When Cloudera announced its sale to a pair of private equity firms yesterday for $5.3 billion, along with a couple of acquisitions of its own, the company detailed a new path that could help it drive back toward relevance in the big data market.

When the company launched in 2008, Hadoop was in its early days. The open-source project developed at Yahoo three years earlier was built to deal with the large amounts of data that the internet pioneer generated. It became increasingly clear over time that every company would have to deal with growing data stores, and it seemed that Cloudera was in the right market at the right time.

And for a while things went well. Cloudera rode the Hadoop startup wave, garnering a cool billion in funding along the way, including a stunning $740 million check from Intel Capital in 2014. It then went public in 2018 to much fanfare.

But the markets had already started to shift by the time of its public debut. Hadoop, a highly labor-intensive way to manage data, was being supplanted by cheaper and less complex cloud-based solutions.

“The excitement around the original promise of the Hadoop market has contracted significantly. It’s incredibly expensive and complex to get it working effectively in an enterprise context,” Casey Aylward, an investor at Costanoa Ventures told TechCrunch.

The company likely saw that writing on the wall when it merged with another Hadoop-based company, Hortonworks, in 2019. That transaction valued the combined entity at $5.2 billion, almost the same amount it sold for yesterday, two years down the road. The decision to sell and go private may also have been spurred by Carl Icahn buying an 18% stake in the company that same year.

Looking to the future, Cloudera’s sale could provide the enterprise unicorn room as it regroups.

Patrick Moorhead, founder and principal analyst at Moor Insight & Strategies, sees the deal as a positive step for the company. “I think this is good news for Cloudera because it now has the capital and flexibility to dive head first into SaaS. The company invented the entire concept of a data life cycle, implemented initially on premises, then extended to private and public clouds,” Moorhead said.

Adam Ronthal, Gartner Research VP, agrees that it at least gives Cloudera more room to make necessary adjustments to its market strategy as long as it doesn’t get stifled by its private equity overlords. “It should give Cloudera an opportunity to focus on their future direction with increased flexibility — provided they are able to invest in that future and that this does not just focus on cost cutting and maximizing profits. Maintaining a culture of innovation will be key,” Ronthal said.

Which brings us to the two purchases Cloudera also announced as part of its news package.

If you want to change direction in a hurry, there are worse ways than via acquisitions. And grabbing Datacoral and Cazena should help Cloudera alter its course more quickly than it could have managed on its own.

“[The] two acquisitions will help Cloudera capture some of the value on top of the lake storage layer — perhaps moving into different data management features and/or expanding into the compute layer for analytics and AI/ML use cases, where there has been a lot of growth and excitement in recent years,” Aylward said.

Chandana Gopal, research director for the future of intelligence at IDC, agrees that the transactions give Cloudera some more modern options that could help speed up the data-wrangling process. “Both the acquisitions are geared towards making the management of cloud infrastructure easier for end-users. Our research shows that data prep and integration takes 70%-80% of an analyst’s time versus the time spent in actual analysis. It seems like both these companies’ products will provide technology to improve the data integration/preparation experience,” she said.

The company couldn’t stay on the path it was on forever, certainly not with an activist investor breathing down its neck. Its recent efforts could give it the time away from public markets it needs to regroup. How successful Cloudera’s turnaround proves to be will depend on whether the private equity companies buying it can both agree on the direction and strategy for the company, while providing the necessary resources to push the company in a new direction. All of that and more will determine if these moves pay off in the end.

Cloudera was once one of the hottest Hadoop startups, but over time the shine has come off that market, and today it went private as KKR and Clayton, Dubilier & Rice, a pair of private equity firms, announced they intended to purchase Cloudera for $5.3 billion. The company has a market cap of around $3.7 billion.

Cloudera and Hortonworks, two key startups in the Hadoop space, merged in 2018 for $5.2 billion. Cloudera was likely under pressure from activist investor Carl Icahn, who took an 18% stake in the company in 2019 and now stands to gain from the sale, which the company stated represented a 24% premium for shareholders at $16 a share. Prior to the market opening this morning, the stock was sitting at $12.86.

Back in the day, about a decade ago, when Hadoop was the way to process big data, venture money was pouring into the space. Over time it lost some of its glow. That’s because it was highly labor intensive, and companies began moving to the cloud and looking at software services that did more of the work for them. More modern technologies like data lakes began replacing it and the company recognized that it must change its approach to survive in the modern data processing marketplace.

Cloudera CEO Rob Bearden sees the transaction as a way to do just that. “We believe that as a private company with the expertise and support of experienced investors such as CD&R and KKR, Cloudera will have the resources and flexibility to drive product-led growth and expand our addressable market opportunity,” Bearden said in a statement.

While there is a lot of executive jargon in that statement, it basically means that the company hopes that these private equity firms can give it some additional financial resources to move toward a more modern approach for processing large amounts of data.

While it was at it, Cloudera also announced a couple of acquisitions of its own to help it move toward that modernization goal. For starters, it grabbed Datacoral, a startup that abstracts away the infrastructure needed to build a data pipeline without using code. It also acquired Cazena, a startup that helps customers build cloud data lakes, giving the company a more modern approach to processing big data. Bearden sees both of these services helping Cloudera reposition itself in the big data self-service market

“Both businesses will enable our combined customers to enjoy a reduction in complexity and faster time to value for their data initiatives, leading to improved insights, faster innovation, and stronger engagements with their customers and partners,” Bearden said in a statement.

Cloudera went public in 2018, closing at $18.09 a share after raising $1 billion. The vast majority of that was a $740 million investment from Intel Capital in 2014. It’s worth noting that Cloudera bought Intel’s stake in the company at the end of last year for $314 million.

Hortonworks raised another $248 million. A third Hadoop startup, MapR, raised $280 million. The company’s assets were sold rather unceremoniously to HPE in 2019 for a price pegged at under $50 million, showing just how far the market has fallen since its earlier glory days.

The Cloudera deal includes a brief “go shop” provision that allows it to continue to look for a better deal. It’s doubtful it will find one, and if it doesn’t the transaction with KKR and CD&R is expected to close in the second half of this year subject to typical regulatory review. The company will announce earnings later today.

Customers have been “experiencing” business since the ancient Romans browsed the Forum for produce, pottery and leather goods. But digitization has radically recalibrated the buyer-seller dynamic, fueling the rise of one of the most talked-about industry acronyms: CX (customer experience).

Part paradigm, part category and part multibillion-dollar market, CX is a broad term used across a myriad of contexts. But great CX boils down to delighting every customer on an emotional level, anytime and anywhere a business interaction takes place.

Optimizing CX requires a sophisticated tool stack. Customer behavior should be tracked, their needs must be understood, and opportunities to engage proactively must be identified. Wall Street, for one, is taking note: Qualtrics, the creator of “XM” (experience management) as a category, was spun-out from SAP and IPO’d in January, and Sprinklr, a social media listening solution that has expanded into a “Digital CXM” platform, recently filed to go public.

Thinking critically about customer experience is hardly a new concept, but a few factors are spurring an inflection point in investment by enterprises and VCs.

Firstly, brands are now expected to create a consistent, cohesive experience across multiple channels, both online and offline, with an ever-increasing focus on the former. Customer experience and the digital customer experience are rapidly becoming synonymous.

The sheer volume of customer data has also reached new heights. As a McKinsey report put it, “Today, companies can regularly, lawfully, and seamlessly collect smartphone and interaction data from across their customer, financial, and operations systems, yielding deep insights about their customers … These companies can better understand their interactions with customers and even preempt problems in customer journeys. Their customers are reaping benefits: Think quick compensation for a flight delay, or outreach from an insurance company when a patient is having trouble resolving a problem.”

Moreover, the app economy continues to raise the bar on user experience, and end users have less patience than ever before. Each time Netflix displays just the right movie, Instagram recommends just the right shoes, or TikTok plays just the right dog video, people are being trained to demand just a bit more magic.

Artificial intelligence is becoming an increasingly common part of how customer service works — a trend that was accelerated in this past year as so many other services went virtual and digital — and today a startup that has built a set of low-code tools to help enterprises integrate more AI into their customer service processes is announcing some funding to fuel its growth.

Cognigy, which provides a low-code conversational AI platform that notably can be used flexibly across a range of applications and geographies — it supports 120 languages; it can be used in external or internal service applications; it can support voice services but also chatbots; it provides real-time assistance for human agents and usage analytics or fully automated responses; it can integrate with standard call center software, and also with RPA packages; and it can be run in the cloud or on-premise — has closed a round of $44 million, funding that it will be using to continue scaling its business internationally.

Insight Partners is leading the Series B investment, with previous backers DN Capital, Global Brain, Nordic Makers, Inventures and Digital Innovation and Growth also participating. The Dusseldorf-based company had previously only raised $11 million and spent the first several years of business bootstrapped.

Cognigy is not disclosing its valuation but it has up to now built up a concentration of customers in areas like transportation, e-commerce and insurance and counts a number of big multinational companies among its customer list, including Lufthansa, Mobily, BioNTech, Vueling Airlines, Bosch and Daimler, with “thousands” of virtual assistants now powered by Cognigy live in the market.

With 25% of Cognigy’s business already coming from the U.S., the plan now is to use some funding to invest in building out its service deeper into the U.S., Asia and across more of Europe, CEO and founder Philipp Heltewig said in an interview.

“Conversational AI” these days appears in many guises: it can be a chatbot you come across on a website when you’re searching for something, or it can be prompts provided to agents or salespeople, information and real-time feedback to help them do their jobs better. Conversational AI can also be a personal assistant on your company’s HR application to help you book time off or deal with any number of other administrative jobs, or a personal assistant that helps you use your phone or set your house alarm.

There are a number of companies in the tech world that have built tools to address these various use cases. Specifically in the area of services aimed at enterprises, some of them, like Gong, are raising huge money right now. What is notable about Cognigy is that it has built a platform that is attempting to address a wide swathe of applications: one platform, many uses, in other words.

Cognigy’s other selling point is that it is playing into the new interest in low- and no-code tools, which in Cognigy’s case makes the integration of AI into a customer assistance process a relatively easy task, something that can be built not just by developers, but data scientists, those working directly on conversation design, and nontechnical business users using the tools themselves.

“The low-code platform helps enterprises adopt what is otherwise complex technology in an easy and flexible way, whether it is a customer or employee contact center,” said Heltewig. As you might expect, there are some direct competitors in the low- and no-code conversational AI space, too, including Ada, Talkie, Snaps and more.

Flexibility seems to be the order of the day for enterprises, and also the companies building tools for them: it means that a company can grow into a larger customer, and that in theory Cognigy will also evolve the platform based on what its customers need. As one example, Heltewig pointed out that a number of its customers are — contrary to the beating drum and march you see every day toward cloud services — running a fair number of applications on-premises, since this appears to be a key way to ensure the security of the customer data that they handle.

“Lufthansa could never run its customer services in the cloud because they handle a lot of sensitive data and they want full ownership of it,” he noted. “We can run cloud services and have a full offering for those who want it, but many large enterprises prefer to run their services on premises.”

Teddie Wardi, an MD at Insight, is joining the board with this round. “We are thrilled to be leading Cognigy’s Series B as the company continues on their ScaleUp journey,” he said in a statement. “Evident by their strong customer retention, Cognigy has created an essential product for global businesses to improve their customer experience in an efficient and effortless manner. With the new funding, Cognigy will be able to expand their leadership position to reach new markets and acquire more customers.”