Snowflake Ventures has made an investment in OpenAP, taking a minority stake in the advanced TV advertising company.
The investment by the venture capital arm of data cloud company Snowflake, will stimulate the development of OpanAP’s cross-platform, clean room data hub as the industry moves towards data-driven, audience based advertising campaigns.
“Since OpenAP’s inception, the programmers have proven that collaboration and partnership is a powerful mechanism in transforming the entire television advertising industry. Now with this partnership and investment, cross-cloud data collaboration at scale will accelerate that transformation,” said Bill Stratton, Head, Media, Entertainment & Advertising at Snowflake.
The deal gives OpenAP, owned by Fox, NBCUniversal, Paramount Global and Warner Bros.Discovery, its first non-TV publisher owner.
Financial terms were not disclosed but Snowflake’s stake in OpenAP is about 5%, according to a source familiar with the situation.
“The publishers have put significant resources into allowing their data to unlock new cross-platform use cases for advertisers and the partnership with Snowflake is a critical step forward in giving us the scale needed to build the foundation in which all cross-platform targeting and measurement will be done in the future. We are proud to expand our strategic alliance with Snowflake as we drive further innovation and growth of the marketplace,” said OpenAP CEO David Levy.
OpenAP announced it was developing its Data Hub and working with Snowflake in June.
The OpenAP Data Hub will enable access to the OpenID spine and TV data appended to the spine, including OpenAP demographic audiences, custom audiences and OpenID exposure data
Pre-built Snowflake functions will make it easier and faster to upload and distribute data, facilitating more effective cross-publisher and cross-platform planning, targeting and measurement in privacy-safe environments, OpenAP said.
“The future of video advertising will be defined by rich audience and viewing data that provides actionable insights to advertisers while protecting consumer privacy and ensuring sensitive data is not shared from party to party. By expanding the Snowflake partnership, we are putting data and identity at the center of OpenAP,” said Dan Callahan, senior VP, Data Strategy and Sales Innovation at Fox; Krishan Bhatia, President & Chief Business Officer at NBCUniversal; John Halley, President at Paramount Advertising, and Jim Keller, executive VP, Digital Ad Sales and Advanced Advertising at Warner Bros Discovery, in a joint statement. ■
John Lewis Partnership is using Snowflake’s technology platform to bring disparate data sources together and deliver analytical insight to people who work across the business.
Barry Panayi, Chief Data and Insight Officer at John Lewis, says how this tight grip on data is allowing the retailer to make faster and more effective decisions on behalf of its customers.
Panayi joined John Lewis in March 2021. While the decision to implement Snowflake pre-dated his arrival, he’s played a crucial role in ensuring the technology is embedded across the organisation. Panayi says Snowflake provides a one-stop shop for a single version of the truth at John Lewis, which is in sharp contrast to how things were in the not-so-distant past:
It’s the place to go to get data. That sounds quite simple, but data was just everywhere before. While it was controlled and we were using a lot of resources to keep track of multiple versions of things, understanding who owned the data and what it meant was difficult. Trying to get an inventory of the data we held was hard, and people were using copies for each individual use case.
Snowflake now sits at the heart of a tightly controlled data ecosystem at John Lewis. The technology provides a cloud-based platform upon which Panayi’s team can standardize data analytics tooling for users across – and even outside – the business:
People can access data, if we say they can, and we can control it. Then they can do all the cool stuff they need to do. We already share data with some suppliers because we've got that kind of relationship with the consumer-packaged goods companies.
According to Panayi, the key to the successful implementation of Snowflake is a recognition that the platform must be seen as more than a data warehouse. While the technology brings data together, he says its real strength comes in helping the business do more with information – and that’s something that can be tough for people in all kinds of positions to recognize:
Originally, I don't think we were getting everything we could out of the relationship with Snowflake. But now, we are much more on the right end of the spectrum – understanding that you can't think about Snowflake as just another data warehouse. Instead, you need to think of it completely differently, which is a real mindset shift for people, especially data engineers.
Panayi cautions that using Snowflake can be a big step change for people who are used to working with traditional data warehouse systems. Rather than cutting and pasting data from one system to another, Snowflake works across IT services to create a cloud-based system of record that can be used to drive decision-making processes:
The data engineers have learnt about Snowflake and are excited about it. Snowflake enables us to use our cloud platform like a cloud platform as opposed to just a cheaper method of storage. People must recognise that the cloud isn't just a server with a really long cable. You’ve got to think about it as something a bit different.
John Lewis’s data stack includes a range of other important technologies. As well as using Google Cloud Platform, the retailer runs Tableau business intelligence on top of Snowflake. His team also uses specialist data tools dbt and Collibra. Most coding takes place using Python and the team is beginning to explore machine-learning tools. Panayi says the team is investigating other Snowflake features but is focused on building firm foundations:
Where we are in our journey now is we need to get all our data in Snowflake and get people consuming it. I'd like a firmer integration with things like data quality and our Collibra tool, which deals with metadata and other high-level elements. I'm focused on making sure that we're doing things properly and at the right pace rather than biting off more than we can chew.
Prior to working for John Lewis, Panayi was data chief at Lloyds Banking Group. He has also worked in senior digital leadership roles at Bupa and Virgin. Having worked for a range of companies in multiple sectors, he says it’s important to enact leadership lessons from the past and build a strong, cloud-based platform for data-led change:
I've been involved in loads of these things that have crashed and burned because people try and do everything at once. So, once the data is in good shape, then we can do the next thing because just decommissioning old technology produces costs savings that are worth going after.
Panayi estimates the first stage of his strategy – getting data into good shape – will be finished during the next 12 months. Once that work is complete, his team will start thinking about how it can use some of Snowflake’s sector-specific offerings, such as the Retail Data Cloud and Snowflake Marketplace, to make more use of its data. Right now, he says the benefits of the Snowflake implantation are clear:
Everything's a lot quicker. Data scientists can work quicker and we can build data pipelines quicker. I am the risk owner for data for the whole business. I need to confidently and very quickly say where the data is and what people are doing with it. And ideally, I don't want to spend a lot of time on that. So, having it all in one place makes sense.
Panayi advises other business and IT leaders who are thinking about implementing Snowflake to focus on focus on the difference between the technology platform and traditional data warehouse technologies. Following advice from a trusted colleague to make sure he knew more about the system, he completed Snowflake certification. That’s quite a step for a senior digital leader to take but Panayi says the investment in time paid off:
It’s about getting a little bit of dirt under your fingernails until it becomes the norm because I don't think you can assume that everyone in the tech organisation will know Snowflake. Now when I go into the executive board and they ask me, ‘what is all this?’, I can explain why it's different from old-fashioned data migrations, where they probably ended up pouring millions and millions of pounds in to get a different flavour of what they already had.
Snowflake (NYSE:SNOW) is one of the few tech stocks that has strongly bounced from its summer lows. Yes, the stock has come down significantly from its all-time highs, but it has managed to hold up a lot better than the majority of tech stocks.
Accordingly, on the one hand, its multiple has already compressed. While on the other hand, still today Snowflake is very expensive. Particularly when we consider its off-balance sheet "debt", in the form of stock-based compensation.
In sum, I struggle to get bullish on this name.
For most investors, it's preposterous to consider that the next bull market could start somewhere outside of tech. We've all been indoctrinated to look for echoes of this market in other bear markets. And that tech will lead the bull by the horns.
But is there a scenario, as improbable as it seems to be today, that tech doesn't lead the next rally?
The problem with this market is that there are just too many institutions and investors that have tied themselves up to this one sector of the market.
In essence, there's too much capital running after too few ideas. And that's causing problems. Not only have these stocks become overcrowded, but any time that tech stocks stop selling off, investors are so quick to clamber back into tech stock and buy the dip.
I read a comment on SA about Snowflake selling off because it had too much debt. And this got me thinking. On the surface, of course, Snowflake is debt free. In fact, it's swimming in approximately $4 billion of cash and equivalents.
But when we dig further and consider that fiscal Q2 2023 saw approximately $230 million of stock-based compensation go out the door this made me reconsider the above question.
Before going further, note that this figure adds to Snowflake's stock-based compensation the taxes paid on the stock-based compensation while subtracting the approximately $9 million infusion from the exercise of the stock options.
Put another way, out of the $497 million in revenues that Snowflake reported in fiscal Q2 2023, 46% goes out the door in the form of stock-based compensation.
So it appears to be the case that the bulk of Snowflake's revenues, nearly half, goes to retaining executive talent. So, for shareholders in Snowflake, this sum isn't being kept in the business to grow intrinsic value.
Snowflake is a database company. Customers use its platform, on-demand, to break down data silos and perform analytics on the platform at a massive scale.
The problem with a consumption-based data model is that when the economy is strong, customers exceed their initial prearranged capacity commitment amounts. But once things cool down, customers look for ways to cut back on spending, and all variable spending becomes due for reconsideration.
To illustrate my point, even though fiscal Q2 2023 saw revenues increase by 83% y/y, deferred revenues were down from $70 million in the prior year to $13 million in the most accurate quarter.
This could just be one quarter, with lackluster deferred revenues, or it could be that customers are starting to push back and question whether the running of data analytics that currently goes through Snowflake, some portions of it could be run elsewhere?
The average business in the S&P 500 (SPY) gets priced at approximately 20x EPS, depending on interest rates. Of course, slower-growing businesses get a lower multiple and faster-growing businesses get a higher multiple.
How much higher should the multiple be for faster-growing businesses? That's where assumptions enter the discussion. It's all about the conviction that investors have in the business's ability to continue growing at above-average rates.
Presently, analysts are expecting Snowflake is able to continue growing at above 50% CAGR in fiscal 2024 (ends January 2024), before dropping to below 50% in fiscal 2025 (ends January 2025).
Thus, investors are paying approximately 180x fiscal 2025 non-GAAP EPS figures. Even if we assume that Snowflake is one of those rare breed companies Michael Mauboussin asserts the possibility of a 5-year growth rate of above 45% at 1% (page 22), even in that case, Snowflake is seriously richly valued.
I know that for many investors I'm over-intellectualizing what is inherently simple, that Snowflake's data management is unlike other businesses.
That the more enterprises use Snowflake's warehouse of data, the more valuable the data becomes, thus the stickier the platform becomes. It's a virtuous circle that will keep customers flocking back to its platform, and that's why Snowflake has net revenue retention rates far, far above even the best-of-the-breed infrastructure-as-a-service platforms.
Indeed, there's really a lot to like about its future prospects, my only question that I keep circling back to is, will shareholders be able to benefit from this investment at this valuation? And I'm not confident that's the case.
Rep. Jamie Raskin blasted former President Donald Trump as a snowflake, after he disparaged the Jan. 6 committee of pursuing a ‘witch hunt’ over him, regarding a recently issued subpoena against him.
Mr. Raskin, one of nine members of the committee investigating the 2021 Capitol riot, said Mr. Trump‘s emotions towards the 2020 election cannot change the outcome of his loss.
“They can’t say they just have a feeling. And in fact, Trump uses that too in this enormously revealing letter, where he says lots of people ‘feel’ that there was fraud. I’m sorry. Your feelings, Mr. Snowflake, cannot dictate the course of the future of the republic. No, your feelings cannot dictate our elections,” Mr. Raskin said on MSNBC.
‘Snowflake’ is often an insult launched by conservatives to describe liberals as being overly-sensitive.
Mr. Raskin‘s comments come in response to a 14-page memo released by Mr. Trump attacking the committee and reasserting his stolen election claims.
“This memo is being written to express our anger, disappointment, and complaint that with all of the hundreds of millions of dollars spent on what many consider to be a charade and with hunt,” Mr. Trump wrote in his memo.
Mr. Trump did not indicate how we would respond to the subpoena demanding he testify and provide documents to the committee over his connection to the riot.
Mr. Trump was subpoenaed by the committee last week in a rare move by Congress to issue a subpoena against a former president.
The committee is expected to produce a report on their findings before the end of the 117th Congress.
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Commercial airline company, JetBlue, is using the integrated Snowflake data stack to power insights into its customer services and operational activities.
Ashley Van Name, general manager of data engineering at JetBlue, recently explained how a tight grip on the vast amounts of data it holds is crucial for the airline. Her team turns information into insight by using a combination of Snowflake’s Data Cloud and Fivetran’s data integration service.
This combination represents the modern data stack. Data management is a complex challenge, and information comes from multiple directions and myriad sources. So, any attempt to turn both structured and unstructured data into useful insight requires a broad collection of techniques and technologies.
For the past few years, Van Name’s work has centered on a massive data consolidation effort. By using an integrated data stack that draws on a combination of systems and services, JetBlue decision-makers benefit from powerful insights that create a competitive advantage.
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“We believe that data should be looked at as a product,” said Van Name. “If you lead a product team, and you build a software tool that is consumed by an end user, then you need to ensure you are meeting their needs and building something that can make lives easier.”
JetBlue’s three-year journey to a modern data stack has involved careful integration work. Snowflake sits at the center of the stack and stores enterprise information as it would in a data warehouse. However, this cloud-based technology also integrates with a range of other services to build the reports that power decision-making processes.
JetBlue uses a variety of software-as-a-service (SaaS) applications, with data streaming into the data warehouse from ServiceNow, Qualtrics, JIRA and Salesforce. The company also uses third-party SQL servers and Oracle databases.
Van Name notes that the key to creating a single view of this information is to ensure raw data enters the Snowflake Data Cloud. That’s where Fivetran then plays a crucial facilitating role, helping the data engineers to ensure JetBlue’s data is centralized rather than siloed.
Fivetran provides a pipeline-as-a-service, which combines data from multiple sources for analysis. The service provides more than 200 source connectors that replicate information sources directly to the Snowflake Data Cloud.
From this consolidated location, JetBlue’s data engineers get to work. Van Name explained that the combination of Fivetran and Snowflake ensures employees are focused on generating insight from information rather than tinkering with the technology.
“We believe that data engineers should spend time making their data useful rather than just moving it around,” she said. “Fivetran creates this world where gone are the days of sitting and laboring over building a custom data pipeline. Instead, you can reap the benefits of the output of that pipeline with just a few button-clicks.”
JetBlue’s tactical use of Fivetran is illustrative of a new phase in the data stack. While Snowflake aims to provide a one-stop shop for executives that want to manage the large volumes of information their businesses collect, the enterprise software giant also recognizes it can’t meet this objective in isolation.
Snowflake CEO Frank Slootman explained in a talk earlier this summer how his company has goals that reach far beyond running databases in the cloud. Either through developing its own tools or — even more crucially — by working with trusted partners like Fivetran — Snowflake wants to create an integrated data stack.
“From the standpoint of the business model, it doesn’t really matter to us whether we own the tool or somebody else does,” Slootman said. “We have a very different strategy than public cloud providers who want to check every box and be able to say to customers, ‘ere’s the whole kit and caboodle.’ We’re a best-of-breed company.”
Take security, which is one of the key areas where Snowflake is investing in. Here, the aim — by working with partners such as Hunters, Panther Labs, and Securonix — is to ensure customers can pick best-of-breed applications that meet their business requirements and which run securely on the Snowflake platform.
In short, Snowflake’s vision of a modern, integrated data stack is one that uses tools to help executives at companies like JetBlue make the most of their information, regardless of who creates the tool.
As Snowflake cofounder Benoît Dageville told to VentureBeat, his company believes the key to delivering an integrated data stack in the longer term will be allowing external developers to build and run their own applications on the Snowflake platform.
“Snowflake will be mostly not be built by our employees – that’s the vision,” Dageville said. “We’re all about removing friction and democratizing things so that everyone can be an application builder.”
Back at JetBlue, Van Name said the ability to work with a specialist pipeline provider to help push data quickly to Snowflake is already paying dividends.
She noted that it is not uncommon for data engineers at other firms to spend around 40% of their time building and testing the ingestion part of the data pipeline. Since implementing Fivetran, Van Name estimates just 10% of a JetBlue data engineer’s time is spent testing, validating and making sure the data is being pushed into the warehouse.
That shift in effort means engineers can now spend 90% of their time focused on how data is consumed in useful products.
“You get the most bang for your buck from your data engineers because you can allocate them to harder, more complex data problems,” she said.
One area where JetBlue is using data to create a competitive advantage is in customer experiences. Van Name pointed to the analysis of a post-flight email survey that is sent out by its partner, Qualtrics. Once customers have entered their survey answers, the responses are logged back in Qualtrics before Fivetran’s pipeline pushes the data into Snowflake.
“This process allows us to replicate the responses very easily and quickly from our customers directly into our Snowflake Data Cloud in their raw form, so that analysts can access the information and derive insights from it,” said Van Name, who also noted the data has sponsored improvements in areas such as in-flight entertainment experiences and digital interactions.
JetBlue is also using data to boost operations maintenance. The airline runs a computerized maintenance management system via an on-premises Oracle database. It uses Fivetran’s HVR technology to replicate the mission-critical operations database in real time. Employees can then use insights from this data to make timely interventions.
“That approach decreases the amount of time it takes analysts to build reports because they have one place to go and pull the information they need,” Van Name said. “It also empowers more consistent reporting; you’re getting closer and closer to that source of truth of a certain set of information that your company cares about.”
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(Bloomberg) -- Business software pricing is starting to look less like a monthly Netflix subscription and more like your home water bill.
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Economic uncertainty and tightening budgets are accelerating a move to consumption pricing, which charges software customers based on how much they use a product rather than a recurring annual or multiyear subscription fee. The model, popularized by Snowflake Inc., is being adopted by a growing number of software makers, including C3.ai Inc. and Autodesk Inc.
Analysts have traditionally viewed pay-as-you-go as a liability for providers, figuring that customers can more quickly dial back spending when times get rough. But in the current market slowdown, consumption-model cheerleader Snowflake said it continues to attract new clients to its data storage and analytics products who want to pay just for what they need when money is tight rather than being locked into a big contract. Subscription-model stalwarts like Salesforce Inc. and ServiceNow Inc. by contrast have reported a slowdown in acquiring new business.
The slowing sales cycles helped push C3.ai, an enterprise software provider led by industry veteran Tom Siebel, to switch all new business to consumption pricing. Signing up new customers is much easier now that initial purchase is cheaper and requires less executive approval, Siebel said. “In a recession, you need to talk about pennies not millions.”
Siebel, who sold his eponymous customer relationship management company to Oracle Corp. in 2006, said the pricing transition will flatten revenue in the short term before accelerating growth. Last month, Mike Cikos, an analyst at Needham & Co., said it’s a challenge for companies to change the way they sell their products, and C3.ai’s shares are “likely to stay in limbo until we have line of sight to the other side of the transition.”
Cloud-computing providers like Amazon.com Inc., Microsoft Corp., and Alphabet Inc. have long charged customers based on how much server space is used, but this pricing model has expanded to more kinds of software services, according to a 2021 report by venture capital firm OpenView Partners. More than half of software companies said they expect to use consumption pricing by 2023, according to a survey it conducted. Other notable examples include customer communication provider Twilio Inc. and OpenAI’s image generator Dall-E.
Software stocks have been battered this year as traders bet on increasingly aggressive interest rate hikes from the Federal Reserve. The iShares expanded software ETF is down 38% this year compared with 214% drop in the broad-based S&P 500. Unprofitability, long accepted in high-growth firms, has been a particular black mark on software companies like Snowflake this year, with a basket of money-losing tech companies compiled by Goldman Sachs Group Inc. down 59%. In this economic backdrop, its unsurprising tech leaders are willing to try new pricing strategies to keep growth going.
Not every executive is convinced. Atlassian Corp. Co-CEO Mike Cannon-Brookes said the pricing model makes less sense for collaborative applications, particularly when there’s not a specific resource like server space being consumed. Customers expect a simple per-user subscription cost for workplace tools that are a part of the typical business day like Atlassian’s Trello, Cannon-Brookes said. “I don’t feel demand to move away from it.”
Consumption pricing doesn’t work as well when users are discouraged from using the service by continually climbing costs -- also known as the “taxi-meter effect” -- according to the OpenView report. They pointed toward Adecco Group AG’s platform Hired.com, where recruiters posted fewer job listings when pricing was pay-per-hire. Customers may also be put off by high cost variability and prefer a more simplified buying experience, according to the OpenView researchers.
Snowflake bills sometimes also have surprised customers. Numerous social media posts share stories of high charges from the company or trade tips on keeping costs down. Earlier this year, Snowflake executives said improvements to its products would lower customer expenses.
Usage-based pricing is less common in applications than infrastructure, but that may be changing. Autodesk, known for its architectural and manufacturing design programs, last year introduced one-day “Flex” licenses. Under this plan, AutoCAD -- one of its flagship applications -- costs $21 for each day of use compared with a standard $235-a-month subscription plan. Chief Executive Officer Andrew Anagnost said about 40% of the users of the flex pricing model are new.
“It’s a powerful tool for small businesses that can’t afford a full subscription to everything we do,” Anagnost said. “I think eventually, most everyone’s going to end up in some kind of consumption plan.”
Snowflake Chief Revenue Officer Chris Degnan started as the company’s first salesperson in 2013, and remembers it was “not easy” to sell the consumption-based product to companies that had never heard of it. Snowflake even had to build its own billing system, since most payment processors were geared toward handling subscriptions.
Today, Snowflake looks like the elder statesman of pay-for-what-you-use pricing. Degnan said he gets many executives calling him to ask about switching their companies to Snowflake’s model.
“There are going to be software-as-a-service companies that don’t make that transition that will fail,” Degnan said.
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Australian accounting software and business management platform MYOB has tapped into Snowflake and Dataiku to streamline its various datasets.
The 30-year-old company tapped into the technologies in order to gain better visibility, insights and discoverability from its various data sources.
Speaking during Snowflake’s Data Cloud World Tour in Sydney, Oliver Dwyer, head of analytics and data strategy at MYOB, said he was currently undertaking a process to ‘SaaS-ify’ the company’s operations and data management.
“As a 30-year-old start-up, we are weighed down by legacy systems, which is true of many organisations. Because of this, making sure the data is clean and usable is key,” he told an audience at Data Cloud World.
“We are blessed with a very talented team. We have five data scientists, all at the PhD level, who are absolute geniuses. We are blessed with a really good data platform team, who are focused on making sure Snowflake is fit for use and making sure we have the right datasets.
“My team is specifically focused on transforming that raw data from Snowflake and visualising on top of that data to provide insights into the rest of the business.
“Having Snowflake allows us to shift a lot of that data, harness discoverability and have confidence in that data,” he added.
As well as Snowflake’s data management solutions, MYOB also started working with Dataiku six months ago on data science and artificial intelligence (AI).
In particular, the US-founded AI company was used to help overcome MYOB’s different data silos, with Dwyer claiming that “wrangling that data into a single dataset on which to build a model is extremely difficult”.
“Dataiku is like what Tableau has been for data visualisation,” he said. “Tableau enabled you to drag and drop your datasets in order to get that visualisation. Dataiku is on that same journey. It allowed us to remove the amount of code we needed to the point of no code.
“We have had Dataiku installed for six months now and have just unlocked our first data use case which will allow us to inform a lot of the operational decisions made with an algorithm.
“Dataiku has also helped us with data exploration. It sometimes helps us discover data; find insights from the data we have got. We use Dataiku and the library of algorithms within to answer some key questions. This requires highly complex algorithms to assess different verticals.”
“Measurement is key and that’s where the value comes in – when you can go deep into the data,” he added.
In August, MYOB acquired Greentree and MYOB Advanced practices of Melbourne-based Endeavour Solutions Australia and Perth-based enterprise resource planning (ERP) specialist Addax Business Solutions.
The acquisition deal saw Endeavour Solutions Australia’s team of ERP and business intelligence specialists and Addax Business Solutions’ team of ERP and business solutions consultants join MYOB’s enterprise division.
It has also acquired its long-time partner Australian workplace financial services platform Flare.
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Some of the worst stocks to start the year could become the best as the market recovers. Many of them are found in the technology and consumer-discretionary sectors.
Five of the best examples are Apple (ticker: AAPL), Snowflake (SNOW), Home Depot (HD), Lowe’s ( LOW ), and Lululemon Athletica (LULU). Those dropped between 27% and 67% (Snowflake) from end of 2021 through the broader market’s then-2022 low in the early summer. At that point, the S&P 500 had fallen only 23%. The problem for the market was that the Federal Reserve was beginning to lift short-term and long-term interest rates to reduce high inflation by lowering economic demand.