Unlike most of its peers, Cloudera (CLDR) has not had a strong start to 2019. The big data stock just closed a massive merger and, following a disappointing earnings, is down a couple points year to date. Although it is too early to promote Cloudera from speculative stock to steady growth stock, the secular trends in big data are clear, and companies are still in the process of building data lakes to integrate analytics to every day operations. From Chief Digital Officer of Sprint (S) Rob Roy:
“Having a data-first mentality is a crucial first step, but then you need to put in place the processes and capabilities to be able to use the data. We had to first collapse data into one or two locales so we could easily extract it. We created a large Hadoop environment and fed in all the data we had: network, store, customer, site, third party, and DMP (data management platform). There was a lot of laying of pipes and foundations to allow us to start using the data.”
In order to support the next step of digital transformations, the storage and use of data from IT investments, companies need to improve their architecture to support the massive amounts of data. To do this, companies are often using Hadoop. Two of the top four Hadoop providers, Cloudera and Hortonworks (NASDAQ:HDP), are benefiting from this next stage transformation.
Hadoop, MapReduce, and data lakes are all common buzzwords relating to big data. Basically, Hadoop is needed to store data from the massive IT investments that companies have been making the last several years. Although applications such as Salesforce (CRM) offer capabilities for analytics, Hadoop is needed for cross-application or cross department analytics. For example, creating predictive analytics models that span between finance with SAP (SAP), HR with Workday (WDAY) and sales with Salesforce, which is an oversimplification of a use case.
Source: Hortonworks (link)
Currently, the new Cloudera is in the process of launching their first major offering since combining Cloudera and Hortonworks, called the Cloudera Data Platform, or CDP. From the conference call:
“In the next two quarters, we plan to deliver CDP as a public cloud service, later in the year we will offer CDP for the public cloud - for the private cloud bringing a public cloud like experience directly into the data center for enterprise customers. With CDP our existing enterprise customers will be able to easily extend their current HDP and CDH data center deployments to a native cloud service in the two most popular public clouds, AWS and Azure.
The initial release of CDP will also offer a full complement of open source data management analytic functions, including data warehousing and machine learning, all delivered as native cloud services. Ultimately, CDP will also provide a single control plane to manage all the infrastructure, data and workloads across hybrid and multi-cloud environments.”
Source: Cloudera (presentation)
Another major offering that is of interest is Cloudera DataFlow, which was an offering only Hortonworks had before. As explained on the website, DataFlow is “a scalable, real-time streaming analytics platform that ingests, curates, and analyzes data for key insights and immediate actionable intelligence.” DataFlow can be used for monitoring, predicative, and risk analytics/exception handling, which has large potential for business value, and offering expansion.
The expansion of Cloudera is pretty clear. After the integrations of the Hortonworks and Cloudera offerings, moving further downstream is a clear next step. Data analysis tools, digital workflow automation, and digital visualization are all likely future investment opportunities for Cloudera. For investors in the sector, think of companies that specialize further downstream, such as Tableau (DATA), Alteryx (AYX), R, SAS, Qlikview etc., as offerings that Cloudera will likely expand to as next steps. As the merger matures, it’s also possible that one of these downstream companies decide to expand themselves, making Cloudera an acquisition target.
Cloudera has a massive potential TAM, which includes the estimation of data analytics, storage, visualization, etc. However, the addressable market will likely involve several winners, and it is more likely their best case scenario is capturing around 10% of the market. Since the core of Cloudera is still Hadoop, moats will be focused on what vendors can provide outside of the core Hadoop platform.
Source: Cloudera (presentation)
Another reason for the low estimation of the TAM capture potential is due to vendor lock-in fears, which effects their competitors more than Cloudera. This gives an independent, focused vendor such as Cloudera an advantage over an AWS (AMZN) offering. Forrester views both companies as leaders in the industry, and also added the comment:
“We estimate that 7% of organizations have completely migrated their traditional data warehouses to big data platforms. The merger will help evolve their data platforms to support a more comprehensive data warehouse strategy that’s easier to migrate and support, especially in the hybrid-cloud environment.”
Of course, one of the big risks facing Cloudera is the lack of a low-code/no code offering. Basically, it means companies have to hire specific developers that have specializations in Hadoop, Spark, and MapReduce in order to develop and integrate Cloudera’s offerings. Currently, there’s no clear winner in making implementation easier, but whichever vendor is able to do this may become an immediate front runner. Companies such as Tableau and Alteryx are specializing in low code and no code, and Cloudera, or a competitor, will likely establish a large moat if they’re able to create solutions that developers without extensive Hadoop/MapReduce experience can handle a majority of the implementation and development. To illustrate this, Forrester listed this as a weakness for both companies pre-merger. For Hortonworks, Forrester notes:
“Customers like its flexible open source platform, multi-cloud support, data ingestion capabilities, performance and scale, and broad ecosystem of partners and tooling. However, some claim it lags in support of comprehensive data integration and requires a lot of training and understanding for complex and large deployments.”
"Customers like Cloudera's HARK platform performance, technical support, road map, continuous innovation, and partner ecosystem. However, some claim the platform's many components require highly skilled resources to deploy and operate."
Financial Health and Valuation
Guidance for the fiscal year is for a midpoint $845 million in revenue, representing a 76% growth, due to the merger. Adjusted annualized recurring revenue, ARR, is used by Cloudera to show what organic growth would be. ARR guidance for the year is 19.5% yoy growth. Similar to other companies, investors are likely hoping that this is a baseline guidance, not accounting for several new offerings in the pipeline that are launching this year.
Software companies that are growing fast and aren’t profitable often have elevated share-based compensation. Last quarter, share-based compensation was slightly under $50 million, versus $145 million in revenue. Although not a rare occurrence among unprofitable software stocks, it is still an uncomfortably large amount, over 1/3 of revenue.
Balance sheet health is strong, considering the heavy use of share-based composition and following a merger. Current assets total close to $800 million, versus total liabilities of $635 million. The merger was all-stock funded.
In terms of valuation, Cloudera lags behind several of their peers. Forward P/S is projected at 3.4, which is considerably below their albeit overvalued peers. P/S/G, using their ARR guidance, is .17, another measure much lower than their peers (I’ve mentioned in previous articles that some of the trendy software companies are close to .4 P/S/G).
Mergers tend to destroy shareholder value rather than create, which is likely one reason for the low valuation. The talent requirement for implementing Hadoop and big data offerings, along with the low adoption rates in the industry, likely mean that the data architectures needed to support big data initiatives are still in the very early innings.
I believe big data focused digitalization investments are dependent on the oft-mentioned digitalization investments happening in corporates. Because of this, the uncertainty may lead to lack of investor interest in giving a higher valuation.
Overall, similar to their industry, Cloudera is still in the early innings of their own organization growth. Margins aren’t expected to turn positive until 2021, but non-GAAP subscription gross margin for the year was 88%, which is on the high end compared to peers.
As corporates continue their massive IT spending, their next steps will be focused on how to handle the data generated from these investments. Companies are still in the early innings of big data analytics, which means it’s too early to determine what use cases, offerings, and architecture offerings will be long-term winners. However, Cloudera is one of the few pure plays in the HARK (Hadoop/Spark) space, which is the foundation for corporate big data investments. Overall, Cloudera is still a speculative investment due to their lack of near-term profitability, and the low levels of big data corporate spending. But there are still strong secular tailwinds, plus a fear of vendor lock-in, that provide favorable factors for Cloudera to succeed in capturing a large amount of their massive TAM.
Disclosure: I am/we are long CRM. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
Additional disclosure: Disclaimer: The above references an opinion and is for information purposes only. This information is general in nature and has not taken into account your personal financial position or objectives. It is not intended to be investment advice. Seek a duly licensed professional for investment advice. Past performance is not an indicator of future performance.