Cloudera’s Transition: Migrating to the Next Stage

May 15, 2018

Cloudera’s Transition: Migrating to the Next Stage

Judith Hurwitz and Jean Bozman

Cloudera was a company at the right place and at the right time when it became a leader in Hadoop analytics in the past decade. Today, it is a leader with strong brand recognition. But it is clear to anyone who has participated or observed the data management market, that change is coming to this market space – and coming fast.

To meet that challenge, Cloudera is now embarking on a major transition in its strategy that requires it to hold on to its predominant position in Hadoop analytics – and to become a provider of machine learning software supporting both on premises and public clouds. But it will have to move quickly to re-position the company. The market for machine learning software is exploding with double-digit growth. It is a highly competitive market that today is dominated by a variety of both well established businesses, and emerging venture funded vendors.

We recently attended Cloudera’s IT industry analyst event, where we met with the company’s Executives and were briefed on product and corporate strategy.

Wall Street’s Impact on Market Cap

Despite its consistent growth in quarterly revenues, Wall Street has not been kind to Cloudera. After the company’s latest earnings announcement for the fourth quarter of 2017 (April 3, 2018) – the company’s stock valuation dropped by more than 28 percent, despite experiencing over a 40% growth in year-over-year quarterly revenue. Despite Cloudera’s consistent revenue gains, losses have also increased and the company has lowered future expectations.

The New Strategy

Cloudera’s strategy is to focus on the complete data lifecycle for enterprise customers. The company is banking on its size and its deep experience in analytics to differentiate itself from the vast array of startups. It is making its transition to new market spaces with annual revenue of $360 million – and with $301 million of that in recurring software revenue. These resources will help it to push past what it considers to be a short-term decline in its market valuation – and to reach higher levels of revenue while cutting losses.

Cloudera will focus on analytics model management, data governance, data security and workload management for analytics data in hybrid clouds. This broad focus is intended to help the company differentiate itself from emerging companies. At the same time, the company is partnering with leading cloud providers, including Amazon AWS, Microsoft Azure and Google Cloud Platform (GCP) to help the company deliver capabilities on its customers’ preferred platforms.

The move to expand the Cloudera’s offerings has already begun: Cloudera has brought in new talent to help on the journey, including acquiring Fast Forward labs, a machine learning research company that develops proofs of concept (PoCs) and engages directly with customers. The company has brought in industry veterans, naming new general managers in areas such as analytics, cloud computing and machine learning.

Going Forward

Why focus on the Global 2000 accounts? The main driver is to leverage Cloudera’s considerable expertise with Hadoop to attract customers that are mature enough to have the business need to expand into new machine learning in their hybrid cloud environments. Smaller organizations are often building solutions on their own, or experimenting with free, open-source toolsets.

We believe that it will take a while for Cloudera to catch up with a robust machine learning-based market characterized by fierce vendor competition involving a range of software and systems vendors. It will be imperative to educate its existing customer base about the way those customers can leverage their existing Hadoop services by expanding into innovative machine learning initiatives.

Therefore, Cloudera’s plan is to meet customers where they are today with their enterprise data platforms. The goal is to focus on helping customers that already have a data warehouse and want to move quickly to incorporate machine learning models in a lifecycle manner. The initial focus will be to provide solutions in retail, manufacturing, financial services. Cloudera’s goal is to provide a self-services-based model so that these powerful machine learning models are accessible to the business user that has traditionally relied on a data warehouse.

Bottom Line

It is clear from Cloudera’s industry analyst meeting that the company management is fully engaged in executing on the new strategy. A focus on lifecycle management in combination with machine learning and a focus on key verticals will help Cloudera move forward. The company is clearly not starting from scratch: rather, it is leveraging its current position to expand its total available market. Its leadership is relying on its ability to provide next-generation self-service software to accelerate growth in the future.




Jean Bozman, Judith Hurwitz , , , , , , , , , , , , , , ,
About Judith Hurwitz

Judith Hurwitz is an author, speaker and business technology consultant with decades of experience.