally from The Netherlands — will remain a partner of Invoca’s, the company said.

Invoca has up to now focused on larger consumer-facing enterprises — its customers include the likes of ADT, AutoNation, DISH, TELUS and The Home Depot — providing them with an AI-based platform that lets their marketing, sales and other teams analyze calls from consumer customers and provide call tracking, coaching and other insights in real time and in the form of post-call reports to help those teams do their jobs more easily.

Gregg Johnson, Invoca’s CEO and one of a growing pool of Salesforce veterans who are reinventing the marketing and sales technology landscape, described DialogTech as “complementary” to what Invoca does, but will specifically help Invoca better target mid-market companies.

The opportunity that both Invoca and DialogTech have identified is that, despite the growth of digital media advertising, social media and other channels for brands to connect to would-be customers, inbound calls remain a very key part of how companies sell goods and services, especially when the sale is of a complex item.

“About 40% to 80% of revenues come through contact centers,” Johnson said. “Brands can do all the retargeting they want but the same strategies in digital don’t work there.”

For those working at the other end of the line, the need for tools to do their jobs better became even more pressing in the last year, a time when customers stayed home and away from physical stores, shifting all of their interactions to virtual and remote channels. Subsequently, they demanded and expected better levels of service there.

“This move enables us to be an even better partner to enterprises and agencies looking to optimize their marketing and drive sales,” said DialogTech CEO Doug Kofoid, in a statement. “Together as Invoca, our combined company will deliver an unrivaled solution for conversation intelligence, with the most innovative technology, expertise, experience, and resources in our industry.”

The combined business will become one of the bigger “martech” startups focusing on conversational insights, with 2,000 customers, more than 300 employees and on track to make more than $100 million this year in revenue. This is, however, just the tip of the iceberg: The conversational intelligence market was estimated to be worth some $4.8 billion in 2020 and is expected to balloon to nearly $14 billion by 2025.

Given how many startups we’ve seen launch in the name of better sales intelligence, it’s likely that this will not be the last piece of consolidation in the area. Combining to expand the functionality of a platform, or to expand the scale and reach of a business, or simply to bring on interesting tech that is easier to acquire than build from scratch, are three areas that will likely drive more M&A.

Invoca last raised funding in October 2019, a $56 million round just ahead of the world shifting into COVID-19 pandemic mode. Johnson confirmed that Invoca — which has to date raised $116 million from Accel, Upfront Ventures, H.I.G. Growth Partners, Morgan Stanley, Salesforce Ventures and others — is in a strong enough position as a business not to need to raise more for this acquisition.

However, I suspect that scaling up like this will help it bid for bigger money and a bigger valuation when it does, as will the fact that peers in the market like Gong (which Johnson described to me as the “B2B version of Invoca”) have seen their valuations catapult in the last year, spurred by the changes in how customers interact with businesses, and sales and marketing can work to better serve them.

PowerPoint may still dominate the landscape for presentations in many people’s minds, but some might say that legacy status also makes Microsoft’s software ripe for disruption. Now, a startup out of Berlin called Pitch has just picked up a substantial Series B of $85 million to take it on with what it believes is a more dynamic approach.

The round is being led by Lakestar and Tiger Global, with previous backers Index Ventures and Thrive Capital also participating. We understand from sources close to the company that the valuation is now at $600 million for the Berlin-based startup.

In the words of CEO and co-founder Christian Reber, the ambition is to create the “YouTube for presentations,” with the ability for people to create, collaborate on and share presentations with each other through an online-based interface.

His interest, meanwhile, in taking on Microsoft has a deeper story to it. As we have covered before, Reber’s previous startup, the planning startup Wunderlist, was acquired by Microsoft and folded into its productivity suite, only to eventually be killed off, much to Reber’s disbelief and disappointment.

Not to dwell too much in the past, the funding Pitch has now raised will be used in several areas, including hiring more people and reach. The startup has already seen good progress on the latter front. Pitch is already being used by tens of thousands of teams, it says, who have created some 125,000 workspaces on the platform. Customers include (ironically) a number of other trailblazers in the world of business productivity: Intercom, Superhuman and Notion are among the list.

The plan will be to work on bringing on more users into its freemium universe, while converting more to its Pitch Pro $10/user/month paid tier, which includes more extensions like unlimited storage, video uploads, version history and advanced permissioning. Pro already has a “couple of thousand” subscribers, Reber said, enough to prove out that “we definitely see our business model working.” Pitch is also working on rolling out an enterprise version so that it can sell Pitch into the bigger businesses and deployments that dominate usage of PowerPoint.

And the other way that Pitch plans to bring more people into the fold will be with more functionality. Along with the funding, Pitch is rolling out some new features that will include the beginnings of an ecosystem, where presentation designers and creators will be able to upload presentation templates, as well as presentations themselves, to help other people get started in creating their own presentations.

The idea here is to celebrate creators, Reber said, but it’s (at least for now) stopping short of paying them, seeing this more as a way of sharing designs and ideas in a more collaborative exchange with each other. Both, however, seem to me to be ripe opportunities down the line for building a marketplace. Creating a great pitch deck for a startup is great to share as a resource, but if you are also, say, a leadership coach who makes a living out of giving people inspiring direction on how to handle something, a pitch deck with that IP in it perhaps might not be something you’d always be willing to part with for free. (Reber says his inspiration here was the world of design forums like Dribble, where an exchange of ideas has thrived.)

Initially, the user-generated content will be selected by Pitch itself, although the plan over time will be to make it something that will be open to everyone, Reber said.

Another new feature will be presentation analytics. This will not be unlike the kind of data that people currently can apply to, say, email or web traffic to measure what people are clicking on, how long they are spending looking at content and where they are dropping off. Pitch will apply the same to its presentations — which are HTML-coded — so that those who are making them and sending them around can get a better idea of how they are performing, and even begin the process of A-B testing to try out different approaches.

Reber points out that analytics will be opt-in only: If users choose not to share that tracking, it won’t be shared, he said.

“As a German business, we have a special relationship with data privacy in the greatest sense,” he said. “We care deeply about making sure we approach features in a privacy-first way.” The idea is to make it less like spyware, and more like the kind of analytics one might have on YouTube for videos there.

Finally, it’s adding in more video features to bring in narrative recording and playback. These first will be “recorded” around the presentations themselves, but longer term, it’s likely that the feature will also have a live element, which makes a lot of sense since a lot of presentations have had their most highly trafficked exposure by way of webinars or live presentations (say, around an earnings call), where you might not only have multiple presenters talking along a slide deck, but also people feeding back, asking questions in relation to the presentation and so on.

If this all sounds a little WordPress-like, that’s not a coincidence. Reber noted that website building is something else that Pitch wants to bring into the platform. “We are experimenting with that,” he said. “In my opinion, presentations are collections of information and we want to publish them in various ways. Slides just happens to be one format. But if it’s all already written in HTML, why not build it also into a site? That will be another feature coming, and something that we will be also using the funding for.”

Indeed, that may not work for deeper content efforts (such as publications like the one you are reading right now), but would be perfectly adequate for, say, basic sites along the kind that are built on sites like Squarespace to lay out some online real estate for a small business. The scope of what you can already do, and what Pitch wants you to do, is precisely what makes this all so interesting to investors, they say.

“The exciting vision that Christian and the team at Pitch have is beyond just being a superior alternative to legacy presentation software,” said Stephen Nundy, partner at Lakestar, in a statement. “A reimagining of the entire workflow surrounding presentations is very much overdue, and when coupled with the ability to harness new data and media integrations, Pitch will lead the way in changing how stories are told. I’m very proud to be joining the board of a European company with its sights set on a truly global opportunity.”

“We are incredibly impressed by the quality of Pitch’s offering today and Christian’s vision for the future. Pitch will be a true productivity platform, and we are excited to become investors in this special company,” John Curtius, partner at Tiger Global, added.

Reber’s take on the new tools are also here:

A little over a decade has passed since The Economist warned us that we would soon be drowning in data. The modern data stack has emerged as a proposed life-jacket for this data flood — spearheaded by Silicon Valley startups such as Snowflake, Databricks and Confluent.

Today, any entrepreneur can sign up for BigQuery or Snowflake and have a data solution that can scale with their business in a matter of hours. The emergence of cheap, flexible and scalable data storage solutions was largely a response to changing needs spurred by the massive explosion of data.

Currently, the world produces 2.5 quintillion bytes of data daily (there are 18 zeros in a quintillion). The explosion of data continues in the roaring ‘20s, both in terms of generation and storage — the amount of stored data is expected to continue to double at least every four years. However, one integral part of modern data infrastructure still lacks solutions suitable for the Big Data era and its challenges: Monitoring of data quality and data validation.

Let me go through how we got here and the challenges ahead for data quality.

The value vs. volume dilemma of Big Data

In 2005, Tim O’Reilly published his groundbreaking article “What is Web 2.0?”, truly setting off the Big Data race. The same year, Roger Mougalas from O’Reilly introduced the term “Big Data” in its modern context  —  referring to a large set of data that is virtually impossible to manage and process using traditional BI tools.

Back in 2005, one of the biggest challenges with data was managing large volumes of it, as data infrastructure tooling was expensive and inflexible, and the cloud market was still in its infancy (AWS didn’t publicly launch until 2006). The other was speed: As Tristan Handy from Fishtown Analytics (the company behind dbt) notes, before Redshift launched in 2012, performing relatively straightforward analyses could be incredibly time-consuming even with medium-sized data sets. An entire data tooling ecosystem has since been created to mitigate these two problems.

The emergence of the modern data stack (example logos and categories). Image Credits: Validio

Scaling relational databases and data warehouse appliances used to be a real challenge. Only 10 years ago, a company that wanted to understand customer behavior had to buy and rack servers before its engineers and data scientists could work on generating insights. Data and its surrounding infrastructure was expensive, so only the biggest companies could afford large-scale data ingestion and storage.

Then came a (Red)shift. In October 2012, AWS presented the first viable solution to the scale challenge with Redshift — a cloud-native, massively parallel processing (MPP) database that anyone could use for a monthly price of a pair of sneakers ($100) — about 1,000x cheaper than the previous “local-server” setup. With a price drop of this magnitude, the floodgates opened and every company, big or small, could now store and process massive amounts of data and unlock new opportunities.

As Jamin Ball from Altimeter Capital summarizes, Redshift was a big deal because it was the first cloud-native OLAP warehouse and reduced the cost of owning an OLAP database by orders of magnitude. The speed of processing analytical queries also increased dramatically. And later on (Snowflake pioneered this), they separated computing and storage, which, in overly simplified terms, meant customers could scale their storage and computing resources independently.

What did this all mean? An explosion of data collection and storage.